Abstract
Online task distribution is a typical problem for the cooperation of robotic swarm. However, there exist several challenges such as the distributed system, large-scale swarm and limited communication. Therefore, this paper proposes an adaptive task distribution approach based on the threshold behavior tree, which solves the task distribution problem of the large-scale robotic swarm. Through observation and perception towards outside, the robot obtains information of targets and neighboring robots in the field of view. In the condition of lacking communication, each robot makes its own decision on which kind of tasks to perform according to its threshold behavior tree. Finally, the robotic swarm can achieve the expected task distribution ratio which equals to that of the targets.
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Acknowledgments
This work is supported by National Natural Science Foundation of China (61872378, 71702186), Science Fund for Distinguished Young Scholars in Hunan Province (2018JJ1032), and Scientific Research Project of National University of Defense Technology (ZK19-03).
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Ma, L. et al. (2021). Adaptive Task Distribution Approach Using Threshold Behavior Tree for Robotic Swarm. In: Tan, Y., Shi, Y. (eds) Advances in Swarm Intelligence. ICSI 2021. Lecture Notes in Computer Science(), vol 12690. Springer, Cham. https://doi.org/10.1007/978-3-030-78811-7_14
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DOI: https://doi.org/10.1007/978-3-030-78811-7_14
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