Energy-Economical Heuristically Based Control of Compass Gait Walking on Stochastically Varying Terrain

The field of legged robotics has been long anticipated in the popular media to herald a revolution in both civilian and military life. From mechanical fire fighters barreling through burning apartments with minimal regard for self-preservation to nimble explorers bounding up Martian ridges who never complain about the cold, finding applications for bipedal machines requires little imagination. Despite their promised dexterity and overall popular appeal, in the early 21 st century, bipedal robots are seldom sighted outside of university research labs or cutting-edge technology firms. The absence of these legged machines in our daily lives can be attributed to significant technical barriers in performance. The largely untold flaw of Honda’s flagship robotic humanoid, ASIMO, is that its exorbitant energy consumption drains its generously sized battery pack in roughly 30 minutes, nullifying its utility outside of relatively short public demonstrations. Recognizing that this energy limitation is not unique to ASIMO but common among current-generation walking robots, academic researchers have recently pushed to develop highly energy-economical bipeds. The consequence has been a series of prototypes which trade an abundance of actuation and control authority for an underactuated approach dubbed Dynamic Walking. Specifically, Cornell University developed two internationally publicized walking machines; one which boasted energy economy on par with human walking (for short distances) and the Cornell Ranger which set a world record for walking 5.6 miles on a single battery charge. While delivering such significant advances in energy economy, dynamic walking robots have still largely fallen short in applications with high speed requirements or