Local control algorithm test only
1.stanley test data accomplishment 2.lqr test data accomplishment
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liuhaoyan
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.gitignore
vendored
@ -11,6 +11,5 @@ log/
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logs/
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data/
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files/
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*.csv
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*.png
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@ -1,5 +1,5 @@
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# auto drive misson center webots simulation:
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该分支修复了原LQR算法中矩阵错误问题，并对参数进行调教，增加stanley前轮转向控制算法，并适配webots仿真环境。后续实车测试优先使用该分支
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lhy本地控制测试分支，无本地控制测试需求请勿使用
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## 1, `ubuntu20.04`, `ubuntu22.04`
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## 2, 安装 `webots`
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`https://github.com/cyberbotics/webots/tags`， 版本： `ubuntu20.04： R2023a， ubuntu22.04：R2025a`
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@ -10,12 +10,12 @@ import matplotlib.pyplot as plt
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# 参数
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# ============================================================
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LOG_PATTERN = "logs/mission_center_logger*.txt"
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LOG_PATTERN = "path_visualizer.log"
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# 每 5 个完整数据取 1 个
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SAMPLE_STEP = 40
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SAMPLE_STEP = 1
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CSV_FILE = "recalculated_tracking_error.csv"
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CSV_FILE = "tracking_error.csv"
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# ============================================================
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@ -74,6 +74,9 @@ current_path_pattern = re.compile(
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r"current_path_yaw:([-+0-9.eE]+)"
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)
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yaw_command_pattern = re.compile(
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r"current_cmd_angular_z:([-+0-9.eE]+)"
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)
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# ============================================================
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# 3. 函数：角度归一化
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@ -178,6 +181,7 @@ def calculate_errors(
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# ============================================================
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all_data = []
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yaw_command_data = []
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total_raw_count = 0
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@ -202,6 +206,7 @@ for file in files:
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# --------------------------------------------------------
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pending_pose = None
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pending_yaw = None
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with file.open(
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@ -222,7 +227,11 @@ for file in files:
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line
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)
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m_yaw = yaw_command_pattern.search(line)
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if m_yaw:
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pending_yaw = float(m_yaw.group(1))
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if file_data_count % SAMPLE_STEP == 0:
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yaw_command_data.append(pending_yaw)
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if m_pose:
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pending_pose = {
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@ -351,6 +360,7 @@ for file in files:
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pending_pose = None
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print(
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f"原始完整数据：{file_data_count}"
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)
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@ -447,6 +457,12 @@ alpha_deg = np.array([
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for d in all_data
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])
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yaw_command = yaw_command_data# 确保长度一致
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print(
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f"yaw size: {len(yaw_command)}"
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)
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# ============================================================
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# 8. 计算车辆累计行驶距离
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@ -524,13 +540,16 @@ with open(
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"heading_error_deg",
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"yaw_command",
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])
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for i in range(
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len(all_data)
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):
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if i>= len(yaw_command):
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break
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writer.writerow([
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f"{distance_m[i]:.8f}",
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@ -545,6 +564,8 @@ with open(
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f"{alpha_deg[i]:.8f}",
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f"{yaw_command[i]:.8f}"
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])
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@ -630,7 +651,43 @@ plt.grid(True)
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plt.tight_layout()
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plt.show()
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# ============================================================
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# 14. yaw command rad
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# ============================================================
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plt.figure(
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figsize=(12, 5)
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)
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plt.plot(
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distance_m,
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yaw_command,
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linewidth=1.2
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)
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plt.axhline(
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0.0,
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linestyle="--",
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linewidth=0.8
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)
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plt.xlabel(
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"Distance (m)"
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)
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plt.ylabel(
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"Yaw Command (rad)"
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)
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plt.title(
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"Recalculated Yaw Command"
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)
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plt.grid(True)
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plt.tight_layout()
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plt.show()
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# ============================================================
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# 15. 车辆轨迹 + 路径点
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@ -1,50 +1,71 @@
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import csv
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import os
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import re
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import matplotlib.pyplot as plt
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import numpy as np
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import glob
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# files = [
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# "stanley_*_*_*_*.csv",
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# ]
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files = [
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"U_turn_0.32_lqr.csv",
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"U_turn_0.32_pp.csv",
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"U_turn_0.32_stanley.csv",
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"lqr_*_*_*_*_*.csv",
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]
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data = {}
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for pattern in files:
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for file in files:
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if not os.path.exists(file):
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raise FileNotFoundError(f"找不到文件: {file}")
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matched_files = glob.glob(pattern)
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distance = []
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lateral_error = []
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heading_error = []
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yaw_command = []
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if not matched_files:
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raise FileNotFoundError(
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f"找不到文件: {pattern}"
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)
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matched_files.sort(
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key=lambda x: (
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float(x.split("_")[1]), # 速度
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float(x.split("_")[2]), # 参数1
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float(x.split("_")[3]), # 参数2
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float(x.split("_")[4]), # 参数2
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float(x.split("_")[5].replace(".csv", "")) # 半径
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)
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)
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with open(file, "r", encoding="utf-8-sig", newline="") as f:
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reader = csv.DictReader(f)
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print(f"匹配到 {len(matched_files)} 个文件:")
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for file in matched_files:
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if not os.path.exists(file):
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raise FileNotFoundError(f"找不到文件: {file}")
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required = {"distance_m", "lateral_error_m", "heading_error_rad","yaw_command"}
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if not required.issubset(reader.fieldnames or []):
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raise ValueError(
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f"{file} 缺少必要列，需要: {required}，实际列: {reader.fieldnames}"
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)
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distance = []
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lateral_error = []
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heading_error = []
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yaw_command = []
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for row in reader:
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try:
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distance.append(float(row["distance_m"]))
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lateral_error.append(abs(float(row["lateral_error_m"])))
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heading_error.append(abs(float(row["heading_error_rad"])))
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yaw_command.append(float(row["yaw_command"]))
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except (ValueError, TypeError):
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continue
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with open(file, "r", encoding="utf-8-sig", newline="") as f:
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reader = csv.DictReader(f)
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name = os.path.splitext(os.path.basename(file))[0]
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data[name] = {
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"distance": distance,
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"lateral_error": lateral_error,
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"heading_error": heading_error,
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"yaw_command": yaw_command,
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}
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required = {"distance_m", "lateral_error_m", "heading_error_rad","yaw_command"}
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if not required.issubset(reader.fieldnames or []):
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raise ValueError(
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f"{file} 缺少必要列，需要: {required}，实际列: {reader.fieldnames}"
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)
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for row in reader:
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try:
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distance.append(float(row["distance_m"]))
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lateral_error.append(abs(float(row["lateral_error_m"])))
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heading_error.append(abs(float(row["heading_error_rad"])))
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yaw_command.append(float(row["yaw_command"]))
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except (ValueError, TypeError):
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continue
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name = os.path.splitext(os.path.basename(file))[0]
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data[name] = {
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"distance": distance,
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"lateral_error": lateral_error,
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"heading_error": heading_error,
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"yaw_command": yaw_command,
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}
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# 颜色由 matplotlib 自动分配，不手动指定
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names = list(data.keys())
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@ -56,21 +77,20 @@ plt.figure(figsize=(12, 6))
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for name in names:
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plt.plot(
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data[name]["distance"],
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data[name]["lateral_error"],
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data[name]["distance"][::15],
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data[name]["lateral_error"][::15],
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label=name,
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linewidth=1.5,
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)
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plt.xlabel("Distance (m)")
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plt.ylabel("Lateral Error (m)")
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plt.title("Lateral Error Comparison")
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plt.grid(True, alpha=0.3)
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plt.legend(["LQR", "Pure Pursuit", "Stanley"])
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plt.legend()
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plt.tight_layout()
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lateral_output = "U_turn_lateral_error_comparison.png"
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lateral_output = "X_Lateral_error_comparison.png"
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plt.savefig(lateral_output, dpi=200)
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plt.show()
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@ -92,10 +112,10 @@ plt.xlabel("Distance (m)")
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plt.ylabel("Heading Error (rad)")
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plt.title("Heading Error Comparison")
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plt.grid(True, alpha=0.3)
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plt.legend(["LQR", "Pure Pursuit", "Stanley"])
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plt.legend()
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plt.tight_layout()
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heading_output = "U_turn_heading_error_comparison.png"
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heading_output = "X_Heading_error_comparison.png"
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plt.savefig(heading_output, dpi=200)
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plt.show()
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@ -118,10 +138,10 @@ plt.xlabel("Distance (m)")
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plt.ylabel("Yaw Command (rad)")
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plt.title("Yaw Command Comparison")
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plt.grid(True, alpha=0.3)
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plt.legend(["LQR", "Pure Pursuit", "Stanley"])
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plt.legend()
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plt.tight_layout()
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yaw_output = "U_turn_yaw_command_comparison.png"
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yaw_output = "X_Yaw_command_comparison.png"
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plt.savefig(yaw_output, dpi=200)
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plt.show()
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print("读取完成：")
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@ -134,7 +154,7 @@ print(heading_output)
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print(yaw_output)
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print("\n" + "=" * 100)
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print("\n" + "=" * 90)
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print(
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f"{'Controller':<20}"
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f"{'Lat Max(m)':>12}"
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2349
lqr_Qe_effort_1.2_0.32_x_15_20_data/lqr_0.32_1.2_100_10_20.csv
Normal file
2349
lqr_Qe_effort_1.2_0.32_x_15_20_data/lqr_0.32_1.2_100_10_20.csv
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Load Diff
2289
lqr_Qe_effort_1.2_0.32_x_15_20_data/lqr_0.32_1.2_150_10_20.csv
Normal file
2289
lqr_Qe_effort_1.2_0.32_x_15_20_data/lqr_0.32_1.2_150_10_20.csv
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Load Diff
2337
lqr_Qe_effort_1.2_0.32_x_15_20_data/lqr_0.32_1.2_50_10_20.csv
Normal file
2337
lqr_Qe_effort_1.2_0.32_x_15_20_data/lqr_0.32_1.2_50_10_20.csv
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Load Diff
2337
lqr_Qe_effort_1.2_0.32_x_15_20_data/lqr_0.32_1.2_80_10_20.csv
Normal file
2337
lqr_Qe_effort_1.2_0.32_x_15_20_data/lqr_0.32_1.2_80_10_20.csv
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Load Diff
2349
lqr_Qh_effort_0.32_1.2_100_x_20_data/lqr_0.32_1.2_100_10_20.csv
Normal file
2349
lqr_Qh_effort_0.32_1.2_100_x_20_data/lqr_0.32_1.2_100_10_20.csv
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Load Diff
2363
lqr_Qh_effort_0.32_1.2_100_x_20_data/lqr_0.32_1.2_100_15_20.csv
Normal file
2363
lqr_Qh_effort_0.32_1.2_100_x_20_data/lqr_0.32_1.2_100_15_20.csv
Normal file
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Load Diff
2344
lqr_Qh_effort_0.32_1.2_100_x_20_data/lqr_0.32_1.2_100_20_20.csv
Normal file
2344
lqr_Qh_effort_0.32_1.2_100_x_20_data/lqr_0.32_1.2_100_20_20.csv
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File diff suppressed because it is too large
Load Diff
2411
lqr_Qh_effort_0.32_1.2_100_x_20_data/lqr_0.32_1.2_100_5_20.csv
Normal file
2411
lqr_Qh_effort_0.32_1.2_100_x_20_data/lqr_0.32_1.2_100_5_20.csv
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File diff suppressed because it is too large
Load Diff
2557
lqr_Ru_effort_0.32_1.2_100_5_x_data/lqr_0.32_1.2_100_5_10.csv
Normal file
2557
lqr_Ru_effort_0.32_1.2_100_5_x_data/lqr_0.32_1.2_100_5_10.csv
Normal file
File diff suppressed because it is too large
Load Diff
2411
lqr_Ru_effort_0.32_1.2_100_5_x_data/lqr_0.32_1.2_100_5_20.csv
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2411
lqr_Ru_effort_0.32_1.2_100_5_x_data/lqr_0.32_1.2_100_5_20.csv
Normal file
File diff suppressed because it is too large
Load Diff
2452
lqr_Ru_effort_0.32_1.2_100_5_x_data/lqr_0.32_1.2_100_5_25.csv
Normal file
2452
lqr_Ru_effort_0.32_1.2_100_5_x_data/lqr_0.32_1.2_100_5_25.csv
Normal file
File diff suppressed because it is too large
Load Diff
2381
lqr_Ru_effort_0.32_1.2_100_5_x_data/lqr_0.32_1.2_100_5_5.csv
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2381
lqr_Ru_effort_0.32_1.2_100_5_x_data/lqr_0.32_1.2_100_5_5.csv
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File diff suppressed because it is too large
Load Diff
@ -1,355 +0,0 @@
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#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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"""
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读取当前目录下：
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mission_center_logger.txt
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mission_center_logger1.txt
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mission_center_logger2.txt
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...
