Energy Prediction on Sloping Ground for Quadruped Robots
This addresses energy management challenges for legged robots in outdoor environments, enabling better mission planning, though it appears incremental as it builds on existing quadruped platforms with a new modeling approach.
The paper tackled the problem of predicting energy consumption for quadruped robots on sloping terrain by developing a simple energy model using only standard onboard sensors. Field validation on natural terrain showed near-linear trends of force-equivalent cost with slope angle, consistently higher lateral costs, and additive behavior across trajectory segments.
Energy management is a fundamental challenge for legged robots in outdoor environments. Endurance directly constrains mission success, while efficient resource use reduces ecological impact. This paper investigates how terrain slope and heading orientation influence the energetic cost of quadruped locomotion. We introduce a simple energy model that relies solely on standard onboard sensors, avoids specialized instrumentation, and remains applicable in previously unexplored environments. The model is identified from field runs on a commercial quadruped and expressed as a compact function of slope angle and heading. Field validation on natural terrain shows near-linear trends of force-equivalent cost with slope angle, consistently higher lateral costs, and additive behavior across trajectory segments, supporting path-level energy prediction for planning-oriented evaluation.