Generating informative paths for persistent sensing in unknown environments
Author(s)Soltero, Daniel E.; Schwager, Mac; Rus, Daniela L.
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We present an online algorithm for a robot to shape its path to a locally optimal configuration for collecting information in an unknown dynamic environment. As the robot travels along its path, it identifies both where the environment is changing, and how fast it is changing. The algorithm then morphs the robot's path online to concentrate on the dynamic areas in the environment in proportion to their rate of change. A Lyapunov-like stability proof is used to show that, under our proposed path shaping algorithm, the path converges to a locally optimal configuration according to a Voronoi-based coverage criterion. The path shaping algorithm is then combined with a previously introduced speed controller to produce guaranteed persistent monitoring trajectories for a robot in an unknown dynamic environment. Simulation and experimental results with a quadrotor robot support the proposed approach.
DepartmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science; Massachusetts Institute of Technology. School of Engineering
Proceedings of the 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems
Institute of Electrical and Electronics Engineers (IEEE)
Soltero, Daniel E., Mac Schwager, and Daniela Rus. “Generating Informative Paths for Persistent Sensing in Unknown Environments.” 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems (October 2012).
Author's final manuscript