Distributed Coordination and Data Fusion for Underwater Search
This paper presents coordination and data fusion methods for teams of vehicles performing target search tasks without guaranteed communication. A fully distributed team planning algorithm is proposed that utilizes limited shared information as it becomes available, and data fusion techniques are introduced for merging estimates of the target’s position from vehicles that regain contact after long periods of time. The proposed data fusion techniques are shown to avoid overcounting information, which ensures that combining data from different vehicles will not decrease the performance of the search. Motivated by the underwater search domain, a realistic underwater acoustic communication channel is used to determine the probability of successful data transfer between two locations. The channel model is integrated into a simulation of multiple autonomous vehicles in both open ocean and harbor search scenarios. The simulated experiments demonstrate that distributed coordination with limited communication signifi- cantly improves team performance versus prior techniques that continually maintain connectivity.
Geoffrey A. Hollinger Srinivas Yerramalli Sanjiv Singh Urbashi Mitra Gaurav S. Sukhatme
Dept. of Computer Science,Viterbi School of Engineering,University of Southern California,Los Angele Dept. of Electrical Engineering,Viterbi School of Engineering,University of Southern California,Los Robotics Institute,School of Computer Science,Carnegie Mellon University,Pittsburgh,PA 15213 USA
国际会议
2011 IEEE International Conference on Robotics and Automation(2011年IEEE世界机器人与自动化大会 ICRA 2011)
上海
英文
349-355
2011-05-09（万方平台首次上网日期，不代表论文的发表时间）