Decentralized cooperative trajectory estimation for autonomous underwater vehicles
Author(s)Paull, Liam; Seto, Mae; Leonard, John Joseph
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Autonomous agents that can communicate and make relative measurements of each other can improve their collective localization accuracies. This is referred to as cooperative localization (CL). Autonomous underwater vehicle (AUV) CL is constrained by the low throughput, high latency, and unreliability of of the acoustic channel used to communicate when submerged. Here we propose a CL algorithm specifically designed for full trajectory, or maximum a posteriori, estimation for AUVs. The method is exact and has the advantage that the broadcast packet sizes increase only linearly with the number of AUVs in the collective and do not grow at all in the case of packet loss. The approach allows for AUV missions to be achieved more efficiently since: 1) vehicles waste less time surfacing for GPS fixes, and 2) payload data is more accurately localized through the smoothing approach.
DepartmentMassachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory; Massachusetts Institute of Technology. Department of Mechanical Engineering
Proceedings of the 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
Institute of Electrical and Electronics Engineers (IEEE)
Paull, Liam, Mae Seto, and John J. Leonard. “Decentralized Cooperative Trajectory Estimation for Autonomous Underwater Vehicles.” 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems (September 2014).
Author's final manuscript