ICRA 2012 Paper Abstract


Paper TuC02.5

Nanayakkara, Thrishantha (King's College, University of London), Byl, Katie (UCSB), Liu, Hongbin (King's College London), Song, Xiaojing (King's College London), Villabona, Tim (Massachusetts Institue of Technology)

Dominant Sources of Variability in Passive Walking

Scheduled for presentation during the Regular Session "Planning and Navigation of Biped Walking" (TuC02), Tuesday, May 15, 2012, 15:30−15:45, Meeting Room 2 (Chief Red Wing)

2012 IEEE International Conference on Robotics and Automation, May 14-18, 2012, RiverCentre, Saint Paul, Minnesota, USA

This information is tentative and subject to change. Compiled on December 13, 2017

Keywords Passive Walking, Contact Modelling, Underactuated Robots


This paper investigates possible sources of variability in the dynamics of legged locomotion, even in its most idealized form. The rimless wheel model is a seemingly deterministic legged dynamic system, popular within the legged locomotion community for understanding basic collision dynamics and energetics during passive phases of walking. Despite the simplicity of this legged model, however, experimental motion capture data recording the passive step-to-step dynamics of a rimless wheel down a constant-slope terrain actually demonstrates significant variability, providing strong evidence that stochasticity is an intrinsic-and thus unavoidable-property of legged locomotion that should be modeled with care when designing reliable walking machines. We present numerical comparisons of several hypotheses as to the dominant source(s) of this variability: 1) the initial distribution of the angular velocity, 2) the uneven profile of the leg lengths and 3) the distribution of the coefficients of friction and restitution across collisions. Our analysis shows that the 3rd hypothesis most accurately predicts the noise characteristics observed in our experimental data while the 1st hypothesis is also valid for certain contexts of terrain friction. These findings suggest that variability due to ground contact dynamics, and not simply due to geometric variations more typically modeled in terrain, is important in determining the stochasticity and resulting stability of walking robots. Althou



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