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Functions298 in github.com/CHH3213/chhRobotics_CPP

↓ 70 callersFunctionget_array
matplotlibcpp.h:359
↓ 70 callersFunctionplot
matplotlibcpp.h:442
↓ 19 callersFunctionshow
matplotlibcpp.h:2542
↓ 17 callersFunctionsave
matplotlibcpp.h:2625
↓ 14 callersFunctiongrid
matplotlibcpp.h:2525
↓ 14 callersFunctionpause
matplotlibcpp.h:2611
↓ 10 callersFunctionclf
matplotlibcpp.h:2668
↓ 8 callersFunctionylim
matplotlibcpp.h:2029
↓ 7 callersFunctionget_2darray
matplotlibcpp.h:379
↓ 6 callersMethodgetState
* 状态获取 * @return */
PathTracking/utils/KinematicModel.cpp:33
↓ 6 callersMethodupdateState
* 控制量为转向角delta_f和加速度a * @param accel 加速度 * @param delta_f 转向角控制量 */
PathTracking/utils/KinematicModel.cpp:22
↓ 5 callersFunctionfigure
matplotlibcpp.h:1875
↓ 4 callersMethodcalc_d
PathTracking/Model_Predictive_Speed_Steel_Control/cubic_spline.hpp:73
↓ 4 callersFunctiondistanceBetweenPoints
PathPlanning/utils/geometry_utils.h:19
↓ 3 callersFunctionaxis
matplotlibcpp.h:2338
↓ 3 callersFunctiondraw
matplotlibcpp.h:2597
↓ 3 callersFunctionfactorial
* 阶乘实现 * @param n * @return */
PathPlanning/Bezier/BezierCurve.cpp:13
↓ 3 callersFunctionnormalizeAngle
* 角度归一化 * @param angle * @return */
PathTracking/utils/NormalizeAngle.hpp:15
↓ 3 callersFunctionvec_diff
PathTracking/Model_Predictive_Speed_Steel_Control/cubic_spline.hpp:18
↓ 2 callersFunctionbaseFunction
* 基函数定义 * @param i * @param k B样条阶数k * @param u 自变量 * @param node_vector 节点向量 array([u0,u1,u2,...,u_n+k],shape=[1,n+k+1]. */
PathPlanning/B-spline/BSpline.cpp:14
↓ 2 callersFunctioncalTargetIndex
* 得到距离参考轨迹最近点的下标 * @param robot_state 机器人状态(x,y) * @param refer_path 参考路径 * @return 距离参考轨迹最近点的下标 */
PathTracking/PID/main.cpp:26
↓ 2 callersMethodcalc
PathTracking/Model_Predictive_Speed_Steel_Control/cubic_spline.hpp:64
↓ 2 callersMethodcalcTrackError
* 计算跟踪误差 * @param robot_state 机器人状态 * @return */
PathTracking/utils/MyReferencePath.cpp:50
↓ 2 callersMethodcalc_dd
PathTracking/Model_Predictive_Speed_Steel_Control/cubic_spline.hpp:82
↓ 2 callersFunctioncalc_nearest_index
* 计算参考轨迹上离当前状态最近的路点 * @param state * @param cx * @param cy * @param cyaw * @param pind * @return */
PathTracking/Model_Predictive_Speed_Steel_Control/ModelPredictiveControl.cpp:35
↓ 2 callersFunctionclosestPointOnSegment
* compute segment p1p2's closed point to point p. * @param p1 * @param p2 * @param p * @return */
PathPlanning/utils/geometry_utils.h:30
↓ 2 callersMethodsetAnEnd
PathPlanning/Rapidly-exploring_Random_Tree_connect/RRT_connect.cpp:146
↓ 2 callersMethodsetBegin
