Computer Science

Computer Science ›› 2022, Vol. 49 ›› Issue (11A): 210900083-11.doi: 10.11896/jsjkx.210900083

• Artificial Intelligence • Previous Articles     Next Articles

Multi-UAV Cooperative Exploring for Large Unknown Indoor Environment Based on Behavior Tree

SHI Dian-xi1,2,3, SU Ya-qian-wen1, LI Ning2, SUN Yi-xuan2, ZHANG Yong-jun1   

  1. 1 National Innovation Institute of Defense Technology,Academy of Military Sciences,Beijing 100166,China
    2 School of Computer Science,National University of Defense Technology,Changsha 410073,China
    3 Tianjin Artificial Intelligence Innovation Center,Tianjin 300457,China
  • Online:2022-11-10 Published:2022-11-21
  • About author:SHI Dian-xi,born in 1966,Ph.D,professor,Ph.D supervisor.His main research interests include distributed object middleware technology,adaptive software technology,artificial intelligence and robot operation systems.
    ZHANG Yong-jun,born in 1966,Ph.D,professor.His main research interests include artificial intelligence,multi-agent cooperation,machine learning and feature recognition.

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Abstract: This paper proposes a method of using behavior tree framework to schedule multiple UAVs and path planning algorithms for collaborative exploration in a large unknown indoor space without GPS signals.The core of this method is to use the Tracking-D*Lite algorithm to track moving targets in unknown terrain,combined with the Wall-Around algorithm based on the Bug algorithm to navigate the UAV in the unknown indoor environment.Finally,the behavior tree is used to schedule and switch multiple UAVs and these two algorithms.This method is based on ROS and uses Gazebo for simulation and visualization.It designs and implements comparative experiments with other unknown indoor environment exploration methods.Experimental results show that it can effectively complete the exploration task and finally draw the boundary contour map of the entire unknown indoor environment.Once extended to the real world,this method can be applied to dangerous buildings after earthquakes,hazar-dous gas factories,underground mines,or other search and rescue scenarios.

Key words: Multi-UAV, Behavior tree, GPS-denied environment, Collaborative exploration, Path planning

CLC Number: 

  • TP391
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