现代制造工程Issue(12)：54-60,86,8.DOI:10.16731/j.cnki.1671-3133.2024.12.007
基于随机重启的机器人高斯过程运动规划
Gaussian process motion planning for robots based on random restarts
摘要
Abstract
In complex obstacle environments,mobile robots using the Gaussian Path Motion Planning(GPMP2)algorithm suffer from the problems of falling into local optimums and poor obstacle avoidance performance,a method based on stochastic restart and obstacle avoidance improvement was proposed Gaussian Process Motion Planning with Stochastic Restart and Obstacle Avoid-ance Improvement(GPMP2-SROAI).Firstly,the random restart mechanism in the Covariant Hamiltonian Optimisation for Motion Planning(CHOMP)was introduced to apply perturbations to the trajectory to jump out of the local optimum and improve the efficiency and robustness of the trajectory optimization.Then,a Model Predictive Control with Control Barrier Function(MPC-CBF)approach based on the barrier function was introduced to avoid collisions by predicting the range of motion of the robot dur-ing the optimisation process.Simulation results show that,the improved algorithm achieves a success rate of 92.6％in path plan-ning,which is 24.9％higher than that of GPMP2,12.5％higher than the path shortest probability,and 4.8％higher than the average smoothing degree,and also achieves a better quality of trajectory planning compared with the mainstream algorithms,with smoother trajectories and better obstacle avoidance effects.关键词
路径规划/随机重启/机器人避障/因子图优化Key words
path planning/random restart/robot obstacle avoidance/factor graph optimisation分类
信息技术与安全科学引用本文复制引用
袁绪清,魏媛媛,王耀力,常青,付世沫..基于随机重启的机器人高斯过程运动规划[J].现代制造工程,2024,(12):54-60,86,8.基金项目
山西省重点研发项目(201903D321003) （201903D321003）
太原供水设计研究院有限公司项目(RH2000005391) （RH2000005391）
山西省自然科学基金项目(201801D121141) （201801D121141）
