Cooperative estimation in pursuit evasion games with bearing-only measurements
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© 2018, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved. Coordinated teams of unmanned vehicles are increasingly practical from a technology standpoint. However, the sensing limitations of small robotic and flying vehicles present new challenges to familiar problems. This paper explores simple concepts for improved performance under these sensing constraints. The first concept is a decentralized cooperative estimation scheme in which agents share measurements. The second concept is an active relative ranging system between cooperating agents, which helps stabilize the associated relative state estimates. To explore these concepts, a simple pursuit-evasion game is considered where two pursuers have angle-only relative sensing to the single evader. One pursuer takes the role of the role of the “capture” vehicle while the other moves around the workspace and shares measurements with the capture agent. Cooperative estimation is implemented with and without the relative range measurements to explore the effect of these measurements. Realistic guidance laws are developed using proportional navigation for the capture vehicle and a nonlinear Lyapunov-based feedback law for the assisting agent. Numerical simulations are conducted to validate the closed-loop performance of the guidance using cooperative estimation. In numerical examples, the capture agent obtains significantly improved range information about the evader, enabling capture even when the parallax between the capture agent and the evader is low. The use of interagent range measurements is shown to improve estimation accuracy when initial conditions are less favorable to the cooperating team.
author list (cited authors)
Woodbury, T. D., & Hurtado, J. E.