Swarm Robot Task Planning Based on Air and Ground Coordination for Disaster Search and Rescue

doi:10.3901/JME.2019.11.001

Abstract

Abstract: A novel method of swarm robot task planning based on air and ground coordination is proposed for earthquake search and rescue. A surveillance aircraft gets the positions of the damaged buildings, and passes this information to the UAV swarm. The UAV swarm uses a decentralized method to plan the searching paths based on this information. They get the positions and number of the injured people, and pass this information to the unmanned vehicles. The vehicles rescue the people according to it. A method of communication-maintain-based auction (CMBA) is provided for the UAV planning, considering the UAV features including that they are cheap, small and easy to be deployed massively. A planning method for the unmanned vehicles is provided, which is a centralized approach of adaptive-feedback-based adjustment-GA (AFBA-GA). Compared with traditional GA, our method is easier to escape from local optimum. By the experiments in the simulated robot environment and the tests on a CVRP benchmark, the effectiveness of the planning methods is validated.

Key words: AFBA-GA, air and ground coordination, CMBA, disaster search and rescue

CLC Number:

TG156

LI Minglong, YANG Wenjing, YI Xiaodong, WANG Yanzhen, WANG Ji. Swarm Robot Task Planning Based on Air and Ground Coordination for Disaster Search and Rescue[J]. Journal of Mechanical Engineering, 2019, 55(11): 1-9.

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