Optimal Multirobot Coverage Path Planning: Ideal-Shaped Spanning Tree. (25th September 2018)

• Record Type: Journal Article
• Authors: Gao, Chunqing; Kou, Yingxin; Li, Zhanwu; Xu, An; Li, You; Chang, Yizhe
• Other Names: Naddeo Alessandro Academic Editor.
• Is Part Of: Mathematical problems in engineering. Volume 2018(2018)
• Publication Date: 2018-09-25
• Subjects: Engineering mathematics -- Periodicals; 510.2462
• DOI: 10.1155/2018/3436429
• Languages: English
• ISSNs: 1024-123X

Abstract

Abstract : The present paper attempts to find the optimal coverage path for multiple robots in a given area including obstacles. For single robot coverage path planning (CPP) problem, an improved ant colony optimization (ACO) algorithm is proposed to construct the best spanning tree and then obtain the optimal path, which contributes to minimizing the energy/time consumption. For the multirobot case, first the DARP (Divide Areas based on Robots Initial Positions) algorithm is utilized to divide the area into separate equal subareas, so much so that it transforms the mCPP problem into several CPP problems, degrading the computation complexity. During the second phase, spanning tree in each subarea is constructed by the aforementioned algorithm. In the last phase, the specific end nodes are exchanged among subareas to achieve ideal-shaped spanning trees, which can also decrease the number of turns in coverage path. And the complete algorithms are proven to be approximately polynomial algorithms. Finally, the simulation confirms the complete algorithms' advantages: complete coverage, nonbacktracks, minimum length, zero preparation time, and the least number of turns.