Legged robots offer the potential of locomotion across various types of terrains. Different terrains require different gait patterns to enable greater traversal efficiency. Consequently, as a legged robot transitions from one type of terrain to another, the gait pattern should be adapted so as to maximise traction and energy efficiency. This paper explores the use of power consumption as estimated by the robot in real-time for guiding this gait transition in the case of statically-stable locomotion. While moving, the robot autonomously assesses its power consumption, relates it to the traction, and switches between gaits so as to maximise efficiency. In this way, the robot only needs proprioceptive sensors and consequently does not require velocity estimation, ground imaging or profiling to maintain efficient locomotion across different terrains. The approach has been tested on a hexapod robot traversing a variety of terrain types and stiffness, including concrete, grass, mulch and leaf litter. The experimental results show that gait switching on energetics alone enables traction maintenance and efficient locomotion across different terrains. We also present comparisons between the power consumption metric used in this work and cost of transport which is used in the literature for characterising energetics for legged locomotion.
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