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Lidar-based exploration and discretization for mobile robot planning

Chen, Yuxiao and Singletary, Andrew and Ames, Aaron D. (2020) Lidar-based exploration and discretization for mobile robot planning. . (Unpublished)

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In robotic applications, the control, and actuation deal with a continuous description of the system and environment, while high-level planning usually works with a discrete description. This paper considers the problem of bridging the low-level control and high-level planning for robotic systems via sensor data. In particular, we propose a discretization algorithm that identifies free polytopes via lidar point cloud data. A transition graph is then constructed where each node corresponds to a free polytope and two nodes are connected with an edge if the two corresponding free polytopes intersect. Furthermore, a distance measure is associated with each edge, which allows for the assessment of quality (or cost) of the transition for high-level planning. For the low-level control, the free polytopes act as a convenient encoding of the environment and allow for the planning of collision-free trajectories that realizes the high-level plan. The results are demonstrated in high-fidelity ROS simulations and experiments with a drone and a Segway.

Item Type:Report or Paper (Discussion Paper)
Related URLs:
URLURL TypeDescription Paper
Chen, Yuxiao0000-0001-5276-7156
Singletary, Andrew0000-0001-6635-4256
Ames, Aaron D.0000-0003-0848-3177
Record Number:CaltechAUTHORS:20210120-165238517
Persistent URL:
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:107612
Deposited By: George Porter
Deposited On:21 Jan 2021 16:14
Last Modified:21 Jan 2021 16:14

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