StaccaToe: A Single-Leg Robot that Mimics the Human Leg and Toe

We introduce StaccaToe, a human-scale, electric motor-powered single-leg robot designed to rival the agility of human locomotion through two distinctive attributes: an actuated toe and a co-actuation configuration inspired by the human leg. Leveraging the foundational design of HyperLeg's lower leg mechanism, we develop a stand-alone robot by incorporating new link designs, custom-designed power electronics, and a refined control system. Unlike previous jumping robots that rely on either special mechanisms (e.g., springs and clutches) or hydraulic/pneumatic actuators, StaccaToe employs electric motors without energy storage mechanisms. This choice underscores our ultimate goal of developing a practical, high-performance humanoid robot capable of human-like, stable walking as well as explosive dynamic movements. In this paper, we aim to empirically evaluate the balance capability and the exertion of explosive ground reaction forces of our toe and co-actuation mechanisms. Throughout extensive hardware and controller development, StaccaToe showcases its control fidelity by demonstrating a balanced tip-toe stance and dynamic jump. This study is significant for three key reasons: 1) StaccaToe represents the first human-scale, electric motor-driven single-leg robot to execute dynamic maneuvers without relying on specialized mechanisms; 2) our research provides empirical evidence of the benefits of replicating critical human leg attributes in robotic design; and 3) we explain the design process for creating agile legged robots, the details that have been scantily covered in academic literature.

Integration of Riemannian Motion Policy and Whole-Body Control for Dynamic Legged Locomotion

In this paper, we present a novel Riemannian Motion Policy (RMP)flow-based whole-body control framework for improved dynamic legged locomotion. RMPflow is a differential geometry-inspired algorithm for fusing multiple task-space policies (RMPs) into a configuration space policy in a geometrically consistent manner. RMP-based approaches are especially suited for designing simultaneous tracking and collision avoidance behaviors and have been successfully deployed on serial manipulators. However, one caveat of RMPflow is that it is designed with fully actuated systems in mind. In this work, we, for the first time, extend it to the domain of dynamic-legged systems, which have unforgiving under-actuation and limited control input. Thorough push recovery experiments are conducted in simulation to validate the overall framework. We show that expanding the valid stepping region with an RMP-based collision-avoidance swing leg controller improves balance robustness against external disturbances by up to $53\%$ compared to a baseline approach using a restricted stepping region. Furthermore, a point-foot biped robot is purpose-built for experimental studies of dynamic biped locomotion. A preliminary unassisted in-place stepping experiment is conducted to show the viability of the control framework and hardware.