Sensor-based complete coverage path planning in dynamic environment for cleaning robot

CAAI Transactions on Intelligence Technology

article

Hong Liu¹  Jiayao Ma¹  Weibo Huang¹ 

[1] Human Robot Interaction Lab, Shenzhen Graduate School, Peking University

关键词: multi-robot systems;    collision avoidance;    mobile robots;    sensors;    backtracking;    short memory model;    collision-free coverage;    obstacle position;    sensor-based complete coverage path planning;    bidding process;    global backtracking mechanism;    CCPP algorithm;    cleaning robot;    multirobot system;    dynamic environment;    deadlock problems;    C3120C Spatial variables control;    C3390C Mobile robots;   

DOI  :  10.1049/trit.2018.0009

学科分类：数学（综合）

来源: Wiley

【 摘 要 】

Using Complete Coverage Path Planning (CCPP), a cleaning robot could visit every accessible area in the workspace. The dynamic environment requires the higher computation of the CCPP algorithm because the path needs to be replanned when the path might become invalid. In previous CCPP methods, when the neighbours of the current position are obstacles or have been visited, it is challenging for the robot to escape from the deadlocks with the least extra time cost. In this study, a novel CCPP algorithm is proposed to deal with deadlock problems in a dynamic environment. A priority template inspired by the short memory model could reduce the number of deadlocks by giving the priority of directions. Simultaneously, a global backtracking mechanism guides the robot to move to the next unvisited area quickly, taking the use of the explored global environmental information. What's more, the authors extend their CCPP algorithm to a multi-robot system with a market-based bidding process which could deploy the coverage time. Experiments of apartment-like scenes show that the authors’ proposed algorithm can guarantee an efficient collision-free coverage in dynamic environments. The proposed method performs better than related approaches on coverage rate and overlap length.

【 授权许可】

CC BY|CC BY-ND|CC BY-NC|CC BY-NC-ND