复杂地形六轮独立驱动与转向机器人轨迹跟踪与避障控制

doi:10.12382/bgxb.2023.0533

摘要/Abstract

摘要：

为研究六轮移动机器人在复杂地形的运动控制方法,针对六轮独立驱动与转向机器人复杂地形轨迹跟踪问题,提出一种预测控制和动态补偿的控制方法。基于非完整约束的线性六轮移动机器人运动学模型,以模型预测控制算法为基础,引入比例-积分-微分补偿控制器,抑制动态滞后引起的跟踪误差,设计速度与转向角动态反馈补偿,以应对地形扰动对轨迹跟踪的影响。分析机器人运动过程中障碍物的避碰问题,设计可求解避障轨迹的避障规划器,通过轨迹跟踪系统对局部避障轨迹进行跟踪控制,实现机器人的轨迹跟踪和自动避碰。对轨迹跟踪算法和避障算法进行仿真实验。实验结果表明:在典型工况下,机器人可完成凹形斜坡、凸形斜坡和凹凸地形正弦型轨迹跟踪控制和静态与动态障碍物避碰,验证了新方法的有效性。

关键词: 六轮独立驱动与转向机器人, 轨迹跟踪控制, 模型预测控制, PID补偿控制, 避障控制

Abstract:

In order to study the motion control method of six-wheel mobile robot in complex terrain environment, a predictive control and dynamic compensation control method is proposed for the trajectory tracking problem of six-wheel independent drive and steering robot in complex terrain. This method is based on the nonholonomically constrained linear six-wheeled mobile robot kinematics model and the model predictive control algorithm, and introduces a proportional-integral-derivative compensation controller to suppress the tracking error caused by dynamic hysteresis. Coping with the effect of terrain disturbance on trajectory tracking. the collision avoidance problem of obstacles in the process of robot movement is analyzed, an obstacle avoidance planner that can solve the obstacle avoidance trajectory is designed to track and control the local obstacle avoidance trajectory through the trajectory tracking system, thus realizing the trajectory tracking and automatic collision avoidance of robot, and the trajectory tracking algorithm and obstacle avoidance algorithm were simulated experiments. The experimental results show that the robot can complete the sinusoidal trajectory tracking control and the static and dynamic obstacle collision avoidances in concave slope, convex slope and uneven terrain under typical working conditions, which verifies the effectiveness of the method.

Key words: six-wheel independent drive and steering robot, trajectory tracking control, model predictive control, PID compensation control, obstacle avoidance control

中图分类号:

TP242.6

刘江涛, 周乐来, 李贻斌. 复杂地形六轮独立驱动与转向机器人轨迹跟踪与避障控制[J]. 兵工学报, 2024, 45(1): 166-183.

LIU Jiangtao, ZHOU Lelai, LI Yibin. Trajectory Tracking and Obstacle Avoidance Control of Six-wheel Independent Drive and Steering Robot in Complex Terrain[J]. Acta Armamentarii, 2024, 45(1): 166-183.

图/表 35

图1 非完整约束六轮独立驱动与转向机器人运动学模型

Fig.1 Kinematic model of non-complete constraint six-wheel independent drive independent steering robot

图2 复杂地形机器人轨迹跟踪控制框图

Fig.2 Block diagram of robot trajectory tracking control in complex terrain

图3 不同地形环境机器人转向对比

Fig.3 Comparison of robot steerings in different terrain environments

图4 机器人偏离参考轨迹

Fig.4 Deviation of robot from the reference trajectory

图5 三维坐标角度表示

Fig.5 Three-dimensional coordinate angle representation

图6 PID补偿校正

Fig.6 PID compensation correction

图7 结合避障控制的轨迹规划控制系统框图

Fig.7 Block diagram of trajectory planning control system combined with obstacle avoidance control

图8 障碍物膨胀与分割点

Fig.8 Obstacle expansion and splitting point

图9 避障惩罚函数

Fig.9 Obstacle avoidance penalty function

图10 部分段轨迹拟合结果

Fig.10 Fitting results of partial segment trajectory

表1 机器人参数

Table 1 Robot parameters

参数	取值
机器人尺寸(长×宽×高)/mm	700×500×550
机器人整机质量/kg	212
轮胎尺寸/mm	宽80,直径215
驱动电机最大扭矩/(N·m)	500
转向电机最大扭矩/(N·m)	500

图11 仿真操作平台与机器人控制

Fig.11 Simulation of operating platform and robot control

图12 四轮机器人与六轮机器人轨迹跟踪误差对比

Fig.12 Comparison of trajectory tracking errors of four-wheeled robot and six-wheeled robot