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从 [path_follow] 日志中提取：
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LQR: dis=..., alpha=...
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path controller, current pose point:x:..., y:..., yaw:...
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绘制：
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1. 横向误差 dis 随实际行驶路程变化
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2. 航向误差 alpha 随实际行驶路程变化
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说明：
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- dis：按你日志中的 LQR dis，单位通常是 m
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- alpha：按你日志中的 alpha，单位是 rad
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- 路程：根据连续 current pose 的 x/y 计算累计行驶距离
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- 日志中同一时刻可能重复打印多次，因此脚本会保留数据，
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但累计距离对相同位置不会增加。
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"""
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import re
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from pathlib import Path
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import numpy as np
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import matplotlib.pyplot as plt
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# ============================================================
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# 1. 日志文件
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# ============================================================
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LOG_PATTERN = "logs/mission_center_logger*.txt"
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files = sorted(Path(".").glob(LOG_PATTERN))
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if not files:
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raise FileNotFoundError(
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f"当前目录没有找到 {LOG_PATTERN}"
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)
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print("找到日志文件：")
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for f in files:
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print(" ", f)
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# ============================================================
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# 2. 正则表达式
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# ============================================================
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# LQR:
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# [LQR: dis=0.001038186, alpha=-0.003193076, ...
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lqr_pattern = re.compile(
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r"\[LQR:\s*"
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r"dis=([-+0-9.eE]+),\s*"
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r"alpha=([-+0-9.eE]+)"
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)
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# current pose:
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# [path controller, current pose point:x:24.68, y:1.16, yaw:0.026;
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pose_pattern = re.compile(
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r"current pose point:x:([-+0-9.eE]+),\s*"
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r"y:([-+0-9.eE]+),\s*"
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r"yaw:([-+0-9.eE]+)"
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)
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yaw_command_pattern = re.compile(
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r"PP output angular=([-+0-9.eE]+)"
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)
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# ============================================================
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# 3. 读取日志
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# ============================================================
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all_data = []
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for file in files:
|
||||
print(f"\n读取：{file}")
|
||||
|
||||
pending_lqr = None
|
||||
pending_yaw = None
|
||||
|
||||
with file.open("r", encoding="utf-8", errors="ignore") as f:
|
||||
for line in f:
|
||||
|
||||
# ---- LQR误差 ----
|
||||
m_lqr = lqr_pattern.search(line)
|
||||
if m_lqr:
|
||||
dis = float(m_lqr.group(1))
|
||||
alpha = float(m_lqr.group(2))
|
||||
|
||||
pending_lqr = {
|
||||
"dis": dis,
|
||||
"alpha": alpha,
|
||||
}
|
||||
|
||||
# ---- 当前车辆位置 ----
|
||||
m_pose = pose_pattern.search(line)
|
||||
m_yaw = yaw_command_pattern.search(line)
|
||||
if m_yaw:
|
||||
pending_yaw = float(m_yaw.group(1))
|
||||
if m_pose and pending_lqr is not None:
|
||||
|
||||
x = float(m_pose.group(1))
|
||||
y = float(m_pose.group(2))
|
||||
yaw = float(m_pose.group(3))
|
||||
|
||||
|
||||
all_data.append({
|
||||
"file": file.name,
|
||||
"x": x,
|
||||
"y": y,
|
||||
"yaw": yaw,
|
||||
"dis": pending_lqr["dis"],
|
||||
"alpha": pending_lqr["alpha"],
|
||||
"yaw_command": pending_yaw,
|
||||
})
|
||||
|
||||
pending_lqr = None
|
||||
|
||||
|
||||
if not all_data:
|
||||
raise RuntimeError(
|
||||
"没有解析到数据，请检查日志格式是否和示例一致。"
|
||||
)
|
||||
|
||||
|
||||
print(f"\n总共解析 {len(all_data)} 个数据点")
|
||||
|
||||
|
||||
# ============================================================
|
||||
# 4. 根据 x/y 计算实际行驶路程
|
||||
# ============================================================
|
||||
|
||||
x = np.array([d["x"] for d in all_data])
|
||||
y = np.array([d["y"] for d in all_data])
|
||||
|
||||
dis = np.array([d["dis"] for d in all_data])
|
||||
alpha = np.array([d["alpha"] for d in all_data])
|
||||
yaw_command = np.array([d["yaw_command"] for d in all_data])
|
||||
|
||||
# 连续位置之间的距离
|
||||
step_distance = np.sqrt(
|
||||
np.diff(x) ** 2 +
|
||||
np.diff(y) ** 2
|
||||
)
|
||||
|
||||
# 累计路程
|
||||
distance = np.zeros(len(x))
|
||||
|
||||
if len(x) > 1:
|
||||
distance[1:] = np.cumsum(step_distance)
|
||||
|
||||
|
||||
# ============================================================
|
||||
# 5. 如果希望横向误差取绝对值，可以取消下面注释
|
||||
# ============================================================
|
||||
|
||||
# dis = np.abs(dis)
|
||||
|
||||
# 注意：
|
||||
# 不建议默认取绝对值。
|
||||
# 保留正负号可以观察车辆是在路径左侧还是右侧。
|
||||
|
||||
|
||||
# ============================================================
|
||||
# 6. 输出基本统计信息
|
||||
# ============================================================
|
||||
|
||||
print("\n========== 误差统计 ==========")
|
||||
|
||||
print(
|
||||
f"总行驶距离 : {distance[-1]:.3f} m"
|
||||
)
|
||||
|
||||
print(
|
||||
f"横向误差最大值 : {np.max(dis):.6f} m"
|
||||
)
|
||||
|
||||
print(
|
||||
f"横向误差最小值 : {np.min(dis):.6f} m"
|
||||
)
|
||||
|
||||
print(
|
||||
f"横向误差绝对最大: {np.max(np.abs(dis)):.6f} m"
|
||||
)
|
||||
|
||||
print(
|
||||
f"横向误差 RMS : {np.sqrt(np.mean(dis ** 2)):.6f} m"
|
||||
)
|
||||
|
||||
print(
|
||||
f"航向误差最大值 : {np.max(alpha):.6f} rad "
|
||||
f"({np.degrees(np.max(alpha)):.3f} deg)"
|
||||
)
|
||||
|
||||
print(
|
||||
f"航向误差最小值 : {np.min(alpha):.6f} rad "
|
||||
f"({np.degrees(np.min(alpha)):.3f} deg)"
|
||||
)
|
||||
|
||||
print(
|
||||
f"航向误差绝对最大: {np.max(np.abs(alpha)):.6f} rad "
|
||||
f"({np.degrees(np.max(np.abs(alpha))):.3f} deg)"
|
||||
)
|
||||
|
||||
print(
|
||||
f"航向误差 RMS : {np.sqrt(np.mean(alpha ** 2)):.6f} rad "
|
||||
f"({np.degrees(np.sqrt(np.mean(alpha ** 2))):.3f} deg)"
|
||||
)
|
||||
|
||||
|
||||
# ============================================================
|
||||
# 7. 转换航向误差为角度
|
||||
# ============================================================
|
||||
|
||||
alpha_deg = np.degrees(alpha)
|
||||
|
||||
|
||||
# ============================================================
|
||||
# 8. 图1：横向误差
|
||||
# ============================================================
|
||||
|
||||
plt.figure(figsize=(12, 5))
|
||||
|
||||
plt.plot(
|
||||
distance,
|
||||
dis,
|
||||
linewidth=2.0
|
||||
)
|
||||
|
||||
plt.axhline(
|
||||
0.0,
|
||||
linestyle="--",
|
||||
linewidth=0.8
|
||||
)
|
||||
|
||||
plt.xlabel("Travel Distance (m)")
|
||||
plt.ylabel("Lateral Error dis (m)")
|
||||
plt.title("Lateral Error vs Travel Distance")
|
||||
plt.grid(True, alpha=0.3)
|
||||
|
||||
plt.tight_layout()
|
||||
|
||||
plt.savefig(
|
||||
"lateral_error_vs_distance.png",
|
||||
dpi=200
|
||||
)
|
||||
