Event Location: NSH 3305

Abstract: We present work to transfer decentralized neuromuscular control strategies of human locomotion to powered segmented robotic legs. State-of-the-art robotic locomotion control approaches, like centralized planning and tracking in fully robotic systems and predefined motion pattern replay in prosthetic systems, do not enable the dynamism and reactiveness of able-bodied humans. Animals largely realize dexterous segmented leg performance with leg-encoded biomechanics and local feedback controls that bypass central processing. A de- centralized neuromuscular controller was recently developed that enables robust locomotion for a simulated multi-segmented planar humanoid. A portion of this controller was used in an active ankle-foot prosthesis to modulate ankle torque during stance, enabling level and inclined ground walking. While these results suggest that the neuromuscular controller is a promising alternative control method for both fully robotic systems and powered prostheses, it is unclear if the controller can be transferred to multi-segmented robotic legs. The goal of this thesis is to investigate the feasibility of controlling a multi-segmented robotic leg with the proposed neuromuscular control approach, which may enable robots and powered prostheses to react to locomotion disturbances dynamically and in a human-like way.

To transfer neuromuscular controls to powered segmented robotic legs, we use a model-based design approach. The initial transfer is focused on neuromuscular swing-leg controls, important for maintaining dynamic stability of both fully robotic systems and powered pros- theses in the presence of unexpected locomotion disturbances, such as trips and pushes. We first present the design of RNL, a three segment, cable-driven, antagonistically actuated robotic leg with joint compliance. The robot’s size, weight, and actuation capabilities correspond to dynamically scaled human values. Next, a high-fidelity simulation of the robot is created to investigate the feasibility of transferring neuromuscular controls, pre-tune hardware gains via optimization, and serve as a benchmark for hardware experiments. An idealized version of the swing-leg controller with mono-articular actuation, as well as the neuromuscular interpretation of this controller with multi-articular actuation is then transferred to RNL and evaluated with foot placement experiments. The results suggest that the swing-leg controller can accurately regulate foot placement of robotic legs during undisturbed and disturbed motions. Compared to impedance control, these decentralized swing-leg controls achieve this foot placement with a single set of gains, which make these control methods an attractive candidate for regulating the motion of legged robots in the real-world.

In parallel to this control transfer, a synthesis method for creating compact nonlinear springs with user-defined torque-deflection profiles is presented to explore methods for improving RNL’s series elastic actuators. The springs use rubber as their elastic element, which, while enabling a compact spring design, introduce viscoelastic behavior in the spring that needs to be accounted for with additional control. To accurately estimate force developed in the rubber, an empirically characterized constitutive rubber model is developed and integrated into the series elastic actuator controller used by the RNL test platforms. Bench-top experiments show that in conjunction with an observer, the nonlinear spring prototype achieves desired behavior at actuation frequencies up to 2Hz, after which spring behavior degrades due to rubber hysteresis. These results show that while the presented methodology is capable of realizing compact nonlinear springs, careful rubber selection that mitigates viscoelastic behavior is necessary during the spring design process.

Committee:Hartmut Geyer, Chair

Ralph Hollis

Steve Collins

Herman van der Kooij, University of Twente, Netherlands