Efﬁcient Planning under Uncertainty for a Target-Tracking Micro-Aerial Vehicle
Author(s)He, Ruijie; Bachrach, Abraham Galton; Roy, Nicholas
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A helicopter agent has to plan trajectories to track multiple ground targets from the air. The agent has partial information of each target's pose, and must reason about its uncertainty of the targets' poses when planning subsequent actions. We present an online, forward-search algorithm for planning under uncertainty by representing the agent's belief of each target's pose as a multi-modal Gaussian belief. We exploit this parametric belief representation to directly compute the distribution of posterior beliefs after actions are taken. This analytic computation not only enables us to plan in problems with continuous observation spaces, but also allows the agent to search deeper by considering policies composed of multi-step action sequences; deeper searches better enable the agent to keep the targets well-localized. We present experimental results in simulation, as well as demonstrate the algorithm on an actual quadrotor helicopter tracking multiple vehicles on a road network constructed indoors.
DepartmentMassachusetts Institute of Technology. Department of Aeronautics and Astronautics; Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Proceedings of the 2009 IEEE International Conference on Robotics and Automation (ICRA)
Institute of Electrical and Electronics Engineers
Ruijie He, A. Bachrach, and N. Roy. “Efficient planning under uncertainty for a target-tracking micro-aerial vehicle.” Robotics and Automation (ICRA), 2010 IEEE International Conference on. 2010. 1-8.
Author's final manuscript
INSPEC Accession Number: 11430981