图13 机器人运动凹形斜坡坐标表示

Fig.13 Concave slope coordinates during robot motion

表2 凹形斜坡实验参数

Table 2 Concave slope experimental parameters

控制器类型	参数	数值
PID控制器	系数	k_p:110, k_i:0.1, k_d:0.30
	采样时间/ms	10
Pure Pursuit	前视距离系数	0.15
控制器	前视距离/m	1.2
	采样时间/ms	10
	MPC采样周期/ms	50
MPC控制器	MPC控制步长	30
	MPC预测步长	60
	MPC采样周期/ms	50
	MPC控制步长	30
	MPC预测步长	60
本文控制器	PID采样周期/ms	10
	Yaw角放大倍数	1.13~1.25
	PID常数项比例系数	k_p:0.25, k_i:0.05, k_d:0.10
	PID增益项比例系数	λ₁:5, λ₂:1.5, λ₃:2

图14 凹形斜坡轨迹跟踪仿真

Fig.14 Trajectory tracking simulation on concave slope

图15 凹形斜坡控制器跟踪轨迹对比

Fig.15 Comparison of tracking trajectories of concave ramp controllers

图16 凹形斜坡控制器跟踪误差对比

Fig.16 Comparison of tracking errors of concave ramp contrllers

图17 凹形斜坡控制器转向角对比

Fig.17 Comparison of steering angles of concave slope controllers

图18 机器人运动凸形斜坡坐标表示

Fig.18 Convex slope coordinates duringrobot motion

表3 凸形斜坡实验参数

Table 3 Convex ramp experimental parameters

控制器类型	参数	数值
PID控制器	系数	k_p:110, k_i:0.1, k_d:0.30
	采样时间/ms	10
Pure Pursuit	前视距离系数	0.15
控制器	前视距离/m	1.2
	采样时间/ms	10
	MPC采样周期/ms	50
MPC控制器	MPC控制步长	30
	MPC预测步长	60
	MPC采样周期/ms	50
	MPC控制步长	30
	MPC预测步长	60
本文控制器	PID采样周期/ms	10
	Yaw角放大倍数	1.13~1.35
	PID常数项比例系数	k_p:0.30, k_i:0.10, k_d:0.15
	PID增益项比例系数	λ₁:5.5, λ₂:1.5, λ₃:2.5

图19 凸形斜坡轨迹跟踪仿真

Fig.19 Trajectory tracking simulation on convex slope

图20 凸形斜坡控制器跟踪轨迹对比

Fig.20 Comparison of tracking trajectories of convex ramp controllers

图21 凸形斜坡控制器跟踪误差对比

Fig.21 Comparison of tracking errors of convex ramp controllers

图22 凸形斜坡控制器转向角对比

Fig.22 Comparison of steering angles of convex ramp controllers

图23 轨迹跟踪过程机器人质心高度变化

Fig.23 The change in the height of robot’s center of mass during trajectory tracking

表4 凹凸路面实验参数

Table 4 Experimental parameters of uneven and convex roads

控制器类型	参数	数值
PID控制器	系数	k_p:110, k_i:0.1, k_d:0.30
	采样时间/ms	10
Pure Pursuit	前视距离系数	0.15
控制器	前视距离/m	1.2
	采样时间/ms	10
	MPC采样周期/ms	50
MPC控制器	MPC控制步长	30
	MPC预测步长	60
	MPC采样周期/ms	50
	MPC控制步长	30
	MPC预测步长	60
本文控制器	PID采样周期/ms	10
	Yaw角放大倍数	1.2~1.4
	PID常数项比例系数	k_p:0.32, k_i:0.13, k_d:0.16
	PID增益项比例系数	λ₁:5.8, λ₂:1.6, λ₃:2.8

图24 凹凸路面控制器跟踪轨迹对比

Fig.24 Comparison of tracking trajectories of concave and convex pavement controllers

图25 凹凸路面控制器跟踪误差对比

Fig.25 Comparison of tracking errors of concave and convex pavement controllers

图26 凹凸路面控制器转向角对比

Fig.26 Comparison of steering angles of concave and convex road controllers

图27 机器人避障流程图

Fig.27 Flowchart of robot obstacle avoidance

表5 障碍物信息

Table 5 Obstacle information

参数	障碍物A	障碍物B
质心初始坐标/m	(0.8,3.2)	(5.4,3.2)
长×宽×高/m	0.3×0.3×0.5	0.3×0.3×0.5
质量/kg	50	50
移动速度/(m·s^-1)	0	0.14~0.15

图28 DWA避障方法与本文避障方法机器人避障轨迹对比

Fig.28 Comparison of obstacle avoidance trajectories of robot by using the dynamic window method and the obstacle avoidance method in the paper

图29 DWA避障方法和本文避障方法机器人与参考轨迹距离偏差表示

Fig.29 Representation of distance deviation between the robot and the reference trajectories by the dynamic window method and the obstacle avoidance method in the paper

图30 DWA避障方法和本文避障方法机器人质心与障碍物质心距离表示

Fig.30 The distance between the robot’s center of mass and the center of the obstacle’s center of mass expressed by the dynamic window method and the obstacle avoidance method in the paper

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