|
||||
plt.show()
|
||||
|
||||
|
||||
# ============================================================
|
||||
# 9. 图2：航向误差
|
||||
# ============================================================
|
||||
|
||||
plt.figure(figsize=(12, 5))
|
||||
|
||||
plt.plot(
|
||||
distance,
|
||||
alpha_deg,
|
||||
linewidth=2.0
|
||||
)
|
||||
|
||||
plt.axhline(
|
||||
0.0,
|
||||
linestyle="--",
|
||||
linewidth=0.8
|
||||
)
|
||||
|
||||
plt.xlabel("Travel Distance (m)")
|
||||
plt.ylabel("Heading Error alpha (deg)")
|
||||
plt.title("Heading Error vs Travel Distance")
|
||||
plt.grid(True, alpha=0.3)
|
||||
|
||||
plt.tight_layout()
|
||||
|
||||
plt.savefig(
|
||||
"heading_error_vs_distance.png",
|
||||
dpi=200
|
||||
)
|
||||
|
||||
plt.show()
|
||||
|
||||
# ============================================================
|
||||
# 13. 航向误差 rad
|
||||
# ============================================================
|
||||
|
||||
plt.figure(
|
||||
figsize=(12, 5)
|
||||
)
|
||||
|
||||
plt.plot(
|
||||
distance,
|
||||
yaw_command,
|
||||
linewidth=1.2
|
||||
)
|
||||
|
||||
plt.axhline(
|
||||
0.0,
|
||||
linestyle="--",
|
||||
linewidth=0.8
|
||||
)
|
||||
|
||||
plt.xlabel(
|
||||
"Distance (m)"
|
||||
)
|
||||
|
||||
plt.ylabel(
|
||||
"Yaw Command (rad)"
|
||||
)
|
||||
|
||||
plt.title(
|
||||
"Recalculated Yaw Command"
|
||||
)
|
||||
|
||||
plt.grid(True)
|
||||
|
||||
plt.tight_layout()
|
||||
|
||||
plt.show()
|
||||
# ============================================================
|
||||
# 10. 同时保存 CSV，方便后续 MATLAB / Excel 分析
|
||||
# ============================================================
|
||||
|
||||
output = np.column_stack(
|
||||
(
|
||||
distance,
|
||||
x,
|
||||
y,
|
||||
dis,
|
||||
alpha,
|
||||
alpha_deg,
|
||||
yaw_command,
|
||||
)
|
||||
)
|
||||
|
||||
np.savetxt(
|
||||
"path_tracking_error.csv",
|
||||
output,
|
||||
delimiter=",",
|
||||
header="distance_m,x_m,y_m,lateral_error_m,heading_error_rad,heading_error_deg,yaw_command",
|
||||
comments="",
|
||||
fmt="%.8f"
|
||||
)
|
||||
|
||||
print("\n输出文件：")
|
||||
print(" lateral_error_vs_distance.png")
|
||||
print(" heading_error_vs_distance.png")
|
||||
print(" path_tracking_error.csv")
|
||||
1177
lqr_radius_effort_0.64_x_100_5_25_data/lqr_0.64_1.0_100_5_25.csv
Normal file
1177
lqr_radius_effort_0.64_x_100_5_25_data/lqr_0.64_1.0_100_5_25.csv
Normal file
File diff suppressed because it is too large
Load Diff
1238
lqr_radius_effort_0.64_x_100_5_25_data/lqr_0.64_1.2_100_5_25.csv
Normal file
1238
lqr_radius_effort_0.64_x_100_5_25_data/lqr_0.64_1.2_100_5_25.csv
Normal file
File diff suppressed because it is too large
Load Diff
1296
lqr_radius_effort_0.64_x_100_5_25_data/lqr_0.64_1.5_100_5_25.csv
Normal file
1296
lqr_radius_effort_0.64_x_100_5_25_data/lqr_0.64_1.5_100_5_25.csv
Normal file
File diff suppressed because it is too large
Load Diff
1475
lqr_radius_effort_0.64_x_100_5_25_data/lqr_0.64_2.0_100_5_25.csv
Normal file
1475
lqr_radius_effort_0.64_x_100_5_25_data/lqr_0.64_2.0_100_5_25.csv
Normal file
File diff suppressed because it is too large
Load Diff
2608
lqr_vel_effort_x_1.5_100_5_25_data/lqr_0.32_1.5_100_5_25.csv
Normal file
2608
lqr_vel_effort_x_1.5_100_5_25_data/lqr_0.32_1.5_100_5_25.csv
Normal file
File diff suppressed because it is too large
Load Diff
2531
lqr_vel_effort_x_1.5_100_5_25_data/lqr_0.32_1.5_100_5_25_noforw.csv
Normal file
2531
lqr_vel_effort_x_1.5_100_5_25_data/lqr_0.32_1.5_100_5_25_noforw.csv
Normal file
File diff suppressed because it is too large
Load Diff
1526
lqr_vel_effort_x_1.5_100_5_25_data/lqr_0.64_1.5_100_5_25.csv
Normal file
1526
lqr_vel_effort_x_1.5_100_5_25_data/lqr_0.64_1.5_100_5_25.csv
Normal file
File diff suppressed because it is too large
Load Diff
1296
lqr_vel_effort_x_1.5_100_5_25_data/lqr_0.64_1.5_100_5_25_noforw.csv
Normal file
1296
lqr_vel_effort_x_1.5_100_5_25_data/lqr_0.64_1.5_100_5_25_noforw.csv
Normal file
File diff suppressed because it is too large
Load Diff
1011
lqr_vel_effort_x_1.5_100_5_25_data/lqr_0.96_1.5_100_5_25.csv
Normal file
1011
lqr_vel_effort_x_1.5_100_5_25_data/lqr_0.96_1.5_100_5_25.csv
Normal file
File diff suppressed because it is too large
Load Diff
@ -0,0 +1,923 @@
|
||||
distance_m,current_x_m,current_y_m,lateral_error_m,heading_error_rad,heading_error_deg,yaw_command
|
||||
0.00000000,0.00000000,0.00000000,0.00000000,0.00000777,0.00044540,0.00001562
|
||||
0.00000000,0.00000000,0.00000000,0.00000000,0.00000777,0.00044540,0.00001562
|
||||
0.00000000,0.00040876,0.00189316,-0.00189316,0.00001089,0.00062371,-0.00372659
|
||||
0.00000000,0.00040876,0.00189316,-0.00189316,0.00001089,0.00062371,-0.00372659
|
||||
0.00000000,0.00040876,0.00189316,-0.00189316,0.00001089,0.00062371,-0.00372659
|
||||
0.00000000,0.00434336,0.00273577,-0.00273582,0.00001199,0.00068720,-0.00539272
|
||||
0.00000000,0.00434336,0.00273577,-0.00273582,0.00001199,0.00068720,-0.00539272
|
||||
0.00000000,0.01825690,0.00331407,-0.00331429,0.00001238,0.00070915,-0.00653699
|
||||
0.00000000,0.01825690,0.00331407,-0.00331429,0.00001238,0.00070915,-0.00653699
|
||||
0.00000000,0.01825690,0.00331407,-0.00331429,0.00001238,0.00070915,-0.00653699
|
||||
0.00000000,0.04220500,0.00389884,-0.00389936,0.00001250,0.00071617,-0.00769459
|
||||
0.00000000,0.04220500,0.00389884,-0.00389936,0.00001250,0.00071617,-0.00769459
|
||||
0.00000000,0.07620478,0.00460014,-0.00460109,0.00001252,0.00071734,-0.00908313
|
||||
0.00000000,0.07620478,0.00460014,-0.00460109,0.00001252,0.00071734,-0.00908313
|
||||
0.00000000,0.07620478,0.00460014,-0.00460109,0.00001252,0.00071734,-0.00908313
|
||||
0.19371847,0.12026528,0.00546277,-0.00546180,0.00001252,0.00071743,-0.01079102
|
||||
0.19371847,0.12026528,0.00546277,-0.00546180,0.00001252,0.00071743,-0.01079102
|
||||
0.19371847,0.12026528,0.00546277,-0.00546180,0.00001252,0.00071743,-0.01079102
|
||||
0.19371847,0.17439076,0.00650497,-0.00650467,0.00001255,0.00071882,-0.01285453
|
||||
0.19371847,0.17439076,0.00650497,-0.00650467,0.00001255,0.00071882,-0.01285453
|
||||
0.19371847,0.23858285,0.00773414,-0.00773465,0.00001261,0.00072263,-0.01528815
|
||||
0.19371847,0.23858285,0.00773414,-0.00773465,0.00001261,0.00072263,-0.01528815
|
||||
0.19371847,0.23858285,0.00773414,-0.00773465,0.00001261,0.00072263,-0.01528815
|
||||
0.38743695,0.31231190,0.00900941,-0.00899935,0.00013250,0.00759168,-0.01757225
|
||||
0.38743695,0.31231190,0.00900941,-0.00899935,0.00013250,0.00759168,-0.01757225
|
||||
0.38743695,0.38826441,0.00986294,-0.00986336,0.00064879,0.03717283,-0.01822504
|
||||
0.38743695,0.38826441,0.00986294,-0.00986336,0.00064879,0.03717283,-0.01822504
|
||||
0.38743695,0.38826441,0.00986294,-0.00986336,0.00064879,0.03717283,-0.01822504
|
||||
0.38743695,0.46418652,0.01061130,-0.01070499,0.00122214,0.07002355,-0.01855497
|
||||
0.38743695,0.46418652,0.01061130,-0.01070499,0.00122214,0.07002355,-0.01855497
|
||||
0.58115542,0.54009715,0.01126934,-0.01119380,0.00183552,0.10516770,-0.01862555
|
||||
0.58115542,0.54009715,0.01126934,-0.01119380,0.00183552,0.10516770,-0.01862555
|
||||
0.58115542,0.54009715,0.01126934,-0.01119380,0.00183552,0.10516770,-0.01862555
|
||||
0.58115542,0.61599213,0.01186707,-0.01195259,0.00246072,0.14098913,-0.01855305
|
||||
0.58115542,0.61599213,0.01186707,-0.01195259,0.00246072,0.14098913,-0.01855305
|
||||
0.58115542,0.61599213,0.01186707,-0.01195259,0.00246072,0.14098913,-0.01855305
|
||||
0.77487390,0.69186015,0.01241582,-0.01215927,0.00308717,0.17688157,-0.01838100
|
||||
0.77487390,0.69186015,0.01241582,-0.01215927,0.00308717,0.17688157,-0.01838100
|
||||
0.77487390,0.76772778,0.01292068,-0.01289384,0.00371263,0.21271818,-0.01812410
|
||||
0.77487390,0.76772778,0.01292068,-0.01289384,0.00371263,0.21271818,-0.01812410
|
||||
0.77487390,0.76772778,0.01292068,-0.01289384,0.00371263,0.21271818,-0.01812410
|
||||
0.77487390,0.84356382,0.01339605,-0.01369372,0.00433858,0.24858223,-0.01780785
|
||||
0.77487390,0.84356382,0.01339605,-0.01369372,0.00433858,0.24858223,-0.01780785
|
||||
0.77487390,0.84356382,0.01339605,-0.01369372,0.00433858,0.24858223,-0.01780785
|
||||
0.96859237,0.91940390,0.01383464,-0.01359048,0.00495494,0.28389732,-0.01743792
|
||||
0.96859237,0.91940390,0.01383464,-0.01359048,0.00495494,0.28389732,-0.01743792
|
||||
0.96859237,0.99524364,0.01423726,-0.01438499,0.00556171,0.31866261,-0.01701615
|
||||
0.96859237,0.99524364,0.01423726,-0.01438499,0.00556171,0.31866261,-0.01701615
|
||||
0.96859237,0.99524364,0.01423726,-0.01438499,0.00556171,0.31866261,-0.01701615
|
||||
1.16231085,1.07108650,0.01460523,-0.01404284,0.00615841,0.35285088,-0.01654590
