基于离散采样的多模态四足机器人路径规划

doi:10.13229/j.cnki.jdxbgxb.20240155

Abstract

Abstract:

Aiming at the challenges of unnecessary leap and significant undulations terrains with large steering angles in path planning of multimodal quadruped robots by Rapidly Exploring Random Tree algorithm， a path planning algorithm solution based on discrete sampling is proposed. The path is preprocessed to remove unnecessary leap and a solution set is obtained by discrete sampling and dynamic programming method. B-spline curves are used to define spline segments and quadratic programming method is used to optimize the final path. The simulation results show that paths planned by the proposed method exhibit an average reduction of 31.4% in the adjustment of robot's center of mass height， a 13.4% decrease in undulation of terrain， an 11.4% reduction in terrain slope angle and a 62.7% reduction in steering angle， which affirm the effectiveness of the proposed method.

Key words: artificial intelligence, quadruped robot, multimodal, path planning, discrete sampling, quadratic programming

CLC Number:

TP242

Shuai-shuai SUN,Chun-xiao FENG,Liang ZHANG. Path planning for multimodal quadruped robots based on discrete sampling[J].Journal of Jilin University(Engineering and Technology Edition), 2024, 54(4): 1120-1128.

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参数	数值/m
地图长度	12.4
地图宽度	12.4
地图网格分辨率	0.2
初始质心相对地面的高度	0.3

算法	路径长度	质心变化	地形起伏	地形倾斜	转向变化
KD-RRT-Connect	16.667	2.744	2.266	11.549	11.098
改进算法	15.703	1.882	1.962	10.238	4.141

算法	路径长度	质心变化	地形起伏	地形倾斜	转向变化
KD-RRT-Connect	1.575	0.321	0.363	2.028	35.520
改进算法	0.896	0.231	0.341	2.268	2.269

Path planning for multimodal quadruped robots based on discrete sampling

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