We study a fundamental motion planning problem of navigating a ground robot to a goal position with minimum energy consumption. Most existing solutions for this problem require an energy consumption model as a function of the environment and the robot motion. Obtaining such models is difficult which prevents the practical applicability of path planning algorithms for energy optimization. To address this issue, we present a new approach based on the assumption that the energy consumption for the ground robot is correlated with ground appearance. The first main contribution of this paper is the validation of the ground appearance assumption by experiments using actual energy consumption data obtained by ground robots. We then show how aerial images collected by an unmanned aerial vehicle can be used to generate the energy cost map of a given environment, which can further be used for planning energy-efficient paths for ground robots.
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Air To Ground Collaboration For Energy-efficient Path Planning For Ground Robots
Semantic Scholar · Engineering · 2019
Abstract
We study a fundamental motion planning problem of navigating a ground robot to a goal position with minimum energy consumption. Most existing solutions for this problem require an energy consumption model as a function of the environment and the robot motion. Obtaining such models is difficult which prevents the practical applicability of path planning algorithms for energy optimization. To address this issue, we present a new approach based on the assumption that the energy consumption for the ground robot is correlated with ground appearance. The first main contribution of this paper is the validation of the ground appearance assumption by experiments using actual energy consumption data obtained by ground robots. We then show how aerial images collected by an unmanned aerial vehicle can be used to generate the energy cost map of a given environment, which can further be used for planning energy-efficient paths for ground robots.