Multitarget Search of Swarm Robots in Unknown Complex Environments
You Zhou,
Anhua Chen,
Hongqiang Zhang,
Xin Zhang and
Shaowu Zhou
Complexity, 2020, vol. 2020, 1-12
Abstract:
When searching for multiple targets in an unknown complex environment, swarm robots should firstly form a number of subswarms autonomously through a task division model and then each subswarm searches for a target in parallel. Based on the probability response principle and multitarget division strategy, a closed-loop regulation strategy is proposed, which includes target type of member, target response intensity evaluation, and distance to the corresponding individuals. Besides, it is necessary to make robots avoid other robots and convex obstacles with various shapes in the unknown complex environment. By decomposing the multitarget search behavior of swarm robots, a simplified virtual-force model (SVF-Model) is developed for individual robots, and a control method is designed for swarm robots searching for multiple targets (SRSMT-SVF). The simulation results indicate that the proposed method keeps the robot with a good performance of collision avoidance, effectively reducing the collision conflicts among the robots, environment, and individuals.
Date: 2020
References: Add references at CitEc
Citations:
Downloads: (external link)
http://downloads.hindawi.com/journals/8503/2020/8643120.pdf (application/pdf)
http://downloads.hindawi.com/journals/8503/2020/8643120.xml (text/xml)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:hin:complx:8643120
DOI: 10.1155/2020/8643120
Access Statistics for this article
More articles in Complexity from Hindawi
Bibliographic data for series maintained by Mohamed Abdelhakeem ().