Energy-aware terrain analysis for mobile robot exploration

Abstract

This paper presents an approach to predict energy consumption in mobility systems for wheeled ground robots. The energy autonomy is a critical problem for various battery-powered systems. Specifically, the consumption prediction in mobility systems, which is difficult to obtain due to its complex interactivity, can be used to improve energy efficiency. To address this problem, a self-supervised approach is presented which considers terrain geometry and soil types. Especially, this paper analyzes soil types which affect energy usage models, then proposes a prediction scheme based on terrain type recognition and simple consumption modeling. The developed vibration-based terrain classifier is validated with a field test in diverse volcanic terrain.