Energy Efficiency of a Quadruped Robot with Neuro-Inspired Control in Complex Environments

This paper proposes an analysis of the energy efficiency of a small quadruped robotic structure, designed based on the MIT Mini Cheetah, controlled using a central pattern generator based on the FitzHugh-Nagumo neuron. The robot's performance evaluated on structurally complex terrain in a dynamic simulation environment is compared with other robotic structures on wheels and with hybrid architectures. The energy cost involved in carrying out an assigned task involving the need to traverse uneven terrain is calculated as a relevant index to be taken into account. In particular, simple control strategies impacting the leg trajectories are taken into account as the main factors affecting the energy efficiency in different terrain configurations. The adaptation of the leg trajectories is evaluated depending on the terrain characteristics, improving the locomotion performance.