|
||||
1.16231085,1.07108650,0.01460523,-0.01404284,0.00615841,0.35285088,-0.01654590
|
||||
1.16231085,1.14692912,0.01494714,-0.01484283,0.00673834,0.38607863,-0.01605783
|
||||
1.16231085,1.14692912,0.01494714,-0.01484283,0.00673834,0.38607863,-0.01605783
|
||||
1.16231085,1.14692912,0.01494714,-0.01484283,0.00673834,0.38607863,-0.01605783
|
||||
1.16231085,1.22277348,0.01526737,-0.01570793,0.00729865,0.41818177,-0.01556627
|
||||
1.16231085,1.22277348,0.01526737,-0.01570793,0.00729865,0.41818177,-0.01556627
|
||||
1.16231085,1.22277348,0.01526737,-0.01570793,0.00729865,0.41818177,-0.01556627
|
||||
1.35602932,1.29862078,0.01556002,-0.01510874,0.00784598,0.44954160,-0.01504606
|
||||
1.35602932,1.29862078,0.01556002,-0.01510874,0.00784598,0.44954160,-0.01504606
|
||||
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|
||||
24.44439292,-3.52114611,7.92542455,-0.01816085,0.00152607,0.08743759,-0.03271861
|
||||
24.64357738,-3.52115430,8.00132329,-0.01790164,0.00273378,0.15663424,-0.03030876
|
||||
24.64357738,-3.52115430,8.00132329,-0.01790164,0.00273378,0.15663424,-0.03030876
|
||||
24.64357738,-3.52115430,8.00132329,-0.01790164,0.00273378,0.15663424,-0.03030876
|
||||
24.64357738,-3.52117278,8.07721671,-0.01813899,0.00385197,0.22070141,-0.02809900
|
||||
24.64357738,-3.52117278,8.07721671,-0.01813899,0.00385197,0.22070141,-0.02809900
|
||||
24.64357738,-3.52119298,8.15310514,-0.01854066,0.00488801,0.28006258,-0.02605763
|
||||
24.64357738,-3.52119298,8.15310514,-0.01854066,0.00488801,0.28006258,-0.02605763
|
||||
24.64357738,-3.52119298,8.15310514,-0.01854066,0.00488801,0.28006258,-0.02605763
|
||||
24.84276184,-3.52116684,8.22898182,-0.01787591,0.00585266,0.33533247,-0.02406811
|
||||
24.84276184,-3.52116684,8.22898182,-0.01787591,0.00585266,0.33533247,-0.02406811
|
||||
24.84276184,-3.52116864,8.30485878,-0.01835563,0.00672980,0.38558901,-0.02230955
|
||||
24.84276184,-3.52116864,8.30485878,-0.01835563,0.00672980,0.38558901,-0.02230955
|
||||
24.84276184,-3.52116864,8.30485878,-0.01835563,0.00672980,0.38558901,-0.02230955
|
||||
25.04194630,-3.52117767,8.38073425,-0.01746607,0.00754197,0.43212309,-0.02069596
|
||||
25.04194630,-3.52117767,8.38073425,-0.01746607,0.00754197,0.43212309,-0.02069596
|
||||
25.04194630,-3.52119588,8.45661018,-0.01804986,0.00829299,0.47515328,-0.01922327
|
||||
25.04194630,-3.52119588,8.45661018,-0.01804986,0.00829299,0.47515328,-0.01922327
|
||||
25.04194630,-3.52119588,8.45661018,-0.01804986,0.00829299,0.47515328,-0.01922327
|
||||
25.04194630,-3.52123429,8.53248327,-0.01876324,0.00897618,0.51429709,-0.01792684
|
||||
25.04194630,-3.52123429,8.53248327,-0.01876324,0.00897618,0.51429709,-0.01792684
|
||||
25.04194630,-3.52123429,8.53248327,-0.01876324,0.00897618,0.51429709,-0.01792684
|
||||
25.24113075,-3.52126375,8.60835598,-0.01764953,0.00962205,0.55130306,-0.01668778
|
||||
25.24113075,-3.52126375,8.60835598,-0.01764953,0.00962205,0.55130306,-0.01668778
|
||||
25.24113075,-3.52129223,8.68422827,-0.01841984,0.01022597,0.58590479,-0.01553096
|
||||
25.24113075,-3.52129223,8.68422827,-0.01841984,0.01022597,0.58590479,-0.01553096
|
||||
25.24113075,-3.52129223,8.68422827,-0.01841984,0.01022597,0.58590479,-0.01553096
|
||||
25.24113075,-3.52131061,8.76010027,-0.01926865,0.01079829,0.61869653,-0.01441759
|
||||
25.24113075,-3.52131061,8.76010027,-0.01926865,0.01079829,0.61869653,-0.01441759
|
||||
25.44031521,-3.52132302,8.83560458,-0.01793106,0.01131232,0.64814831,-0.01340962
|
||||
25.44031521,-3.52132302,8.83560458,-0.01793106,0.01131232,0.64814831,-0.01340962
|
||||
25.44031521,-3.52132302,8.83560458,-0.01793106,0.01131232,0.64814831,-0.01340962
|
||||
25.44031521,-3.52137065,8.91108275,-0.01885497,0.01178868,0.67544174,-0.01254696
|
||||
25.44031521,-3.52137065,8.91108275,-0.01885497,0.01178868,0.67544174,-0.01254696
|
||||
25.44031521,-3.52137065,8.91108275,-0.01885497,0.01178868,0.67544174,-0.01254696
|
||||
25.63949967,-3.52140886,8.98658718,-0.01740076,0.01223941,0.70126669,-0.01171726
|
||||
25.63949967,-3.52140886,8.98658718,-0.01740076,0.01223941,0.70126669,-0.01171726
|
||||
25.63949967,-3.52144460,9.06211365,-0.01836045,0.01266153,0.72545239,-0.01094002
|
||||
25.63949967,-3.52144460,9.06211365,-0.01836045,0.01266153,0.72545239,-0.01094002
|
||||
25.63949967,-3.52144460,9.06211365,-0.01836045,0.01266153,0.72545239,-0.01094002
|
||||
25.63949967,-3.52148073,9.13765354,-0.01938234,0.01305516,0.74800567,-0.01022079
|
||||
25.63949967,-3.52148073,9.13765354,-0.01938234,0.01305516,0.74800567,-0.01022079
|
||||
25.83868413,-3.52151755,9.21319210,-0.01778703,0.01342197,0.76902217,-0.00955693
|
||||
25.83868413,-3.52151755,9.21319210,-0.01778703,0.01342197,0.76902217,-0.00955693
|
||||
25.83868413,-3.52151755,9.21319210,-0.01778703,0.01342197,0.76902217,-0.00955693
|
||||
25.83868413,-3.52155921,9.28872528,-0.01885139,0.01376017,0.78839941,-0.00896000
|
||||
25.83868413,-3.52155921,9.28872528,-0.01885139,0.01376017,0.78839941,-0.00896000
|
||||
25.83868413,-3.52155921,9.28872528,-0.01885139,0.01376017,0.78839941,-0.00896000
|
||||
26.03786858,-3.52159516,9.36425299,-0.01715470,0.01408108,0.80678628,0.00000000
|
||||
26.03786858,-3.52159516,9.36425299,-0.01715470,0.01408108,0.80678628,0.00000000
|
||||
26.03786858,-3.52162875,9.43977518,-0.01824513,0.01438280,0.82407349,0.00000000
|
||||
26.03786858,-3.52162875,9.43977518,-0.01824513,0.01438280,0.82407349,0.00000000
|
||||
26.03786858,-3.52162875,9.43977518,-0.01824513,0.01438280,0.82407349,0.00000000
|
||||
26.03786858,-3.52161211,9.50909370,-0.01923981,0.01468499,0.84138802,0.00000000
|
||||
26.03786858,-3.52161211,9.50909370,-0.01923981,0.01468499,0.84138802,0.00000000
|
||||
26.03786858,-3.52161211,9.50909370,-0.01923981,0.01468499,0.84138802,0.00000000
|
||||
26.03786858,-3.52153683,9.56837078,-0.02006748,0.01498909,0.85881183,0.00000000
|
||||
26.03786858,-3.52153683,9.56837078,-0.02006748,0.01498909,0.85881183,0.00000000
|
||||
26.03786858,-3.52140215,9.61761260,-0.02071830,0.01529296,0.87622199,0.00000000
|
||||
26.03786858,-3.52140215,9.61761260,-0.02071830,0.01529296,0.87622199,0.00000000
|
||||
26.03786858,-3.52140215,9.61761260,-0.02071830,0.01529296,0.87622199,0.00000000
|
||||
26.03786858,-3.52121341,9.65682636,-0.02118852,0.01559647,0.89361165,0.00000000
|
||||
26.03786858,-3.52121341,9.65682636,-0.02118852,0.01559647,0.89361165,0.00000000
|
||||
26.03786858,-3.52097697,9.68601657,-0.02147536,0.01589950,0.91097399,0.00000000
|
||||
26.03786858,-3.52097697,9.68601657,-0.02147536,0.01589950,0.91097399,0.00000000
|
||||
26.03786858,-3.52097697,9.68601657,-0.02147536,0.01589950,0.91097399,0.00000000
|
||||
26.03786858,-3.52069898,9.70518549,-0.02157590,0.01620217,0.92831584,0.00000000
|
||||
26.03786858,-3.52069898,9.70518549,-0.02157590,0.01620217,0.92831584,0.00000000
|
||||
26.03786858,-3.52038555,9.71433425,-0.02148709,0.01650424,0.94562354,0.00000000
|
||||
26.03786858,-3.52038555,9.71433425,-0.02148709,0.01650424,0.94562354,0.00000000
|
||||
26.03786858,-3.52038555,9.71433425,-0.02148709,0.01650424,0.94562354,0.00000000
|
||||
26.03786858,-3.52021554,9.71512122,-0.02136839,0.01665528,0.95427739,0.00000000
|
||||
26.03786858,-3.52021554,9.71512122,-0.02136839,0.01665528,0.95427739,0.00000000
|
||||
26.03786858,-3.52021554,9.71512122,-0.02136839,0.01665528,0.95427739,0.00000000
|
||||
26.03786858,-3.52021482,9.71508470,-0.02136706,0.01665528,0.95427739,0.00000000
|
||||
26.03786858,-3.52021482,9.71508470,-0.02136706,0.01665528,0.95427739,0.00000000
|
||||
26.03786858,-3.52021456,9.71506980,-0.02136655,0.01665528,0.95427739,0.00000000
|
||||
26.03786858,-3.52021456,9.71506980,-0.02136655,0.01665528,0.95427739,0.00000000
|
||||
26.03786858,-3.52021456,9.71506980,-0.02136655,0.01665528,0.95427739,0.00000000
|
||||
26.03786858,-3.52021449,9.71506371,-0.02136638,0.01665528,0.95427739,0.00000000
|
||||
26.03786858,-3.52021449,9.71506371,-0.02136638,0.01665528,0.95427739,0.00000000
|
||||
26.03786858,-3.52021449,9.71506119,-0.02136634,0.01665528,0.95427739,0.00000000
|
||||
26.03786858,-3.52021449,9.71506119,-0.02136634,0.01665528,0.95427739,0.00000000
|
||||
26.03786858,-3.52021449,9.71506119,-0.02136634,0.01665528,0.95427739,0.00000000
|
||||
26.03786858,-3.52021452,9.71506013,-0.02136635,0.01665528,0.95427739,0.00000000
|
||||
26.03786858,-3.52021452,9.71506013,-0.02136635,0.01665528,0.95427739,0.00000000
|
||||
26.03786858,-3.52021452,9.71506013,-0.02136635,0.01665528,0.95427739,0.00000000
|
||||
26.03786858,-3.52021456,9.71505966,-0.02136639,0.01665528,0.95427739,0.00000000
|
||||
