Curating tunable, compliant legs for specialized tasks

Having a well-rounded fixed leg design for a quadruped inevitably limits performance across diverse tasks, while tunability enables specialization and leads to better performance. This paper introduces a sub-500-gram quadruped robot with a rich leg design space. Made with laminate design and fabrication techniques, its legs have a range of tunable design parameters, including leg length, transmission ratio, and passive parallel and series stiffness. The legs are also straightforward to model, low-cost, and fast to manufacture. We propose methods to span the leg’s feasible design space and construct simulation environments for training a locomotion policy with reinforcement learning to remove the need for manual controller design and tuning. This policy not only works across leg designs but also exploits the unique dynamics of each leg for better locomotion. A curation process is employed to select designs given performance goals, which is more interpretable than optimization and provides insights for design improvements and discoveries of design principles. Thanks to the tight integration of design, fabrication, simulation, and control, our proposed pipeline produces leg designs with performance that aligns with the simulation, while the learned locomotion policy can be used successfully on the real robot. The fast longitudinal running design reaches a maximum speed of 0.7 m/s or 5.4 body lengths per second, and the low cost of transport (COT) design has a COT of 0.3.