PathPlanning/Rapidly-exploring_Random_Tree_connect/RRT_connect.cpp:142
↓ 2 callersMethodstateSpace
* 将模型离散化后的状态空间表达 * @param ref_delta 名义控制输入 * @param ref_yaw 名义偏航角 * @return */
PathTracking/utils/KinematicModel.cpp:43
↓ 2 callersFunctiontitle
matplotlibcpp.h:2296
↓ 2 callersFunctionxlabel
matplotlibcpp.h:2431
↓ 2 callersFunctionxlim
matplotlibcpp.h:2048
↓ 2 callersFunctionylabel
matplotlibcpp.h:2452
↓ 1 callersFunctionarrow
matplotlibcpp.h:856
↓ 1 callersFunctionbezierCommon
* 贝塞尔公式 * @param Ps * @param t * @return */
PathPlanning/Bezier/BezierCurve.cpp:24
↓ 1 callersMethodcalObstacleMap
* 得到障碍物信息图,有障碍物的地方标记为true,没有标记为false * @param ox 障碍物x坐标集合 * @param oy 障碍物y坐标集合 */
PathPlanning/A_Star/Astar.cpp:16
↓ 1 callersMethodcalObstacleMap
* 得到障碍物信息图,有障碍物的地方标记为true,没有标记为false * @param ox 障碍物x坐标集合 * @param oy 障碍物y坐标集合 */
PathPlanning/Dijkstra/Dijkstra.cpp:16
↓ 1 callersMethodcalOutput
* 计算控制输出 * @param state 当前状态量 * @return */
PathTracking/PID/PID_controller.cpp:50
↓ 1 callersMethodcalTargetIndex
* 计算邻近路点 * @param robot_state 当前机器人位置 * @param refer_path 参考轨迹(数组) * @param l_d 前向距离 * @return */
PathTracking/Pure_Pursuit/PurePursuit.cpp:14
↓ 1 callersMethodcalc_curvature
PathTracking/Model_Predictive_Speed_Steel_Control/cubic_spline.hpp:145
↓ 1 callersMethodcalc_postion
PathTracking/Model_Predictive_Speed_Steel_Control/cubic_spline.hpp:139
↓ 1 callersFunctioncalc_ref_trajectory
* 参考轨迹 * @param state * @param cx * @param cy * @param cyaw * @param ck * @param sp * @param dl * @param target_ind * @param xref */
PathTracking/Model_Predictive_Speed_Steel_Control/ModelPredictiveControl.cpp:95
↓ 1 callersMethodcalc_ref_trajectory
* 计算参考轨迹点,统一化变量数组,只针对MPC优化使用 * @param robot_state 车辆的状态(x,y,yaw,v) * @param param 超參數 * @param dl Defaults to 1.0. * @return {xref, dref, ind}结构体
PathTracking/utils/MyReferencePath.cpp:91
↓ 1 callersFunctioncalc_speed_profile
PathTracking/Model_Predictive_Speed_Steel_Control/ModelPredictiveControl.cpp:58
↓ 1 callersMethodcalc_yaw
PathTracking/Model_Predictive_Speed_Steel_Control/cubic_spline.hpp:153
↓ 1 callersFunctioncla
matplotlibcpp.h:2680
↓ 1 callersFunctioncum_sum
PathTracking/Model_Predictive_Speed_Steel_Control/cubic_spline.hpp:26
↓ 1 callersMethoddubins_path_planning
PathPlanning/Dubins_Path/Dubins.cpp:379
↓ 1 callersMethoddwaControl
* 滚动窗口算法控制器 * @param state 机器人当前状态--[x,y,yaw,v,w] * @param goal 目标点位置,[x,y] * @param obstacle 障碍物位置,dim:[num_ob,2] * @return 最优控制量[v,w]、最优轨迹 */
PathPlanning/Dynamic_Window_Approach/DWA.cpp:234
↓ 1 callersFunctionfill
matplotlibcpp.h:790
↓ 1 callersMethodgetMotionModel
