Title: Optimizing robotic jumping on granular media

Author (Talk): Christian Hubicki, Georgia Institute of Technology


Substrate dynamics can have a significant impact on terrestrial locomotion behaviors; for example, movement strategies that perform well on hard ground can lead to failure on yielding substrates like granular media. We performed a robophysical experiment to investigate how granular media dynamics can be manipulated to modify performance in a simple behavior, jumping. Using recent models of granular bulk reaction forces during rapid intrusions [Aguilar & Goldman, Nature Physics, 2015] and a numerical optimal control algorithm, we control a jumping robot to leap from a bed of loose packed poppy seeds to a commanded apex using minimal motor work. The optimal control algorithm was able to exploit the terrain dynamics to jump to commanded heights; the patterns of robot self-deformation differed from those which produced similar heights on hard ground. For a subset of optimized behaviors, jumps overshot the commanded/predicted apex height by ~40%. In particular, this excessive jump height occurred when the intruding foot briefly (~40 ms) halted its penetration before resuming its downward thrust. As a result, we hypothesized the presence of additional un-modeled terrain dynamics which activate when the intruder pauses. Ongoing intrusion experiments with an instrumented robotic arm identify that short-duration pauses in motion (~100ms) result in increased resistive forces upon resumed intrusion. These experiments aim to identify further transient substrate physics which may be exploitable for the purpose of robotic locomotion.

Valid HTML 4.01!

Copyright © All Rights Reserved.

Valid CSS!