Dynamic Walking on Randomly-Varying Discrete Terrain with One-step Preview

An inspiration for developing a bipedal walking system is the ability to navigate rough terrain with discrete footholds like stepping stones. In this paper, we present a novel methodology to overcome the problem of dynamic walking over stepping stones with significant random changes to step length and step height at each step. Using a 2-step gait optimization, we not only consider the desired location of the next footstep but also the current configuration of the robot, thereby resolving the problem of step transition when we switch between different walking gaits. We then use gait interpolation to generate the desired walking gait in real-time. We demonstrate the method on a planar dynamical walking model of ATRIAS, an underactuated bipedal robot walking over a randomly generated stepping stones with step length and step height changing in the range of [30:80] (cm) and [30:30] (cm) respectively. Experimental validation on the real robot was also successful for the problem of dynamic walking on stepping stones with step lengths varied within [23:78] (cm) and average walking speed of 0.6 (m/s).