26.03786858,-3.52021456,9.71505966,-0.02136639,0.01665528,0.95427739,0.00000000
|
||||
26.03786858,-3.52021462,9.71505942,-0.02136640,0.01665516,0.95427056,0.00000000
|
||||
|
232
path_generate_json.py
Normal file
232
path_generate_json.py
Normal file
@ -0,0 +1,232 @@
|
||||
import json
|
||||
import math
|
||||
import matplotlib.pyplot as plt
|
||||
|
||||
# ============================================================
|
||||
# 参数配置
|
||||
# ============================================================
|
||||
|
||||
# 起点：采用你提供的第一个路径点
|
||||
START_LAT = 30.80062100422322
|
||||
START_LON = 121.21541599992909
|
||||
|
||||
TURN_RADIUS = 1.0
|
||||
MISSION_SPEED = 0.64
|
||||
ARC_SPACING = 0.3
|
||||
|
||||
# stanley para
|
||||
K_YAW = 2.0
|
||||
K_LAT = 4.0
|
||||
|
||||
# lqr para
|
||||
Q_e = 100
|
||||
Q_h = 5
|
||||
R_u = 25
|
||||
|
||||
# 地球半径（m）
|
||||
EARTH_RADIUS = 6378137.0
|
||||
|
||||
|
||||
#
|
||||
first_line_length = 6.0
|
||||
first_arc_rad = math.pi # 180° 半圆
|
||||
|
||||
second_line_length = 8.0
|
||||
second_arc_rad = math.pi / 2 # 90° 四分之一圆
|
||||
|
||||
third_line_length = 5.0
|
||||
|
||||
|
||||
|
||||
# ============================================================
|
||||
# 工具函数
|
||||
# ============================================================
|
||||
|
||||
def normalize_yaw(yaw):
|
||||
"""将 yaw 归一化到 [-pi, pi]。"""
|
||||
return math.atan2(math.sin(yaw), math.cos(yaw))
|
||||
|
||||
|
||||
def local_to_latlon(x, y):
|
||||
"""
|
||||
局部 ENU 坐标转经纬度。
|
||||
x: East，向东为正，单位 m
|
||||
y: North，向北为正，单位 m
|
||||
"""
|
||||
lat0 = math.radians(START_LAT)
|
||||
|
||||
lat = START_LAT + math.degrees(y / EARTH_RADIUS)
|
||||
lon = START_LON + math.degrees(
|
||||
x / (EARTH_RADIUS * math.cos(lat0))
|
||||
)
|
||||
|
||||
return lat, lon
|
||||
|
||||
|
||||
def add_point(points, x, y, yaw):
|
||||
"""添加一个 [latitude, longitude, yaw] 路径点。"""
|
||||
lat, lon = local_to_latlon(x, y)
|
||||
|
||||
points.append([
|
||||
round(lat, 12),
|
||||
round(lon, 12),
|
||||
round(normalize_yaw(yaw), 9)
|
||||
])
|
||||
|
||||
|
||||
def add_arc(points, cx, cy, radius,
|
||||
start_angle, sweep_angle, spacing):
|
||||
"""
|
||||
添加圆弧采样点，不重复添加圆弧起点。
|
||||
yaw 为圆弧的切线方向，单位 rad。
|
||||
"""
|
||||
arc_length = abs(radius * sweep_angle)
|
||||
num_segments = max(1, math.ceil(arc_length / spacing))
|
||||
|
||||
for i in range(1, num_segments + 1):
|
||||
ratio = i / num_segments
|
||||
angle = start_angle + sweep_angle * ratio
|
||||
|
||||
x = cx + radius * math.cos(angle)
|
||||
y = cy + radius * math.sin(angle)
|
||||
|
||||
# CCW 左转时，切线方向 = 圆心角 + pi/2
|
||||
yaw = angle + (
|
||||
math.pi / 2 if sweep_angle > 0
|
||||
else -math.pi / 2
|
||||
)
|
||||
|
||||
add_point(points, x, y, yaw)
|
||||
|
||||
|
||||
|
||||
coordinates = []
|
||||
|
||||
# 1. 第一段直线：长度 6 m
|
||||
# 起点 (0, 0)，终点 (6, 0)
|
||||
add_point(coordinates, 0, 0, 0.0)
|
||||
add_point(coordinates, first_line_length, 0, 0.0)
|
||||
|
||||
# 第一段圆弧起始索引
|
||||
first_turn_index = len(coordinates) - 1
|
||||
|
||||
# 2. 第一段半圆：R=1，逆时针 180°
|
||||
# 圆心 (6, 1)，从 -90° 转到 90°
|
||||
add_arc(
|
||||
coordinates,
|
||||
cx=first_line_length,
|
||||
cy=TURN_RADIUS,
|
||||
radius=TURN_RADIUS,
|
||||
start_angle=-math.pi / 2,
|
||||
sweep_angle= first_arc_rad,
|
||||
spacing=ARC_SPACING
|
||||
)
|
||||
|
||||
# 3. 第二段直线：长度 8 m
|
||||
# 半圆终点 (6, 2)，直线终点 (-2, 2)
|
||||
second_line_end_x = first_line_length - second_line_length
|
||||
second_line_end_y = 2 * TURN_RADIUS
|
||||
|
||||
add_point(
|
||||
coordinates,
|
||||
second_line_end_x,
|
||||
second_line_end_y,
|
||||
math.pi
|
||||
)
|
||||
# 第二段圆弧起始索引
|
||||
second_turn_index = len(coordinates) - 1
|
||||
|
||||
# 4. 第二段四分之一圆：顺时针 90°
|
||||
# 与第一段圆弧方向相反
|
||||
second_arc_cx = second_line_end_x
|
||||
second_arc_cy = second_line_end_y + TURN_RADIUS
|
||||
|
||||
add_arc(
|
||||
coordinates,
|
||||
cx=second_arc_cx,
|
||||
cy=second_arc_cy,
|
||||
radius=TURN_RADIUS,
|
||||
start_angle=-math.pi / 2,
|
||||
sweep_angle=-second_arc_rad,
|
||||
spacing=ARC_SPACING
|
||||
)
|
||||
|
||||
# 5. 最后一段直线：长度 5 m
|
||||
|
||||
third_line_start_x = second_arc_cx
|
||||
third_line_start_y = second_arc_cy
|
||||
|
||||
add_point(
|
||||
coordinates,
|
||||
third_line_start_x - TURN_RADIUS,
|
||||
third_line_start_y + third_line_length,
|
||||
math.pi / 2
|
||||
)
|
||||
|
||||
|
||||
# ============================================================
|
||||
# 构造符合现有项目的 GeoJSON
|
||||
# ============================================================
|
||||
|
||||
path_json = {
|
||||
"type": "FeatureCollection",
|
||||
"properties": {
|
||||
"turnRadius": TURN_RADIUS,
|
||||
"misionSpeed": MISSION_SPEED,
|
||||
"k_yaw": K_YAW,
|
||||
"k_lat": K_LAT,
|
||||
"lqr_Q_e": Q_e,
|
||||
"lqr_Q_h": Q_h,
|
||||
"lqr_R_u": R_u
|
||||
},
|
||||
"features": [
|
||||
{
|
||||
"type": "Feature",
|
||||
"properties": {
|
||||
"turnInds": [
|
||||
first_turn_index,
|
||||
second_turn_index
|
||||
],
|
||||
"mission": [],
|
||||
|
||||
},
|
||||
"geometry": {
|
||||
"type": "LineString",
|
||||
"coordinates": coordinates
|
||||
}
|
||||
}
|
||||
]
|
||||
}
|
||||
|
||||
|
||||
# ============================================================
|
||||
# 保存文件
|
||||
# ============================================================
|
||||
|
||||
output_file = "test_path.json"
|
||||
|
||||
with open(output_file, "w", encoding="utf-8") as f:
|
||||
json.dump(
|
||||
path_json,
|
||||
f,
|
||||
ensure_ascii=False,
|
||||
indent=2
|
||||
)
|
||||
|
||||
print(f"JSON 文件已生成: {output_file}")
|
||||
print(f"路径点数量: {len(coordinates)}")
|
||||
print(f"turnInds: {path_json['features'][0]['properties']['turnInds']}")
|
||||
print(f"起点: {coordinates[0]}")
|
||||
print(f"终点: {coordinates[-1]}")
|
||||
|
||||
|
||||
fig, ax = plt.subplots(figsize=(10, 6))
|
||||
ax.plot([p[0] for p in coordinates], [p[1] for p in coordinates], "-o", markersize=3, label="Path")
|
||||
|
||||
ax.set_xlabel("X (m)")
|
||||
ax.set_ylabel("Y (m)")
|
||||
ax.axis("equal")
|
||||
ax.grid(True)
|
||||
ax.legend()
|
||||
plt.tight_layout()
|
||||
plt.show()
|
||||
6011
path_visualizer.log
Normal file
6011
path_visualizer.log
Normal file
File diff suppressed because it is too large
Load Diff
@ -22,6 +22,13 @@
|
||||
#include <tf2_ros/transform_broadcaster.h>
|
||||
#include <tf2/LinearMath/Quaternion.h>
|
||||
#include <std_msgs/msg/int32.hpp>
|
||||
#include <Eigen/Dense>
|
||||
|
||||
|
||||
#include <spdlog/spdlog.h>
|
||||
#include <spdlog/sinks/stdout_color_sinks.h>
|
||||
#include <spdlog/sinks/rotating_file_sink.h>
|
||||
#include <spdlog/sinks/basic_file_sink.h>
|
||||
|
||||
class PathVisualizer : public rclcpp::Node
|
||||
{
|
||||
@ -38,6 +45,8 @@ private:
|
||||
double w);
|
||||
double normalize_angle(double angle);
|
||||
bool downloadPathJson(const std::string &url,std::string &json_data);
|
||||
bool downloadPathJson(const std::string &file_path,std::string &json_data,
|
||||
bool is_local_file);
|
||||
bool loadPathFromJson(const std::string &json_data);
|
||||
|
||||
double gps_to_x(double lat,double lon);
|
||||
@ -56,7 +65,9 @@ private:
|
||||
void interpolatePoints(double max_interval_distance);
|
||||
void publishLocalPose();
|
||||
void publishOdomPath();
|
||||
|
||||
void computePathCurvature();
|
||||
// lqr
|
||||
Eigen::MatrixXd lqr(const Eigen::MatrixXd &A, const Eigen::MatrixXd &B, const Eigen::MatrixXd &Q, const Eigen::MatrixXd &R);
|
||||
private:
|
||||
// topic pub
|
||||
rclcpp::Publisher<geometry_msgs::msg::Twist>::SharedPtr cmd_pub_;
|
||||
@ -84,6 +95,7 @@ private:
|
||||
std::vector<double> path_x_;
|
||||
std::vector<double> path_y_;
|
||||
std::vector<double> path_yaw_;
|
||||
std::vector<double> path_kappa_;
|
||||
// odom history pose
|
||||
std::vector<double> history_x_;
|
||||
std::vector<double> history_y_;
|
||||
@ -100,8 +112,8 @@ private:
|
||||
bool has_pose_;
|
||||
// contorl paramss
|
||||
double max_speed_ = 0.8;
|
||||
double max_yaw_rate_ = 2.0;
|
||||
double lookahead_distance_ =0.6;
|
||||
double max_yaw_rate_ = 5.0;
|
||||
double lookahead_distance_ =0.4;
|
||||
double max_interval_distance_ = 0.2;
|
||||
double origin_lat_;
|
||||
double origin_lon_;
|
||||
@ -110,13 +122,27 @@ private:
|
||||
int forward_index_limit_=100;
|
||||
int path_track_index_ = -1;
|
||||
|
||||
// stanley parametres
|
||||
double k_yaw_ = 1.0;
|
||||
double k_lat_ = 1.0;
|
||||
|
||||
//lqr parametres
|
||||
double Q_e = 1.0;
|
||||
double Q_h = 1.0;
|
||||
double R_u = 1.0;
|
||||
bool kappa_cal_ = false;
|
||||
|
||||
bool origin_set_= false;
|
||||
bool path_transed = false;
|
||||
std::string file_path_;
