Chair: Jessy Grizzle

ABSTRACT:
Legged robots are accessible to unstructured environments, which enables legged robots to aid in package delivery, terrain exploration, search and rescue, and disaster relief, and becoming assistants in our homes. Two-legged robots (i.e., bipedal robots) with tall and slim shapes can easily adapt to structures built for humans (narrow staircases or passages). Besides assisting the elderly or people with physical disabilities, research on bipedal robots and exoskeletons habilitates humans to improve productivity.

The capabilities of bipedal robots have yet to be unleashed to serve the society due to a number of challenges. One key challenge involves problems in sensor fusion, pose estimation, and smooth motion planning, as these aspects are critical for a bipedal robot to autonomously walk toward a distant destination and to smoothly avoid obstacles detected from different calibrated sensors while maintaining its stability.

In this defense, I am going to introduce a full autonomy system that allows bipedal robots to 1) acquire multi-modal data from a calibrated perception suite; 2) estimate their poses in textureless environments; 3) detect and avoid dynamic obstacles; 4) traverse unexplored, unstructured environments and undulating terrains; 5) perform point-to-point topometric navigation. All the research presented in this dissertation focuses on advancing the state-of-the-art algorithms that will achieve autonomy of bipedal robots — Cassie Blue and Digit.