Mechanically Cost-Effective Approach For Bipedal Walking In Robots Using Instantaneous Collision Angle

Humans, as bipedal locomotors, are effective at reducing the mechanical cost of transport (CoTmech) by adopting movement strategies and gaits that minimize energy expenditure for a given distance. By using different gaits at different speeds, leveraging their long spring-like tendons and muscle elasticity which store and release energy during movement, humans reduce the mechanical effort required for locomotion. Current locomotion solutions offered in bipedal robots, based on legacy walking and running gait models, are not great at energy efficiency unless walking at very low speeds. Additionally, the control system of robots, designed to ensure stability and adaptability, requires substantial resources, further increasing the overall energy consumption compared to biological bipedal locomotion. Thus, there is a need to minimize the mechanical cost of transport in robots and powered prosthetics, especially to conserve battery power. In this research thesis, I propose a novel bipedal gait algorithm for robots and active prosthetic devices, inspired by the human walking gait, that minimizes the mechanical cost of transport at every instance of the step by leveraging the constraint of orthogonality. By applying the theory of collision mechanics at different stages of walking, the proposed algorithm attempts to minimize instantaneous and overall work required for walking by maintaining the orthogonality between the center of mass ground reaction forces and velocity. This proposed algorithm partitions the walking stride into multiple stages, each focused on minimizing the instantaneous collision angle while maintaining the desired speed. The algorithm achieves a mechanical cost of transport comparable to that of a human. Furthermore, we have designed a real-time control system called the Dynamic Control Platform to measure the forces and employ these walking algorithms for practical applications. This is a bipedal walking test platform that uses feedback from a force sensing trackway to control the robot. I demonstrate the effectiveness of the proposed algorithm by simulating its operation over various speeds and comparing the resulting cost of transport to that of humans. This algorithm serves as a practical baseline to design future mechanically cost-effective humanoid bipedal robots and powered prosthetics.