Abstract
Field robotics applications typically require platforms to be deployed for extended periods of time, traversing large distances over often uneven terrains. To best leverage these platforms, it is important to know the energy costs of their operation, to maximise range and operating time. This is particularly the case for electrically powered robots, which share a single power source for actuation, sensing, and computation. In this paper we build upon our prior work—derivation of a physics-based power model for an omnidirectional wheeled mobile robot— to develop an energy-aware rough terrain motion planner, which enables efficient missions to be defined and carried out whilst considering the impact of the terrain slope and slippage characteristics on the energy cost of motion. We develop an effective pipeline for the generation of such missions on-the-fly, and compare the performance of the proposed energy-aware approach against a 3D Euclidean distance metric, experimentally verifying the increased energy efficiency of the resulting plans.
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