Chen, Yuxiao and Singletary, Andrew and Ames, Aaron D. (2020) Lidar-based exploration and discretization for mobile robot planning. . (Unpublished) https://resolver.caltech.edu/CaltechAUTHORS:20210120-165238517
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Abstract
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) | ||||||||
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Record Number: | CaltechAUTHORS:20210120-165238517 | ||||||||
Persistent URL: | https://resolver.caltech.edu/CaltechAUTHORS:20210120-165238517 | ||||||||
Usage Policy: | No commercial reproduction, distribution, display or performance rights in this work are provided. | ||||||||
ID Code: | 107612 | ||||||||
Collection: | CaltechAUTHORS | ||||||||
Deposited By: | George Porter | ||||||||
Deposited On: | 21 Jan 2021 16:14 | ||||||||
Last Modified: | 21 Jan 2021 16:14 |
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