Trotting robots offer insights into animal gait transitions

A four-legged robot trained with machine learning by EPFL researchers has learned to avoid falls by spontaneously switching between walking, trotting, and pronking – a leaping, arch-backed gait used by animals like springbok and gazelles. With the help of a form of machine learning called deep reinforcement learning (DRL), the EPFL robot notably learned to transition from trotting to pronking to navigate a challenging terrain with gaps ranging from 14-30cm. The study, led by the BioRobotics Laboratory in EPFL's School of Engineering, offers new insights into why and how such gait transitions occur in animals. "Previous research has introduced energy efficiency and musculoskeletal injury avoidance as the two main explanations for gait transitions. More recently, biologists have argued that stability on flat terrain could be more important. But animal and robotic experiments have shown that these hypotheses are not always valid, especially on uneven ground," says PhD student Milad Shafiee, first author on a paper published in Nature Communications.