diff --git a/.gitignore b/.gitignore index 004038b..395b527 100644 --- a/.gitignore +++ b/.gitignore @@ -11,6 +11,5 @@ log/ logs/ data/ files/ -*.csv *.png diff --git a/Readme.md b/Readme.md index 0391cc3..b8180f8 100644 --- a/Readme.md +++ b/Readme.md @@ -1,5 +1,5 @@ # auto drive misson center webots simulation: -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 +lhy本地控制测试分支，无本地控制测试需求请勿使用 ## 1, `ubuntu20.04`, `ubuntu22.04` ## 2, 安装 `webots` `https://github.com/cyberbotics/webots/tags`， 版本： `ubuntu20.04： R2023a， ubuntu22.04：R2025a` diff --git a/pp_stanley_plot_path_tracking_error.py b/error_calculate.py similarity index 92% rename from pp_stanley_plot_path_tracking_error.py rename to error_calculate.py index e6275c4..c900348 100644 --- a/pp_stanley_plot_path_tracking_error.py +++ b/error_calculate.py @@ -10,12 +10,12 @@ import matplotlib.pyplot as plt # 参数 # ============================================================ -LOG_PATTERN = "logs/mission_center_logger*.txt" +LOG_PATTERN = "path_visualizer.log" # 每 5 个完整数据取 1 个 -SAMPLE_STEP = 40 +SAMPLE_STEP = 1 -CSV_FILE = "recalculated_tracking_error.csv" +CSV_FILE = "tracking_error.csv" # ============================================================ @@ -74,6 +74,9 @@ current_path_pattern = re.compile( r"current_path_yaw:([-+0-9.eE]+)" ) +yaw_command_pattern = re.compile( + r"current_cmd_angular_z:([-+0-9.eE]+)" +) # ============================================================ # 3. 函数：角度归一化 @@ -178,6 +181,7 @@ def calculate_errors( # ============================================================ all_data = [] +yaw_command_data = [] total_raw_count = 0 @@ -202,6 +206,7 @@ for file in files: # -------------------------------------------------------- pending_pose = None + pending_yaw = None with file.open( @@ -222,7 +227,11 @@ for file in files: line ) - + m_yaw = yaw_command_pattern.search(line) + if m_yaw: + pending_yaw = float(m_yaw.group(1)) + if file_data_count % SAMPLE_STEP == 0: + yaw_command_data.append(pending_yaw) if m_pose: pending_pose = { @@ -351,6 +360,7 @@ for file in files: pending_pose = None + print( f"原始完整数据：{file_data_count}" ) @@ -447,6 +457,12 @@ alpha_deg = np.array([ for d in all_data ]) +yaw_command = yaw_command_data# 确保长度一致 + +print( + f"yaw size: {len(yaw_command)}" +) + # ============================================================ # 8. 计算车辆累计行驶距离 @@ -524,13 +540,16 @@ with open( "heading_error_deg", + "yaw_command", + ]) for i in range( len(all_data) ): - + if i>= len(yaw_command): + break writer.writerow([ f"{distance_m[i]:.8f}", @@ -545,6 +564,8 @@ with open( f"{alpha_deg[i]:.8f}", + f"{yaw_command[i]:.8f}" + ]) @@ -630,7 +651,43 @@ plt.grid(True) plt.tight_layout() plt.show() +# ============================================================ +# 14. yaw command rad +# ============================================================ +plt.figure( + figsize=(12, 5) +) + +plt.plot( + distance_m, + 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() # ============================================================ # 15. 车辆轨迹 + 路径点 diff --git a/pp_lqr_stanley_error.py b/error_comparsion.py similarity index 52% rename from pp_lqr_stanley_error.py rename to error_comparsion.py index 6a24435..fc62bdc 100644 --- a/pp_lqr_stanley_error.py +++ b/error_comparsion.py @@ -1,50 +1,67 @@ import csv import os +import re import matplotlib.pyplot as plt import numpy as np +import glob files = [ - "U_turn_0.32_lqr.csv", - "U_turn_0.32_pp.csv", - "U_turn_0.32_stanley.csv", + "stanley_*_*_*_*.csv", ] data = {} +for pattern in files: -for file in files: - if not os.path.exists(file): - raise FileNotFoundError(f"找不到文件: {file}") + matched_files = glob.glob(pattern) - distance = [] - lateral_error = [] - heading_error = [] - yaw_command = [] + if not matched_files: + raise FileNotFoundError( + f"找不到文件: {pattern}" + ) + matched_files.sort( + key=lambda x: ( + float(x.split("_")[1]), # 速度 + float(x.split("_")[2]), # 参数1 + float(x.split("_")[3]), # 参数2 + float(x.split("_")[4].replace(".csv", "")) # 半径 + ) + ) - with open(file, "r", encoding="utf-8-sig", newline="") as f: - reader = csv.DictReader(f) + print(f"匹配到 {len(matched_files)} 个文件:") + for file in matched_files: + if not os.path.exists(file): + raise FileNotFoundError(f"找不到文件: {file}") - required = {"distance_m", "lateral_error_m", "heading_error_rad","yaw_command"} - if not required.issubset(reader.fieldnames or []): - raise ValueError( - f"{file} 缺少必要列，需要: {required}，实际列: {reader.fieldnames}" - ) + distance = [] + lateral_error = [] + heading_error = [] + yaw_command = [] - for row in reader: - try: - distance.append(float(row["distance_m"])) - lateral_error.append(abs(float(row["lateral_error_m"]))) - heading_error.append(abs(float(row["heading_error_rad"]))) - yaw_command.append(float(row["yaw_command"])) - except (ValueError, TypeError): - continue + with open(file, "r", encoding="utf-8-sig", newline="") as f: + reader = csv.DictReader(f) - name = os.path.splitext(os.path.basename(file))[0] - data[name] = { - "distance": distance, - "lateral_error": lateral_error, - "heading_error": heading_error, - "yaw_command": yaw_command, - } + required = {"distance_m", "lateral_error_m", "heading_error_rad","yaw_command"} + if not required.issubset(reader.fieldnames or []): + raise ValueError( + f"{file} 缺少必要列，需要: {required}，实际列: {reader.fieldnames}" + ) + + for row in reader: + try: + distance.append(float(row["distance_m"])) + lateral_error.append(abs(float(row["lateral_error_m"]))) + heading_error.append(abs(float(row["heading_error_rad"]))) + yaw_command.append(float(row["yaw_command"])) + except (ValueError, TypeError): + continue + + name = os.path.splitext(os.path.basename(file))[0] + data[name] = { + "distance": distance, + "lateral_error": lateral_error, + "heading_error": heading_error, + "yaw_command": yaw_command, + } # 颜色由 matplotlib 自动分配，不手动指定 names = list(data.keys()) @@ -56,21 +73,20 @@ plt.figure(figsize=(12, 6)) for name in names: plt.plot( - data[name]["distance"], - data[name]["lateral_error"], + data[name]["distance"][::15], + data[name]["lateral_error"][::15], label=name, linewidth=1.5, ) - plt.xlabel("Distance (m)") plt.ylabel("Lateral Error (m)") plt.title("Lateral Error Comparison") plt.grid(True, alpha=0.3) -plt.legend(["LQR", "Pure Pursuit", "Stanley"]) +plt.legend() plt.tight_layout() -lateral_output = "U_turn_lateral_error_comparison.png" +lateral_output = "Lateral_error_comparison.png" plt.savefig(lateral_output, dpi=200) plt.show() @@ -92,10 +108,10 @@ plt.xlabel("Distance (m)") plt.ylabel("Heading Error (rad)") plt.title("Heading Error Comparison") plt.grid(True, alpha=0.3) -plt.legend(["LQR", "Pure Pursuit", "Stanley"]) +plt.legend() plt.tight_layout() -heading_output = "U_turn_heading_error_comparison.png" +heading_output = "Heading_error_comparison.png" plt.savefig(heading_output, dpi=200) plt.show() @@ -118,10 +134,10 @@ plt.xlabel("Distance (m)") plt.ylabel("Yaw Command (rad)") plt.title("Yaw Command Comparison") plt.grid(True, alpha=0.3) -plt.legend(["LQR", "Pure Pursuit", "Stanley"]) +plt.legend() plt.tight_layout() -yaw_output = "U_turn_yaw_command_comparison.png" +yaw_output = "Yaw_command_comparison.png" plt.savefig(yaw_output, dpi=200) plt.show() print("读取完成：") @@ -134,7 +150,7 @@ print(heading_output) print(yaw_output) -print("\n" + "=" * 100) +print("\n" + "=" * 90) print( f"{'Controller':<20}" f"{'Lat Max(m)':>12}" diff --git a/lqr_plot_path_tracking_error.py b/lqr_plot_path_tracking_error.py deleted file mode 100644 index 218f62f..0000000 --- a/lqr_plot_path_tracking_error.py +++ /dev/null @@ -1,355 +0,0 @@ -#!/usr/bin/env python3 -# -*- coding: utf-8 -*- - -""" -读取当前目录下： - mission_center_logger.txt - mission_center_logger1.txt - mission_center_logger2.txt - ... - -从 [path_follow] 日志中提取： - LQR: dis=..., alpha=... - path controller, current pose point:x:..., y:..., yaw:... - -绘制： - 1. 横向误差 dis 随实际行驶路程变化 - 2. 航向误差 alpha 随实际行驶路程变化 - -说明： -- dis：按你日志中的 LQR dis，单位通常是 m -- alpha：按你日志中的 alpha，单位是 rad -- 路程：根据连续 current pose 的 x/y 计算累计行驶距离 -- 日志中同一时刻可能重复打印多次，因此脚本会保留数据， - 但累计距离对相同位置不会增加。 -""" - -import re -from pathlib import Path - -import numpy as np -import matplotlib.pyplot as plt - - -# ============================================================ -# 1. 日志文件 -# ============================================================ - -LOG_PATTERN = "logs/mission_center_logger*.txt" - -files = sorted(Path(".").glob(LOG_PATTERN)) - -if not files: - raise FileNotFoundError( - f"当前目录没有找到 {LOG_PATTERN}" - ) - -print("找到日志文件：") -for f in files: - print(" ", f) - - -# ============================================================ -# 2. 正则表达式 -# ============================================================ - -# LQR: -# [LQR: dis=0.001038186, alpha=-0.003193076, ... -lqr_pattern = re.compile( - r"\[LQR:\s*" - r"dis=([-+0-9.eE]+),\s*" - r"alpha=([-+0-9.eE]+)" -) - -# current pose: -# [path controller, current pose point:x:24.68, y:1.16, yaw:0.026; -pose_pattern = re.compile( - r"current pose point:x:([-+0-9.eE]+),\s*" - r"y:([-+0-9.eE]+),\s*" - r"yaw:([-+0-9.eE]+)" -) - -yaw_command_pattern = re.compile( - r"PP output angular=([-+0-9.eE]+)" -) - -# ============================================================ -# 3. 读取日志 -# ============================================================ - -all_data = [] - -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") diff --git a/path_generate_json.py b/path_generate_json.py new file mode 100644 index 0000000..0f9293c --- /dev/null +++ b/path_generate_json.py @@ -0,0 +1,224 @@ +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 + +# 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 + }, + "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() \ No newline at end of file diff --git a/path_visualizer.log b/path_visualizer.log new file mode 100644 index 0000000..a245410 --- /dev/null +++ b/path_visualizer.log @@ -0,0 +1,3373 @@ +[2026-10-05 17:28:36.617] [path_visualizer] [info] PathVisualizer started +[2026-10-05 17:28:47.117] [path_visualizer] [debug] current_pose_x:0.0, current_pose_y:0.0,current_pose_yaw:-7.77364220994059e-06 +[2026-10-05 17:28:47.117] [path_visualizer] [debug] current_path_x:0.0, current_path_y:0.0,current_path_yaw:0.0 +[2026-10-05 17:28:47.117] [path_visualizer] [debug] current_cmd_angular_z:1.554728441988118e-05 +[2026-10-05 17:28:47.167] [path_visualizer] [debug] current_pose_x:0.0, 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[path_visualizer] [debug] current_path_x:-3.00263417952926, current_path_y:7.569009852445404,current_path_yaw:1.570796327 +[2026-10-05 17:29:43.116] [path_visualizer] [debug] current_cmd_angular_z:-0.02318458800994788 +[2026-10-05 17:29:43.166] [path_visualizer] [debug] current_pose_x:-3.0063135278401227, current_pose_y:7.663143039478612,current_pose_yaw:1.5708907842636108 +[2026-10-05 17:29:43.166] [path_visualizer] [debug] current_path_x:-3.00263417952926, current_path_y:7.569009852445404,current_path_yaw:1.570796327 +[2026-10-05 17:29:43.166] [path_visualizer] [debug] current_cmd_angular_z:-0.02318458800994788 +[2026-10-05 17:29:43.216] [path_visualizer] [debug] current_pose_x:-3.0063135278401227, current_pose_y:7.663143039478612,current_pose_yaw:1.5708907842636108 +[2026-10-05 17:29:43.216] [path_visualizer] [debug] current_path_x:-3.00263417952926, current_path_y:7.569009852445404,current_path_yaw:1.570796327 +[2026-10-05 17:29:43.216] [path_visualizer] [debug] current_cmd_angular_z:-0.02318458800994788 +[2026-10-05 17:29:43.266] [path_visualizer] [debug] current_pose_x:-3.0064544697503397, current_pose_y:7.7137222869574895,current_pose_yaw:1.5701225996017458 +[2026-10-05 17:29:43.266] [path_visualizer] [debug] current_path_x:-3.002634123680103, current_path_y:7.768194309764552,current_path_yaw:1.570796327 +[2026-10-05 17:29:43.266] [path_visualizer] [debug] current_cmd_angular_z:-0.02252942461789793 diff --git a/rviz2.jpg b/rviz2.jpg deleted file mode 100644 index 961eac3..0000000 Binary files a/rviz2.jpg and /dev/null differ diff --git a/src/webots_simulation/include/sweet_webots_robot/PathVisualizer.hpp