Journal
IEEE-ASME TRANSACTIONS ON MECHATRONICS
Volume 20, Issue 2, Pages 541-552Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TMECH.2014.2301459
Keywords
Cooperative control; miniature air vehicles; path planning; target tracking
Categories
Funding
- OSD
- Air Force Research Laboratory [FA8650-08-C-1411]
- Brigham Young University
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As the need for autonomous reconnaissance and surveillance missions in cluttered urban environments has been increasing, this paper describes a cooperative path planning algorithm for tracking a moving target in urban environments using both unmanned air vehicles (UAVs) and unmanned ground vehicles (UGVs). The novelty of the algorithm is that it takes into account vision occlusions due to obstacles in the environment. The algorithm uses a dynamic occupancy grid to model the target state, which is updated by sensor measurements using a Bayesian filter. Based on the current and predicted target behavior, the path planning algorithm for a single vehicle (UAV/UGV) is first designed to maximize the sum of the probability of detection over a finite look-ahead horizon. The algorithm is then extended to multiple vehicle collaboration scenarios, where a decentralized planning algorithm relying on an auction scheme is designed to plan finite look-ahead paths that maximize the sum of the joint probability of detection over all vehicles.
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