This research project aims to explore and enhance the control systems of quasi-passive dynamic bipedal walkers at different scales, focusing on improving their robustness and agility in varied terrains. At small scales, motor scaling laws and mechanical design constraints necessitate fewer actuators, which limits both torque output and controllability. Each actuator must consequently be precisely controlled by adaptable algorithms.

We present a Proportional-Integral-Derivative (PID) control strategy for Mugatu, a single degree of freedom (DOF) hip-actuated bipedal robot, designed to achieve straight-line walking while maintaining stability and maximizing velocity. In our robot, the single DOF is an actuated joint at the hip, the only control input into the system. Our approach integrates proprioceptive joint feedback with an Inertial Measurement Unit (IMU) to measure body state and the robot's spatial awareness. The sensory integration enables real-time monitoring of the robot's orientation and acceleration, allowing adjustment during various phases of the gait cycle.

The research aims to provide a comprehensive analysis of underactuated biped dynamics, examining how physical parameters such as mass distribution and spherical foot profile influence the system's behavior. This work explores gait optimization strategies maximizing walking stability and speed of quasi-passive dynamic walkers across different terrain types, including slippery surfaces and inclines. These findings have implications for applications requiring efficient bipedal locomotion in confined or intricate spaces, such as industrial inspection, and disaster recovery tasks. The developed control framework provides a foundation for designing more capable small-scale walking robots that can operate effectively in real-world environments while maintaining simplicity in mechanical design.