Model-based motion optimization for quadruped robots with an actuated articulated torso

Abstract

In recent years, the deployment of ground-based mobile robots has gained more and more interest in various domains. In contrast to other types of mobile robots, legged robots can traverse irregular terrains, climb stairs, and step over obstacles. However, these unique properties intensify the energy demand and require highly advanced perception methods, actuator designs, and motion control algorithms. The most significant challenges in legged robotics lie in robustness, energy efficiency, and agility.

In recent years, the integration of an articulated torso or active spine, inspired by the body motion of high-performance mammals like the cheetah, has shown promising results. Various studies observed higher maximum velocities and lower energy consumption compared to a rigid torso. However, in these studies, the compliant systems were typically controlled using basic control strategies. In recent years, the development of highly dynamic model-based motion optimization strategies has greatly enhanced the overall performance of various legged robots. Therefore, a model-based motion optimization scheme is developed specifically for articulated quadruped robots. This scheme fully exploits the additional degrees of freedom of the torso to enhance the dynamic performance of the legged robot further.