* 标记移动代价 * @return */
PathPlanning/A_Star/Astar.cpp:60
↓ 1 callersMethodgetMotionModel
* 标记移动代价 * @return */
PathPlanning/Dijkstra/Dijkstra.cpp:60
↓ 1 callersFunctionget_listlist
matplotlibcpp.h:427
↓ 1 callersMethodkinematicModel
* 机器人运动学模型 * @param state 状态量---x,y,yaw,v,w * @param control 控制量---v,w,线速度和角速度 * @param dt 采样时间 * @return 下一步的状态 */
PathPlanning/Dynamic_Window_Approach/DWA.cpp:92
↓ 1 callersMethodlinearMPCControl
PathTracking/MPC/MPCControl.cpp:5
↓ 1 callersMethodlqrControl
* LQR控制器 * @param robot_state * @param refer_path * @param s0 * @param A * @param B * @param Q * @param R * @return */
PathTracking/LQR/LQRControl.cpp:47
↓ 1 callersFunctionmpc_simulation
PathTracking/Model_Predictive_Speed_Steel_Control/ModelPredictiveControl.cpp:244
↓ 1 callersFunctionmpc_solve
PathTracking/Model_Predictive_Speed_Steel_Control/ModelPredictiveControl.cpp:152
↓ 1 callersMethodplanning
* 规划 * @param start 起点 * @param goal 终点 * @return 规划后的路径 */
PathPlanning/A_Star/Astar.cpp:139
↓ 1 callersMethodplanning
* 规划 * @param start 起点 * @param goal 终点 * @return 规划后的路径 */
PathPlanning/Dijkstra/Dijkstra.cpp:139
↓ 1 callersMethodplanning
PathPlanning/Rapidly-exploring_Random_Tree_Star/RRT_Star.cpp:15
↓ 1 callersMethodplanning
* rrt path planning,两边同时进行搜索 * @return 轨迹数据 */
PathPlanning/Rapidly-exploring_Random_Tree_connect/RRT_connect.cpp:243
↓ 1 callersMethodplanning
* rrt path planning * @return 轨迹数据 */
PathPlanning/Rapidly-exploring_Random_Tree/RRT.cpp:213
↓ 1 callersFunctionplotArrow
* 画箭头 * @param x * @param y * @param yaw * @param len * @param width */
PathPlanning/Dynamic_Window_Approach/main.cpp:18
↓ 1 callersFunctionplotRobot
PathPlanning/Dynamic_Window_Approach/main.cpp:24
↓ 1 callersMethodpurePursuitControl
* purePursuitControl * @param robot_state 当前机器人位置 * @param current_ref_point 参考轨迹点 * @param l_d 前向距离 * @param psi 机器人航向角 * @param L 轴距 * @return
PathTracking/Pure_Pursuit/PurePursuit.cpp:40
↓ 1 callersMethodrearWheelFeedbackControl
* 后轮位置反馈控制 * @param robot_state 机器人位姿,包括x,y,yaw,v * @param e 误差 * @param k 曲率 * @param ref_psi 参考轨迹上点的切线方向的角度 * @return */
PathTracking/Rear_Wheel_Feedback/RearWheelFeedback.cpp:30
↓ 1 callersMethodreedsSheppPathPlanning
PathPlanning/Reeds_Shepp_Path/ReedsShepp.cpp:426
↓ 1 callersMethodrunAPF
* 人工势场法控制器 * @param robot_state * @return 车辆下一步位置 */
PathPlanning/Artifical_Potential_Field/APF.cpp:115
↓ 1 callersMethodsetAnEnd
PathPlanning/Rapidly-exploring_Random_Tree/RRT.cpp:136
↓ 1 callersMethodsetBegin
PathPlanning/Rapidly-exploring_Random_Tree/RRT.cpp:132
↓ 1 callersMethodsetD
