Abstract
This paper proposes an adaptive planning architecture for multivehicle teams subject to an uncertain, spatially varying disturbance force. Motivated by a persistent surveillance task, the planning architecture is designed with three hierarchical levels. The highest level generates interference-free routes for the entire team to monitor areas of interest that have higher uncertainty. The lower level planners compute trajectories that can be tracked accurately along these routes by anticipating the effects of the disturbance force. To this end, the vehicles maintain an online estimate of the disturbance force, which drives adaptation at all planning levels. A set of simulation results validate the proposed method and demonstrate its utility for persistent surveillance.
We gratefully acknowledge the support of ARL Grant W911NF-08-2-0004.
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Desaraju, V.R., Liu, L., Michael, N. (2016). Multi-Vehicle Adaptive Planning with Online Estimated Cost Due to Disturbance Forces. In: Menegatti, E., Michael, N., Berns, K., Yamaguchi, H. (eds) Intelligent Autonomous Systems 13. Advances in Intelligent Systems and Computing, vol 302. Springer, Cham. https://doi.org/10.1007/978-3-319-08338-4_24
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DOI: https://doi.org/10.1007/978-3-319-08338-4_24
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