A multi-robot cooperative exploration algorithm considering working efficiency and working load
The cooperative exploration in unknown environment is a tough task for the multi-robot system. The imbalance of individual workload caused by the weak autonomous cooperation ability will affect the working efficiency of the multi-robot system. In this paper, a two-objective cooperative exploration algorithm (TOCEA) is proposed, where the working efficiency and working load at the individual and system levels are both considered. There are three parts in the proposed algorithm, namely, frontier detection, target point selection and exploration decision. First, based on the analysis of the frontier characteristics, the accumulation of local frontiers is used to replace the method of traversal search, which greatly improves the exploration efficiency. Second, each robot plays as an equal role to select their candidate target points from the individual level, and uses the maximum area criterion to select the final target points. Finally, the robot target points are clustered to reduce the repeated exploration of the robots, which is essential for reduce the path length and exploration time. Significantly, the whole exploration process is completely based on the autonomous cooperation of the robots. The experimental results performed on three different platforms illustrate that the TOCEA shows improvements in terms of working efficiency, cooperation performance and applicable fields.
Beijing Municipal Natural Science Foundation;National Natural Science Foundation of China;National Natural Science Foundation of China;National Natural Science Foundation of China;
|EI Accession Number|
Efficiency ; Industrial robots ; Robot learning
|ESI Classification Code|
Robotics:731.5 ; Robot Applications:731.6 ; Production Engineering:913.1
|ESI Research Field|
Cited Times [WOS]:0
|Document Type||Journal Article|
|Department||Department of Computer Science and Engineering|
1.School of Electronic and Information Engineering,Beihang University,Beijing,100191,China
2.School of Computer Science,Shaanxi Normal University,Xi'an,710062,China
3.Department of Computer Science and Engineering,Southern University of Science and Technology,Shenzhen,518055,China
Zhao，Meng,Lu，Hui,Cheng，Shi,et al. A multi-robot cooperative exploration algorithm considering working efficiency and working load[J]. APPLIED SOFT COMPUTING,2022,128.
Zhao，Meng,Lu，Hui,Cheng，Shi,Yang，Siyi,&Shi，Yuhui.(2022).A multi-robot cooperative exploration algorithm considering working efficiency and working load.APPLIED SOFT COMPUTING,128.
Zhao，Meng,et al."A multi-robot cooperative exploration algorithm considering working efficiency and working load".APPLIED SOFT COMPUTING 128(2022).
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