|
||||
std::string file_name_;
|
||||
std::string path_url_ ;
|
||||
std::string json_data_;
|
||||
std::unique_ptr<GeodeticConverter> geodetic_converter_;
|
||||
|
||||
// logger
|
||||
std::shared_ptr<spdlog::logger> logger_;
|
||||
|
||||
};
|
||||
|
||||
#endif
|
||||
|
||||
@ -1,5 +1,7 @@
|
||||
#include "sweet_webots_robot/PathVisualizer.hpp"
|
||||
|
||||
|
||||
|
||||
PathVisualizer::PathVisualizer(const std::string& file_name):
|
||||
Node("path_visualizer"),
|
||||
target_index_(0),
|
||||
@ -7,6 +9,7 @@ has_pose_(false)
|
||||
{
|
||||
file_name_ = file_name;
|
||||
path_url_ = "https://test.sweetai.cn:4433/load/locationCmdPath/" + file_name_;
|
||||
file_path_ = "/home/sweetai/auto_drive_misson_center_webots_simulation/test_path.json";
|
||||
RCLCPP_INFO(this->get_logger(),"PathVisualizer started");
|
||||
// pub
|
||||
cmd_pub_ = this->create_publisher<geometry_msgs::msg::Twist>("/twist_cmd_vel",10);
|
||||
@ -39,8 +42,35 @@ has_pose_(false)
|
||||
// urdf pose
|
||||
tf_broadcaster_ = std::make_unique<tf2_ros::TransformBroadcaster>(*this);
|
||||
// path get
|
||||
downloadPathJson(path_url_,json_data_);
|
||||
downloadPathJson(file_path_,json_data_,true);
|
||||
loadPathFromJson(json_data_);
|
||||
|
||||
|
||||
// logger初始化
|
||||
auto console_sink =
|
||||
std::make_shared<spdlog::sinks::stdout_color_sink_mt>();
|
||||
|
||||
// 每次启动时清空原文件
|
||||
auto file_sink =
|
||||
std::make_shared<spdlog::sinks::basic_file_sink_mt>(
|
||||
"./path_visualizer.log",
|
||||
true // truncate：清空原文件
|
||||
);
|
||||
|
||||
std::vector<spdlog::sink_ptr> sinks{
|
||||
console_sink,
|
||||
file_sink
|
||||
};
|
||||
|
||||
logger_ = std::make_shared<spdlog::logger>(
|
||||
"path_visualizer",
|
||||
sinks.begin(),
|
||||
sinks.end()
|
||||
);
|
||||
|
||||
logger_->set_level(spdlog::level::debug);
|
||||
|
||||
logger_->info("PathVisualizer started");
|
||||
|
||||
|
||||
}
|
||||
@ -122,6 +152,60 @@ void PathVisualizer::transformPathToVehicleStart(double vehicle_initial_yaw)
|
||||
}
|
||||
|
||||
}
|
||||
|
||||
#include <fstream>
|
||||
#include <sstream>
|
||||
#include <string>
|
||||
|
||||
bool PathVisualizer::downloadPathJson(const std::string &file_path,
|
||||
std::string &json_data,
|
||||
bool is_local_file)
|
||||
{
|
||||
json_data.clear();
|
||||
|
||||
// 打开本地 JSON 文件
|
||||
std::ifstream file(file_path);
|
||||
if (!file.is_open())
|
||||
{
|
||||
RCLCPP_ERROR(
|
||||
this->get_logger(),
|
||||
"Failed to open JSON file: %s",
|
||||
file_path.c_str());
|
||||
return false;
|
||||
}
|
||||
|
||||
// 读取文件全部内容
|
||||
std::stringstream buffer;
|
||||
buffer << file.rdbuf();
|
||||
|
||||
if (file.bad())
|
||||
{
|
||||
RCLCPP_ERROR(
|
||||
this->get_logger(),
|
||||
"Failed to read JSON file: %s",
|
||||
file_path.c_str());
|
||||
return false;
|
||||
}
|
||||
|
||||
json_data = buffer.str();
|
||||
|
||||
if (json_data.empty())
|
||||
{
|
||||
RCLCPP_ERROR(
|
||||
this->get_logger(),
|
||||
"JSON file is empty: %s",
|
||||
file_path.c_str());
|
||||
return false;
|
||||
}
|
||||
|
||||
RCLCPP_INFO(
|
||||
this->get_logger(),
|
||||
"Path JSON loaded successfully, size = %zu, path = %s",
|
||||
json_data.size(),
|
||||
file_path.c_str());
|
||||
|
||||
return true;
|
||||
}
|
||||
bool PathVisualizer::downloadPathJson(const std::string &url,
|
||||
std::string &json_data)
|
||||
{
|
||||
@ -171,6 +255,19 @@ bool PathVisualizer::loadPathFromJson(
|
||||
{
|
||||
// 解析 JSON
|
||||
json data =json::parse(json_data);
|
||||
// 检查 properties
|
||||
if (!data.contains("properties") ||
|
||||
!data["properties"].is_object())
|
||||
{
|
||||
RCLCPP_ERROR(this->get_logger(),"JSON does not contain valid properties");
|
||||
return false;
|
||||
}
|
||||
max_speed_ = data["properties"]["misionSpeed"].get<double>();
|
||||
k_yaw_ = data["properties"]["k_yaw"].get<double>();
|
||||
k_lat_ = data["properties"]["k_lat"].get<double>();
|
||||
Q_e = data["properties"]["lqr_Q_e"].get<double>();
|
||||
Q_h = data["properties"]["lqr_Q_h"].get<double>();
|
||||
R_u = data["properties"]["lqr_R_u"].get<double>();
|
||||
// 检查 features
|
||||
if (!data.contains("features") ||
|
||||
!data["features"].is_array() ||
|
||||
@ -502,6 +599,38 @@ void PathVisualizer::publishPathRviz()
|
||||
origin_path_pub_->publish(origin_path);
|
||||
|
||||
}
|
||||
|
||||
void PathVisualizer::computePathCurvature()
|
||||
{
|
||||
if (path_x_.size() < 3) {
|
||||
return;
|
||||
}
|
||||
path_kappa_.resize(path_x_.size());
|
||||
for (size_t i = 1; i < path_x_.size() - 1; ++i)
|
||||
{
|
||||
int p_prev = i - 1;
|
||||
int p_curr = i;
|
||||
int p_next = i + 1;
|
||||
double ds1 = std::hypot(path_x_[p_curr] - path_x_[p_prev],path_y_[p_curr] - path_y_[p_prev]);
|
||||
double ds2 = std::hypot(path_x_[p_next] - path_x_[p_curr],path_y_[p_next] - path_y_[p_curr]);
|
||||
double ds = 0.5 * (ds1 + ds2);
|
||||
if (ds < 1e-6) {
|
||||
path_kappa_[i] = 0.0;
|
||||
continue;
|
||||
}
|
||||
double dyaw = path_yaw_[p_next] - path_yaw_[p_prev];
|
||||
while (dyaw > M_PI)
|
||||
dyaw -= 2.0 * M_PI;
|
||||
|
||||
while (dyaw < -M_PI)
|
||||
dyaw += 2.0 * M_PI;
|
||||
path_kappa_[i] = dyaw / (ds1 + ds2);
|
||||
logger_->debug("path ind:{}, kappa:{}", i, path_kappa_[i]);
|
||||
}
|
||||
// 首尾点处理
|
||||
path_kappa_[0] = path_kappa_[1];
|
||||
path_kappa_[path_kappa_.size() - 1] = path_kappa_[path_kappa_.size() - 2];
|
||||
}
|
||||
void PathVisualizer::publishHistoryPathRviz(){
|
||||
history_x_.push_back(x_);
|
||||
history_y_.push_back(y_);
|
||||
@ -592,7 +721,22 @@ void PathVisualizer::localozation_callback(const geometry_msgs::msg::PoseWithCov
|
||||
publishOdomPath();
|
||||
}
|
||||
}
|
||||
|
||||
Eigen::MatrixXd PathVisualizer::lqr(const Eigen::MatrixXd &A, const Eigen::MatrixXd &B, const Eigen::MatrixXd &Q, const Eigen::MatrixXd &R)
|
||||
{
|
||||
|
||||
Eigen::MatrixXd P = Q; // 初始化P为Q
|
||||
Eigen::MatrixXd P_prev = Eigen::MatrixXd::Zero(A.rows(), A.cols());
|
||||
for (int i = 0; i < 1000; ++i)
|
||||
{
|
||||
P_prev = P;
|
||||
P = Q + A.transpose() * P * A - A.transpose() * P * B * (R + B.transpose() * P * B).inverse() * B.transpose() * P * A;
|
||||
if ((P - P_prev).norm() < 1e-6)
|
||||
break; // 收敛条件
|
||||
}
|
||||
// LQR增益矩阵K
|
||||
Eigen::MatrixXd K = (R + B.transpose() * P * B).inverse() * B.transpose() * P * A;
|
||||
return K;
|
||||
};
|
||||
void PathVisualizer::control(){
|
||||
if(!has_pose_)
|
||||
{
|
||||
@ -601,15 +745,22 @@ void PathVisualizer::control(){
|
||||
"control has not pose.");
|
||||
return;
|
||||
}
|
||||
|
||||
double speed=max_speed_;
|
||||
publishVehicleInfoRviz();
|
||||
publishLocalPose();
|
||||
if(!kappa_cal_){
|
||||
kappa_cal_=true;
|
||||
computePathCurvature();
|
||||
}
|
||||
|
||||
target_index_= findClosestPoint(forward_index_limit_);
|
||||
int current_index = target_index_;
|
||||
int target =findLookAheadPoint();
|
||||
|
||||
double target_x =path_x_[target];
|
||||
double target_y =path_y_[target];
|
||||
double target_yaw =path_yaw_[target];
|
||||
double target_kappa =path_kappa_[target];
|
||||
|
||||
/*世界坐标转换到车辆坐标系*/
|
||||
double dx =target_x-x_;
|
||||
@ -617,15 +768,65 @@ void PathVisualizer::control(){
|
||||
double local_x =cos(yaw_)*dx+sin(yaw_)*dy;
|
||||
double local_y =-sin(yaw_)*dx+cos(yaw_)*dy;
|
||||
|
||||
/*Pure Pursuit*/
|
||||
double Ld =sqrt(local_x*local_x+local_y*local_y);
|
||||
double curvature =2.0*local_y/(Ld*Ld);
|
||||
double target_angle = std::atan2(dy, dx);
|
||||
double alpha = target_angle - yaw_;
|
||||
while (alpha > M_PI) alpha -= 2 * M_PI;
|
||||
while (alpha < -M_PI) alpha += 2 * M_PI;
|
||||
|
||||
geometry_msgs::msg::Twist cmd;
|
||||
|
||||
double speed=max_speed_;
|
||||
cmd.linear.x =speed;
|
||||
cmd.angular.z =speed*curvature;
|
||||
/*Pure Pursuit*/
|
||||
// double Ld =sqrt(local_x*local_x+local_y*local_y);
|
||||
// double w_cmd =2.0*speed*sin(alpha)/(Ld);
|
||||
|
||||
/*Stanley*/
|
||||
double curent_path_x = path_x_[current_index];
|
||||
double curent_path_y = path_y_[current_index];
|
||||
double current_path_yaw =path_yaw_[current_index];
|
||||
double current_path_kappa = path_kappa_[current_index];
|
||||
alpha = current_path_yaw - yaw_;
|
||||
while (alpha > M_PI) alpha -= 2 * M_PI;
|
||||
while (alpha < -M_PI) alpha += 2 * M_PI;
|
||||
|
||||
double dx_path = x_ - curent_path_x;
|
||||
double dy_path = y_ - curent_path_y;
|
||||
double error_lat = -dx_path * sin(current_path_yaw) + dy_path * cos(current_path_yaw);
|
||||
double w_cmd =k_yaw_ * alpha - k_lat_ * std::atan2(error_lat,speed);
|
||||
|
||||
/*lqr*/
|
||||
double dt = 0.01;