b/src/webots_simulation/include/sweet_webots_robot/PathVisualizer.hpp index d60a864..f7d5211 100644 --- a/src/webots_simulation/include/sweet_webots_robot/PathVisualizer.hpp +++ b/src/webots_simulation/include/sweet_webots_robot/PathVisualizer.hpp @@ -23,6 +23,11 @@ #include #include +#include +#include +#include +#include + class PathVisualizer : public rclcpp::Node { public: @@ -38,6 +43,8 @@ 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); @@ -100,8 +107,8 @@ 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 +117,22 @@ private: int forward_index_limit_=100; int path_track_index_ = -1; + // stanley parametres + double k_yaw_ = 1.0; + double k_lat_ = 1.0; + 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 geodetic_converter_; + + // logger + std::shared_ptr logger_; + }; #endif diff --git a/src/webots_simulation/src/PathVisualizer.cpp b/src/webots_simulation/src/PathVisualizer.cpp index d5e5615..f97902b 100644 --- a/src/webots_simulation/src/PathVisualizer.cpp +++ b/src/webots_simulation/src/PathVisualizer.cpp @@ -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("/twist_cmd_vel",10); @@ -39,9 +42,35 @@ has_pose_(false) // urdf pose tf_broadcaster_ = std::make_unique(*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(); + + // 每次启动时清空原文件 + auto file_sink = + std::make_shared( + "./path_visualizer.log", + true // truncate：清空原文件 + ); + + std::vector sinks{ + console_sink, + file_sink + }; + + logger_ = std::make_shared( + "path_visualizer", + sinks.begin(), + sinks.end() + ); + + logger_->set_level(spdlog::level::debug); + + logger_->info("PathVisualizer started"); + } using json = nlohmann::json; @@ -122,6 +151,60 @@ void PathVisualizer::transformPathToVehicleStart(double vehicle_initial_yaw) } } + +#include +#include +#include + +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 +254,16 @@ 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(); + k_yaw_ = data["properties"]["k_yaw"].get(); + k_lat_ = data["properties"]["k_lat"].get(); // 检查 features if (!data.contains("features") || !data["features"].is_array() || @@ -601,10 +694,11 @@ void PathVisualizer::control(){ "control has not pose."); return; } - + double speed=max_speed_; publishVehicleInfoRviz(); publishLocalPose(); target_index_= findClosestPoint(forward_index_limit_); + int current_index = target_index_; int target =findLookAheadPoint(); double target_x =path_x_[target]; @@ -617,15 +711,41 @@ void PathVisualizer::control(){ double local_x =cos(yaw_)*dx+sin(yaw_)*dy; double local_y =-sin(yaw_)*dx+cos(yaw_)*dy; + 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; + /*Pure Pursuit*/ - double Ld =sqrt(local_x*local_x+local_y*local_y); - double curvature =2.0*local_y/(Ld*Ld); + // 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]; + 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); geometry_msgs::msg::Twist cmd; - double speed=max_speed_; - cmd.linear.x =speed; - cmd.angular.z =speed*curvature; + 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 +757,8 @@ void PathVisualizer::control(){ cmd.angular.z=-max_yaw_rate_; } - //cmd_pub_->publish(cmd); + cmd_pub_->publish(cmd); + logger_->debug("current_cmd_angular_z:{}",cmd.angular.z); // RCLCPP_INFO_THROTTLE( // this->get_logger(), diff --git a/stanley_k_lat_effor_0.32_1.2_1.0_x_data/stanley_0.32_1.2_1.0_0.8.csv b/stanley_k_lat_effor_0.32_1.2_1.0_x_data/stanley_0.32_1.2_1.0_0.8.csv new file mode 100644 index 0000000..7cc7c3d --- /dev/null +++ b/stanley_k_lat_effor_0.32_1.2_1.0_x_data/stanley_0.32_1.2_1.0_0.8.csv @@ -0,0 +1,2333 @@ +distance_m,current_x_m,current_y_m,lateral_error_m,heading_error_rad,heading_error_deg,yaw_command +0.00000000,0.00000000,0.00000000,0.00000000,0.00000777,0.00044540,0.00000777 +0.00000000,0.00000000,0.00000000,0.00000000,0.00000777,0.00044540,0.00000777 +0.00000000,0.00040876,0.00189316,-0.00189316,0.00001089,0.00062371,-0.00472196 +0.00000000,0.00040876,0.00189316,-0.00189316,0.00001089,0.00062371,-0.00472196 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