SUMMARY

This dissertation presents two main contributions. Firstly, a formal framework for achieving multi-contact bipedal robotic walking is proposed, and realized experimentally on the robotic platforms: AMBER2. Inspired by the key feature encoded in human walking---multi-contact behavior---this approach begins with the analysis of human locomotion and uses it to motivate the construction of a hybrid system model representing a multi-contact robotic walking gait. Human-inspired outputs extracted from reference locomotion are employed to develop the human-inspired control and an optimization problem that yields stable multi-domain walking. Through a trajectory reconstruction strategy, the mathematical constructions are successfully translated to the physical robot experimentally.

Secondly, the proposed systematic methodology is extended from bipedal locomotion to achieve human-like multi-contact prosthetic walking on a custom-built prosthesis AMPRO. To achieve this goal, unimpaired human locomotion data is collected via Inertial measurement Units (IMUs). The human-inspired optimization problem that utilizes the collected reference human gait as reference is utilized to design stable multi-contact prosthetic gaits that can be implemented on the prostheses directly. Leveraging control Lyapunov function based quadratic programs synthesized with variable impedance control, an online optimization-based controller is formulated to realize the designed gait in both simulation and experimentally on AMPRO. Improved tracking and energy efficiency are seen when this methodology is implemented experimentally. Importantly, the resulted multi-contact prosthetic walking captures the essentials of natural human walking both kinematically and kinetically.