|
||||
Eigen::MatrixXd A(2, 2),B(2, 1),Q(2, 2),R(1, 1);
|
||||
// A << 1.0 , speed * dt,
|
||||
// 0 , 1.0;
|
||||
// B << 0.5 * speed * dt * dt,
|
||||
// dt;
|
||||
A << 1.0 , speed * dt,
|
||||
0 , 1.0;
|
||||
B << 0,
|
||||
dt;
|
||||
Q << Q_e , 0 ,
|
||||
0 , Q_h;
|
||||
R << R_u;
|
||||
|
||||
Eigen::VectorXd x(2);
|
||||
x << error_lat, -alpha;
|
||||
Eigen::MatrixXd K = lqr(A, B, Q, R);
|
||||
|
||||
std::stringstream ss;
|
||||
ss << K;
|
||||
logger_->debug("LQR Gain Matrix K:\n{}", ss.str());
|
||||
w_cmd = - 1 * speed * 0 -(K * x)(0, 0);
|
||||
|
||||
logger_->debug("current_pose_x:{}, current_pose_y:{},current_pose_yaw:{}",
|
||||
x_, y_,yaw_
|
||||
);
|
||||
logger_->debug("current_path_x:{}, current_path_y:{},current_path_yaw:{}",
|
||||
curent_path_x,
|
||||
curent_path_y,
|
||||
current_path_yaw
|
||||
);
|
||||
cmd.linear.x = speed;
|
||||
cmd.angular.z = w_cmd;
|
||||
|
||||
if(cmd.angular.z >max_yaw_rate_)
|
||||
{
|
||||
@ -637,7 +838,15 @@ void PathVisualizer::control(){
|
||||
cmd.angular.z=-max_yaw_rate_;
|
||||
}
|
||||
|
||||
//cmd_pub_->publish(cmd);
|
||||
if (current_index == path_x_.size() - 1)
|
||||
{
|
||||
cmd.linear.x = 0.0;
|
||||
cmd.angular.z = 0.0;
|
||||
RCLCPP_INFO(this->get_logger(),"Reached the end of the path.");
|
||||
}
|
||||
|
||||
cmd_pub_->publish(cmd);
|
||||
logger_->debug("current_cmd_angular_z:{}",cmd.angular.z);
|
||||
|
||||
// RCLCPP_INFO_THROTTLE(
|
||||
// this->get_logger(),
|
||||
|
||||
2333
stanley_k_lat_effor_0.32_1.2_1.0_x_data/stanley_0.32_1.2_1.0_0.8.csv
Normal file
2333
stanley_k_lat_effor_0.32_1.2_1.0_x_data/stanley_0.32_1.2_1.0_0.8.csv
Normal file
File diff suppressed because it is too large
Load Diff
2395
stanley_k_lat_effor_0.32_1.2_1.0_x_data/stanley_0.32_1.2_1.0_1.0.csv
Normal file
2395
stanley_k_lat_effor_0.32_1.2_1.0_x_data/stanley_0.32_1.2_1.0_1.0.csv
Normal file
File diff suppressed because it is too large
Load Diff
2422
stanley_k_lat_effor_0.32_1.2_1.0_x_data/stanley_0.32_1.2_1.0_1.2.csv
Normal file
2422
stanley_k_lat_effor_0.32_1.2_1.0_x_data/stanley_0.32_1.2_1.0_1.2.csv
Normal file
File diff suppressed because it is too large
Load Diff
2275
stanley_k_lat_effor_0.32_1.2_1.0_x_data/stanley_0.32_1.2_1.0_1.5.csv
Normal file
2275
stanley_k_lat_effor_0.32_1.2_1.0_x_data/stanley_0.32_1.2_1.0_1.5.csv
Normal file
File diff suppressed because it is too large
Load Diff
2318
stanley_k_lat_effor_0.32_1.2_1.0_x_data/stanley_0.32_1.2_1.0_2.0.csv
Normal file
2318
stanley_k_lat_effor_0.32_1.2_1.0_x_data/stanley_0.32_1.2_1.0_2.0.csv
Normal file
File diff suppressed because it is too large
Load Diff
2319
stanley_k_lat_effor_0.32_1.2_1.0_x_data/stanley_0.32_1.2_1.0_4.0.csv
Normal file
2319
stanley_k_lat_effor_0.32_1.2_1.0_x_data/stanley_0.32_1.2_1.0_4.0.csv
Normal file
File diff suppressed because it is too large
Load Diff
2363
stanley_k_yaw_effor_0.32_1.2_x_2.0_data/stanley_0.32_1.2_0.8_2.0.csv
Normal file
2363
stanley_k_yaw_effor_0.32_1.2_x_2.0_data/stanley_0.32_1.2_0.8_2.0.csv
Normal file
File diff suppressed because it is too large
Load Diff
2318
stanley_k_yaw_effor_0.32_1.2_x_2.0_data/stanley_0.32_1.2_1.0_2.0.csv
Normal file
2318
stanley_k_yaw_effor_0.32_1.2_x_2.0_data/stanley_0.32_1.2_1.0_2.0.csv
Normal file
File diff suppressed because it is too large
Load Diff
2367
stanley_k_yaw_effor_0.32_1.2_x_2.0_data/stanley_0.32_1.2_1.2_2.0.csv
Normal file
2367
stanley_k_yaw_effor_0.32_1.2_x_2.0_data/stanley_0.32_1.2_1.2_2.0.csv
Normal file
File diff suppressed because it is too large
Load Diff
2288
stanley_k_yaw_effor_0.32_1.2_x_2.0_data/stanley_0.32_1.2_1.5_2.0.csv
Normal file
2288
stanley_k_yaw_effor_0.32_1.2_x_2.0_data/stanley_0.32_1.2_1.5_2.0.csv
Normal file
File diff suppressed because it is too large
Load Diff
2257
stanley_k_yaw_effor_0.32_1.2_x_2.0_data/stanley_0.32_1.2_2.0_2.0.csv
Normal file
2257
stanley_k_yaw_effor_0.32_1.2_x_2.0_data/stanley_0.32_1.2_2.0_2.0.csv
Normal file
File diff suppressed because it is too large
Load Diff
1125
stanley_radius_effor_x_y_1.0_2.0_data/stanley_0.64_1.0_2.0_4.0.csv
Normal file
1125
stanley_radius_effor_x_y_1.0_2.0_data/stanley_0.64_1.0_2.0_4.0.csv
Normal file
File diff suppressed because it is too large
Load Diff
1170
stanley_radius_effor_x_y_1.0_2.0_data/stanley_0.64_1.2_2.0_4.0.csv
Normal file
1170
stanley_radius_effor_x_y_1.0_2.0_data/stanley_0.64_1.2_2.0_4.0.csv
Normal file
File diff suppressed because it is too large
Load Diff
1385
stanley_radius_effor_x_y_1.0_2.0_data/stanley_0.64_1.5_2.0_4.0.csv
Normal file
1385
stanley_radius_effor_x_y_1.0_2.0_data/stanley_0.64_1.5_2.0_4.0.csv
Normal file
File diff suppressed because it is too large
Load Diff
1385
stanley_radius_effor_x_y_1.0_2.0_data/stanley_0.64_2.0_2.0_4.0.csv
Normal file
1385
stanley_radius_effor_x_y_1.0_2.0_data/stanley_0.64_2.0_2.0_4.0.csv
Normal file
File diff suppressed because it is too large
Load Diff
2318
stanley_vel_effor_x_1.2_y_z_data/stanley_0.32_1.2_1.0_2.0.csv
Normal file
2318
stanley_vel_effor_x_1.2_y_z_data/stanley_0.32_1.2_1.0_2.0.csv
Normal file
File diff suppressed because it is too large
Load Diff
821
stanley_vel_effor_x_1.2_y_z_data/stanley_0.64_2.0_2.0_4.0.csv
Normal file
821
stanley_vel_effor_x_1.2_y_z_data/stanley_0.64_2.0_2.0_4.0.csv
Normal file
@ -0,0 +1,821 @@
|
||||
distance_m,current_x_m,current_y_m,lateral_error_m,heading_error_rad,heading_error_deg,yaw_command
|
||||
0.00000000,0.00000000,0.00000000,0.00000000,0.00000777,0.00044540,0.00002332
|
||||
0.00000000,0.00000000,0.00000000,0.00000000,0.00000777,0.00044540,0.00002332
|
||||
0.00000000,0.00000000,0.00000000,0.00000000,0.00000777,0.00044540,0.00002332
|
||||
0.00000000,0.00101846,0.00190493,-0.00190494,0.00001076,0.00061645,-0.01187354
|
||||
0.00000000,0.00101846,0.00190493,-0.00190494,0.00001076,0.00061645,-0.01187354
|
||||
0.00000000,0.00101846,0.00190493,-0.00190494,0.00001076,0.00061645,-0.01187354
|
||||
0.00000000,0.00998646,0.00284354,-0.00284366,0.00001190,0.00068185,-0.01773635
|
||||
0.00000000,0.00998646,0.00284354,-0.00284366,0.00001190,0.00068185,-0.01773635
|
||||
0.00000000,0.02894594,0.00351799,-0.00351835,0.00001239,0.00071011,-0.02195014
|
||||
0.00000000,0.02894594,0.00351799,-0.00351835,0.00001239,0.00071011,-0.02195014
|
||||
0.00000000,0.02894594,0.00351799,-0.00351835,0.00001239,0.00071011,-0.02195014
|
||||
0.00000000,0.05793384,0.00419885,-0.00419958,0.00001258,0.00072071,-0.02620489
|
||||
0.00000000,0.05793384,0.00419885,-0.00419958,0.00001258,0.00072071,-0.02620489
|
||||
0.00000000,0.05793384,0.00419885,-0.00419958,0.00001258,0.00072071,-0.02620489
|
||||
0.19371847,0.09697061,0.00499620,-0.00499493,0.00001264,0.00072435,-0.03118773
|
||||
0.19371847,0.09697061,0.00499620,-0.00499493,0.00001264,0.00072435,-0.03118773
|
||||
0.19371847,0.14606672,0.00595488,-0.00595422,0.00001268,0.00072646,-0.03717916
|
||||
0.19371847,0.14606672,0.00595488,-0.00595422,0.00001268,0.00072646,-0.03717916
|
||||
0.19371847,0.14606672,0.00595488,-0.00595422,0.00001268,0.00072646,-0.03717916
|
||||
0.19371847,0.20522699,0.00709311,-0.00709320,0.00001274,0.00072967,-0.04429258
|
||||
0.19371847,0.20522699,0.00709311,-0.00709320,0.00001274,0.00072967,-0.04429258
|
||||
0.19371847,0.27445325,0.00841830,-0.00841928,0.00001283,0.00073522,-0.05257421
|
||||
0.19371847,0.27445325,0.00841830,-0.00841928,0.00001283,0.00073522,-0.05257421
|
||||
0.19371847,0.27445325,0.00841830,-0.00841928,0.00001283,0.00073522,-0.05257421
|
||||
0.38743695,0.35016477,0.00835564,-0.00830543,0.00134400,0.07700542,-0.04818874
|
||||
0.38743695,0.35016477,0.00835564,-0.00830543,0.00134400,0.07700542,-0.04818874
|
||||
0.38743695,0.42612335,0.00768871,-0.00780901,0.00311345,0.17838776,-0.03871235
|
||||
0.38743695,0.42612335,0.00768871,-0.00780901,0.00311345,0.17838776,-0.03871235
|
||||
0.38743695,0.42612335,0.00768871,-0.00780901,0.00311345,0.17838776,-0.03871235
|
||||
0.58115542,0.50205676,0.00714168,-0.00677316,0.00465607,0.26677318,-0.03066547
|
||||
0.58115542,0.50205676,0.00714168,-0.00677316,0.00465607,0.26677318,-0.03066547
|
||||
0.58115542,0.50205676,0.00714168,-0.00677316,0.00465607,0.26677318,-0.03066547
|
||||
0.58115542,0.57797251,0.00682669,-0.00680765,0.00589138,0.33755094,-0.02499092
|
||||
0.58115542,0.57797251,0.00682669,-0.00680765,0.00589138,0.33755094,-0.02499092
|
||||
0.58115542,0.65385568,0.00665324,-0.00715621,0.00692296,0.39665619,-0.02081220
|
||||
0.58115542,0.65385568,0.00665324,-0.00715621,0.00692296,0.39665619,-0.02081220
|
||||
0.58115542,0.65385568,0.00665324,-0.00715621,0.00692296,0.39665619,-0.02081220
|
||||
