计算机工程与应用2025，Vol.61Issue(20)：105-113,9.DOI:10.3778/j.issn.1002-8331.2406-0128
未知环境应用OSPGB的清洁机器人全覆盖路径规划
Full Coverage Path Planning for Cleaning Robots with Unknown Environment Application of OSPGB
摘要
Abstract
Aiming at the problem of high repetition rate and high number of turns of the paths of multiple robots performing cleaning tasks in unknown environments,a coverage algorithm guided by obstacles and starting points and fused with a backtracking mechanism(OSPGB)is proposed,and a local raster activity value(LRA)function is added to the algorithm to assist decision-making,which is applied to the path planning of cleaning robots.Firstly,the raster map is used to repre-sent the area to be cleaned,and the working environment is covered by the guidance of obstacles and starting points,and a backtracking mechanism is added to the algorithm to help the robot to get out of the"dead zone",and at the same time to avoid backtracking area conflicts between the robots as well as the emergence of long backtracking paths.Secondly,the LRA function is introduced to optimize the algorithm to reduce the number of turns and the length of the path covered by the robot.Finally,simulation experiments are conducted in different environments,and the obtained path lengths are reduced by 17.9%and 17.6%compared with the biologically inspired neural network(BINN)algorithm and the boustro-phedon A*(BA*)algorithm,respectively,and the number of turns is reduced by 18.0%and 34.7%compared with the BA*algorithm and the decentralized predator-prey modeling algorithm(R-DPPCPP),respectively.This verifies the effec-tiveness of the proposed algorithm in the full-coverage path planning of cleaning robots.关键词
多机器人/未知环境/全覆盖算法/回溯机制/活性值函数/路径规划Key words
multi-robot/unknown environment/full coverage algorithm/backtracking mechanism/activity value function/path planning分类
信息技术与安全科学引用本文复制引用
张方方,蔡一飞,辛健斌,彭金柱,刘艳红..未知环境应用OSPGB的清洁机器人全覆盖路径规划[J].计算机工程与应用,2025,61(20):105-113,9.基金项目
河南省自然科学基金面上项目(242300421400) （242300421400）
国家自然科学基金面上项目(62173311). （62173311）
