An Unmanned Swarm Search Method Based on Human-Robot Cooperation

doi:10.16182/j.issn1004731x.joss.20-0898

Abstract

Abstract:

Human-robot collaboration is a research hotspot and the human and unmanned swarm collaborative search is a typical scenario. It can carry out the more complex tasks by combining the human complex reasoning capabilities with repeated and precise execution capabilities of unmanned swarm. Based on the high-value target search of the uncertain scenarios, the concept definition for the collaborative search of human and unmanned swarm is given. A multi-agent dynamic programming model under uncertain with unknown prior knowledge is proposed, established to describe how the multi-agent system carries out the search under human support. A dynamic programming algorithm based on sequential allocation is proposed and the simulation experiments are carried out. The experimental results show that the performance of the algorithm is significantly better than that of the basic algorithm.

Key words: unmanned swarm, human-robot collaboration, dynamic planning, multi-agent system

CLC Number:

TP391.9

Xin Zhou, Weiping Wang, Yifan Zhu, Tao Wang, Tian Jing. An Unmanned Swarm Search Method Based on Human-Robot Cooperation[J]. Journal of System Simulation, 2022, 34(4): 735-744.

Figures/Tables 5

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