0.77487390,0.72972891,0.00665827,-0.00630897,0.00772826,0.44279679,-0.01842741
|
||||
0.77487390,0.72972891,0.00665827,-0.00630897,0.00772826,0.44279679,-0.01842741
|
||||
0.77487390,0.72972891,0.00665827,-0.00630897,0.00772826,0.44279679,-0.01842741
|
||||
0.77487390,0.80557660,0.00675516,-0.00701299,0.00841274,0.48201472,-0.01697946
|
||||
0.77487390,0.80557660,0.00675516,-0.00701299,0.00841274,0.48201472,-0.01697946
|
||||
0.96859237,0.88141546,0.00687319,-0.00608468,0.00903869,0.51787866,-0.01583895
|
||||
0.96859237,0.88141546,0.00687319,-0.00608468,0.00903869,0.51787866,-0.01583895
|
||||
0.96859237,0.88141546,0.00687319,-0.00608468,0.00903869,0.51787866,-0.01583895
|
||||
0.96859237,0.95725723,0.00700920,-0.00689971,0.00960732,0.55045893,-0.01498307
|
||||
0.96859237,0.95725723,0.00700920,-0.00689971,0.00960732,0.55045893,-0.01498307
|
||||
0.96859237,1.03310019,0.00713515,-0.00778907,0.01014720,0.58139184,-0.01415055
|
||||
0.96859237,1.03310019,0.00713515,-0.00778907,0.01014720,0.58139184,-0.01415055
|
||||
0.96859237,1.03310019,0.00713515,-0.00778907,0.01014720,0.58139184,-0.01415055
|
||||
1.16231085,1.10894211,0.00726042,-0.00669123,0.01065172,0.61029832,-0.01341959
|
||||
1.16231085,1.10894211,0.00726042,-0.00669123,0.01065172,0.61029832,-0.01341959
|
||||
1.16231085,1.18478524,0.00737056,-0.00762005,0.01113609,0.63805077,-0.01265483
|
||||
1.16231085,1.18478524,0.00737056,-0.00762005,0.01113609,0.63805077,-0.01265483
|
||||
1.16231085,1.18478524,0.00737056,-0.00762005,0.01113609,0.63805077,-0.01265483
|
||||
1.35602932,1.26062994,0.00748152,-0.00637523,0.01158747,0.66391290,-0.01199380
|
||||
1.35602932,1.26062994,0.00748152,-0.00637523,0.01158747,0.66391290,-0.01199380
|
||||
1.35602932,1.26062994,0.00748152,-0.00637523,0.01158747,0.66391290,-0.01199380
|
||||
1.35602932,1.33647690,0.00758559,-0.00734975,0.01201488,0.68840201,-0.01136194
|
||||
1.35602932,1.33647690,0.00758559,-0.00734975,0.01201488,0.68840201,-0.01136194
|
||||
1.35602932,1.41232342,0.00767544,-0.00837399,0.01242646,0.71198356,-0.01068873
|
||||
1.35602932,1.41232342,0.00767544,-0.00837399,0.01242646,0.71198356,-0.01068873
|
||||
1.35602932,1.41232342,0.00767544,-0.00837399,0.01242646,0.71198356,-0.01068873
|
||||
1.54974779,1.48817100,0.00776672,-0.00697691,0.01280933,0.73392042,-0.01011025
|
||||
1.54974779,1.48817100,0.00776672,-0.00697691,0.01280933,0.73392042,-0.01011025
|
||||
1.54974779,1.56401969,0.00784880,-0.00803571,0.01317490,0.75486600,-0.00952652
|
||||
1.54974779,1.56401969,0.00784880,-0.00803571,0.01317490,0.75486600,-0.00952652
|
||||
1.54974779,1.56401969,0.00784880,-0.00803571,0.01317490,0.75486600,-0.00952652
|
||||
1.54974779,1.63986944,0.00793039,-0.00914733,0.01351652,0.77443972,-0.00901153
|
||||
1.54974779,1.63986944,0.00793039,-0.00914733,0.01351652,0.77443972,-0.00901153
|
||||
1.54974779,1.63986944,0.00793039,-0.00914733,0.01351652,0.77443972,-0.00901153
|
||||
1.74346627,1.71571477,0.00801693,-0.00763172,0.01383590,0.79273881,-0.00859389
|
||||
1.74346627,1.71571477,0.00801693,-0.00763172,0.01383590,0.79273881,-0.00859389
|
||||
1.74346627,1.79153322,0.00811610,-0.00879393,0.01412922,0.80954454,-0.00833373
|
||||
1.74346627,1.79153322,0.00811610,-0.00879393,0.01412922,0.80954454,-0.00833373
|
||||
1.74346627,1.79153322,0.00811610,-0.00879393,0.01412922,0.80954454,-0.00833373
|
||||
1.93718474,1.86733628,0.00819503,-0.00718750,0.01440515,0.82535424,-0.00799888
|
||||
1.93718474,1.86733628,0.00819503,-0.00718750,0.01440515,0.82535424,-0.00799888
|
||||
1.93718474,1.94315149,0.00826230,-0.00834846,0.01467990,0.84109639,-0.00759501
|
||||
1.93718474,1.94315149,0.00826230,-0.00834846,0.01467990,0.84109639,-0.00759501
|
||||
1.93718474,1.94315149,0.00826230,-0.00834846,0.01467990,0.84109639,-0.00759501
|
||||
1.93718474,2.01899269,0.00832462,-0.00954682,0.01495832,0.85704867,-0.00714926
|
||||
1.93718474,2.01899269,0.00832462,-0.00954682,0.01495832,0.85704867,-0.00714926
|
||||
1.93718474,2.01899269,0.00832462,-0.00954682,0.01495832,0.85704867,-0.00714926
|
||||
2.13090322,2.09483157,0.00838160,-0.00783096,0.01522241,0.87218005,-0.00671273
|
||||
2.13090322,2.09483157,0.00838160,-0.00783096,0.01522241,0.87218005,-0.00671273
|
||||
2.13090322,2.17067090,0.00843203,-0.00904579,0.01547453,0.88662504,-0.00627153
|
||||
2.13090322,2.17067090,0.00843203,-0.00904579,0.01547453,0.88662504,-0.00627153
|
||||
2.13090322,2.17067090,0.00843203,-0.00904579,0.01547453,0.88662504,-0.00627153
|
||||
2.32462169,2.24651112,0.00848551,-0.00725698,0.01570701,0.89994551,-0.00590798
|
||||
2.32462169,2.24651112,0.00848551,-0.00725698,0.01570701,0.89994551,-0.00590798
|
||||
2.32462169,2.32235240,0.00853515,-0.00849727,0.01592745,0.91257581,-0.00555686
|
||||
2.32462169,2.32235240,0.00853515,-0.00849727,0.01592745,0.91257581,-0.00555686
|
||||
2.32462169,2.32235240,0.00853515,-0.00849727,0.01592745,0.91257581,-0.00555686
|
||||
2.32462169,2.39819475,0.00858501,-0.00977015,0.01613298,0.92435149,-0.00525193
|
||||
2.32462169,2.39819475,0.00858501,-0.00977015,0.01613298,0.92435149,-0.00525193
|
||||
2.32462169,2.39819475,0.00858501,-0.00977015,0.01613298,0.92435149,-0.00525193
|
||||
2.51834017,2.47403815,0.00863309,-0.00790797,0.01632640,0.93543389,-0.00497174
|
||||
2.51834017,2.47403815,0.00863309,-0.00790797,0.01632640,0.93543389,-0.00497174
|
||||
2.51834017,2.54988252,0.00867713,-0.00919601,0.01651057,0.94598579,-0.00469452
|
||||
2.51834017,2.54988252,0.00867713,-0.00919601,0.01651057,0.94598579,-0.00469452
|
||||
2.51834017,2.54988252,0.00867713,-0.00919601,0.01651057,0.94598579,-0.00469452
|
||||
2.71205864,2.62572779,0.00871992,-0.00727771,0.01668355,0.95589682,-0.00444261
|
||||
2.71205864,2.62572779,0.00871992,-0.00727771,0.01668355,0.95589682,-0.00444261
|
||||
2.71205864,2.70157388,0.00876027,-0.00858164,0.01684721,0.96527392,-0.00420383
|
||||
2.71205864,2.70157388,0.00876027,-0.00858164,0.01684721,0.96527392,-0.00420383
|
||||
2.71205864,2.70157388,0.00876027,-0.00858164,0.01684721,0.96527392,-0.00420383
|
||||
2.71205864,2.77742071,0.00879990,-0.00990901,0.01700060,0.97406235,-0.00399130
|
||||
2.71205864,2.77742071,0.00879990,-0.00990901,0.01700060,0.97406235,-0.00399130
|
||||
2.71205864,2.77742071,0.00879990,-0.00990901,0.01700060,0.97406235,-0.00399130
|
||||
2.90577711,2.85326820,0.00883746,-0.00793510,0.01714559,0.98236967,-0.00379075
|
||||
2.90577711,2.85326820,0.00883746,-0.00793510,0.01714559,0.98236967,-0.00379075
|
||||
2.90577711,2.92911901,0.00886680,-0.00926808,0.01728350,0.99027145,-0.00356037
|
||||
2.90577711,2.92911901,0.00886680,-0.00926808,0.01728350,0.99027145,-0.00356037
|
||||
2.90577711,2.92911901,0.00886680,-0.00926808,0.01728350,0.99027145,-0.00356037
|
||||
3.09949559,3.00498918,0.00886464,-0.00721722,0.01740939,0.99748445,-0.00316886
|
||||
3.09949559,3.00498918,0.00886464,-0.00721722,0.01740939,0.99748445,-0.00316886
|
||||
3.09949559,3.08085990,0.00885711,-0.00852826,0.01752751,1.00425232,-0.00276742
|
||||
3.09949559,3.08085990,0.00885711,-0.00852826,0.01752751,1.00425232,-0.00276742
|
||||
3.09949559,3.08085990,0.00885711,-0.00852826,0.01752751,1.00425232,-0.00276742
|
||||
3.09949559,3.15675651,0.00886190,-0.00986926,0.01763259,1.01027270,-0.00248214
|
||||
3.09949559,3.15675651,0.00886190,-0.00986926,0.01763259,1.01027270,-0.00248214
|
||||
3.09949559,3.15675651,0.00886190,-0.00986926,0.01763259,1.01027270,-0.00248214
|
||||
3.29321406,3.23269616,0.00886843,-0.00779355,0.01772399,1.01550975,-0.00224838
|
||||
3.29321406,3.23269616,0.00886843,-0.00779355,0.01772399,1.01550975,-0.00224838
|
||||
3.29321406,3.30862946,0.00887677,-0.00914895,0.01780820,1.02033464,-0.00204789
|
||||
3.29321406,3.30862946,0.00887677,-0.00914895,0.01780820,1.02033464,-0.00204789
|
||||
3.29321406,3.30862946,0.00887677,-0.00914895,0.01780820,1.02033464,-0.00204789
|
||||
3.29321406,3.38455921,0.00888981,-0.01052090,0.01788285,1.02461183,-0.00190544
|
||||
3.29321406,3.38455921,0.00888981,-0.01052090,0.01788285,1.02461183,-0.00190544
|
||||
3.48693254,3.46048591,0.00890388,-0.00842674,0.01795176,1.02855989,-0.00178633
|
||||
3.48693254,3.46048591,0.00890388,-0.00842674,0.01795176,1.02855989,-0.00178633
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|
||||
|
821
stanley_vel_effor_x_1.2_y_z_data/stanley_0.96_1.2_3.0_6.0.csv
Normal file
821
stanley_vel_effor_x_1.2_y_z_data/stanley_0.96_1.2_3.0_6.0.csv
Normal file
@ -0,0 +1,821 @@
|
||||
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134
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134
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Loading…
Reference in New Issue
Block a user