Abstract
AbstractThis paper focuses on the problem of robot rescue task allocation, in which multiple robots and a global optimal algorithm are employed to plan the rescue task allocation. Accordingly, a modified particle swarm optimization (PSO) algorithm, referred to as task allocation PSO (TAPSO), is proposed. Candidate assignment solutions are represented as particles and evolved using an evolutionary process. The proposed TAPSO method is characterized by a flexible assignment decoding scheme to avoid the generation of unfeasible assignments. The maximum number of successful tasks (survivors) is considered as the fitness evaluation criterion under a scenario where the survivors’ survival time is uncertain. To improve the solution, a global best solution update strategy, which updates the global best solution depends on different phases so as to balance the exploration and exploitation, is proposed. TAPSO is tested on different scenarios and compared with other counterpart algorithms to verify its efficiency.
Funder
National Natural Science Foundation of China
Natural Science Foundation of Jiangsu Normal University
Publisher
Springer Science and Business Media LLC
Subject
General Earth and Planetary Sciences,General Environmental Science
Reference45 articles.
1. Balta H, Bedkowski J, Govindaraj S, Majek K, Musialik P, Serrano D (2017) Integrated data management for a fleet of search-and-rescue robots. J Field Robot 34(3):539–582
2. Sawas Y, Takasaki Y (2017) Natural disaster, poverty, and development: an introduction. World Dev 16:2–15
3. Konyo M, Ambe Y, Nagano H, Yamauchi Y (2019) ImPACT- TRC thin serpentine robot platform for urban search and rescue. Disaster robotics. Springer, Berlin
4. Sousa P, Ferreira A, Moreira M, Santos T (2018) ISEP/INESC TEC aerial robotics team for search and rescue operations at the euRathlon 2015. J Intell Robot Syst 5:1–14
5. Zhang HT, Song GA (2017) System centroid position based tipover stability enhancement method for a tracked search and rescue robot. Adv Robot 28(23):1571–1585
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