Probabilistic pursuit-evasion games: theory, implementation, and experimental evaluation
Vidal, R.
Shakernia, O.
Kim, H.J.
Shim, D.H.
Sastry, S.
Dept. of Electr. Eng. & Comput. Sci., California Univ., Berkeley, CA;
This paper appears in: Robotics and Automation, IEEE Transactions on
Publication Date: Oct 2002
Volume: 18,
Issue: 5
On page(s): 662- 669
ISSN: 1042-296X
INSPEC Accession Number: 7472236
Digital Object Identifier: 10.1109/TRA.2002.804040
Current Version Published: 2002-12-10
Abstract
We consider the problem of having a team of unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs) pursue a second team of evaders while concurrently building a map in an unknown environment. We cast the problem in a probabilistic game theoretical framework, and consider two computationally feasible greedy pursuit policies: local-mar and global-max. To implement this scenario on real UAVs and UGVs, we propose a distributed hierarchical hybrid system architecture which emphasizes the autonomy of each agent, yet allows for coordinated team efforts. We describe the implementation of the architecture on a fleet of UAVs and UGVs, detailing components such as high-level pursuit policy computation, map building and interagent communication, and low-level navigation, sensing, and control. We present both simulation and experimental results of real pursuit-evasion games involving our fleet of UAVs and UGVs, and evaluate the pursuit policies relating expected capture times to the speed and intelligence of the evaders and the sensing capabilities of the pursuers.
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