PathPlanning/Artifical_Potential_Field/APF.cpp:38
↓ 1 callersMethodsetGo
PathPlanning/A_Star/Astar.cpp:222
↓ 1 callersMethodsetGo
PathPlanning/Dijkstra/Dijkstra.cpp:221
↓ 1 callersMethodsetLenStep
PathPlanning/Artifical_Potential_Field/APF.cpp:50
↓ 1 callersMethodsetObstaclePos
PathPlanning/Artifical_Potential_Field/APF.cpp:16
↓ 1 callersMethodsetOx
PathPlanning/A_Star/Astar.cpp:226
↓ 1 callersMethodsetOx
PathPlanning/Dijkstra/Dijkstra.cpp:225
↓ 1 callersMethodsetOy
PathPlanning/A_Star/Astar.cpp:230
↓ 1 callersMethodsetOy
PathPlanning/Dijkstra/Dijkstra.cpp:229
↓ 1 callersMethodsetSt
PathPlanning/A_Star/Astar.cpp:218
↓ 1 callersMethodsetSt
PathPlanning/Dijkstra/Dijkstra.cpp:217
↓ 1 callersMethodsetTargetPos
PathPlanning/Artifical_Potential_Field/APF.cpp:12
↓ 1 callersMethodsetW
PathPlanning/Artifical_Potential_Field/APF.cpp:42
↓ 1 callersFunctionsmooth_yaw
PathTracking/Model_Predictive_Speed_Steel_Control/ModelPredictiveControl.cpp:137
↓ 1 callersMethodstanleyControl
* stanley控制 * @param robot_state 机器人位姿,包括x,y,yaw,v * @param refer_path 参考轨迹的位置和参考轨迹上点的切线方向的角度 x,y,theta * @return 控制量+目标点索引 */
PathTracking/Stanley/Stanley.cpp:47
↓ 1 callersFunctionu_piecewise_B_Spline
* 分段B样条 * 首末值定义为 0 和 1 * 分段Bezier曲线的节点向量计算,共n+1个控制顶点,k阶B样条,k-1次曲线 * 分段Bezier端节点重复度为k,内间节点重复度为k-1,且满足n/(k-1)为正整数 * @param n 控制点个数-1,控制点共n+1个 * @pa
PathPlanning/B-spline/BSpline.cpp:70
↓ 1 callersFunctionu_quasi_uniform
* 准均匀B样条的节点向量计算 * 首末值定义为 0 和 1 * @param n 控制点个数-1,控制点共n+1个 * @param k B样条阶数k, k阶B样条,k-1次曲线. * @return */
PathPlanning/B-spline/BSpline.cpp:46
↓ 1 callersFunctionupdate_state
* 车辆状态更新 * @param state * @param a 加速度 * @param delta 转角控制量 */
PathTracking/Model_Predictive_Speed_Steel_Control/ModelPredictiveControl.cpp:13
↓ 1 callersMethod~_interpreter
matplotlibcpp.h:287
MethodAPF
PathPlanning/Artifical_Potential_Field/APF.cpp:7
MethodAstar
PathPlanning/A_Star/Astar.cpp:9
MethodDWA
PathPlanning/Dynamic_Window_Approach/DWA.cpp:7
MethodDijkstra
PathPlanning/Dijkstra/Dijkstra.cpp:9
MethodDiscreteStateSpace
PathTracking/utils/LateralErrorModel.cpp:39
MethodFG_EVAL
PathTracking/Model_Predictive_Speed_Steel_Control/ModelPredictiveControl.cpp:319
MethodGenerateStateSpace
PathTracking/utils/LateralErrorModel.cpp:9
MethodKinematicModel
* 机器人运动学模型构造 * @param x 位置x * @param y 位置y * @param psi 偏航角 * @param v 速度 * @param l 轴距 * @param dt 采样时间 */
PathTracking/utils/KinematicModel.cpp:15
MethodLQRControl
PathTracking/LQR/LQRControl.cpp:8
MethodLateralErrorModel
PathTracking/utils/LateralErrorModel.cpp:6
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