Dynamic walking on randomly-varying discrete terrain with one-step preview

Abstract

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).