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Aaron Johnson

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Tail Assisted Dynamic Self Righting

Proceedings of the International Conference on Climbing and Walking Robots, July, 2012

Part of the Throwing Your Weight Around: Using Appendage Inertia special session, and a Best Student Paper Finalist

Aaron M. Johnson*, Thomas Libby†, Evan Chang-Siu†, Masayoshi Tomizuka†, Robert J. Full†, and D. E. Koditschek*
*: University of Pennsylvania
†: University of California Berkeley
Full PDF | Penn Scholarly Commons

      In this paper we explore the design space of tails intended for self-righting a robotís body during free fall. Conservation of total angular momentum imposes a dimensionless index of rotational efficacy upon the robotís kinematic and dynamical parameters whose selection insures that for a given tail rotation, the body rotation will be identical at any size scale. In contrast, the duration of such a body reorientation depends upon the acceleration of the tail relative to the body, and power density of the tailís actuator must increase with size in order to achieve the same maneuver in the same relative time. Assuming a simple controller and power-limited actuator, we consider maneuverability constraints upon two different types of parameters ó morphological and energetic ó that can be used for design. We show how these constraints inform contrasting tail design on two robots separated by a four-fold length scale, the 177g Tailbot and the 8.1kg X-RHex Lite (XRL). We compare previously published empirical self-righting behavior of the Tailbot with new, tailed XRL experiments wherein we drop it nose first from a 2.7 body length height and also deliberately run it off an elevated cliff to land safely on its springy legs in both cases.
This was supported primarily by the ARL/GDRS RCTA and the NSF CiBER-IGERT under Award DGE-0903711.
BibTeX entry
  Author = {Aaron M. Johnson and Thomas Libby and Evan Chang-Siu 
and Masayoshi Tomizuka and Robert J. Full and D. E. Koditschek},
  booktitle={Proceedings of the Fifteenth International Conference on Climbing and Walking Robots},
  title = {Tail Assisted Dynamic Self Righting},
  month = {July},
  year = {2012},
  pages = {611--620}

Tail Assisted Dynamic Self Righting: Full Derivation

A technical report containing the full derivations. Penn ScholarlyCommons | Full PDF

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