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On challenging, uneven terrain a legged robot’s open loop posture will almost inevitably be inefficient, due to uncoordinated support of gravitational loads with coupled internal torques. By reasoning about certain structural properties governing the infinitesimal kinematics of the closed chains arising from a typical stance, we have developed a computationally trivial self-manipulation behavior that can minimize both internal and external torques absent any terrain information. The key to this behavior is a change of basis in torque space that approximates the partially decoupled nature of the two types of disturbances. The new coordinates reveal how to use actuator current measurements as proprioceptive sensors for the approximate gradients of both the internal and external task potential fields, without recourse to further modeling. The behavior is derived using a manipulation framework informed by the dual relationship between a legged robot and a multifingered hand. We implement the reactive posture controller resulting from simple online descent along these proprioceptively sensed gradients on the X-RHex robot to document the significant savings in standing power.

For more information: Kod*Lab

Document Type

Conference Paper

Subject Area

GRASP, Kodlab

Date of this Version



BibTeX entry

@inproceedings{paper:johnson-iros-2012, author = {Aaron M. Johnson and G Clark Haynes and D E Koditschek}, title = {Standing Self-Manipulation for a Legged Robot}, booktitle = {Proceedings of the IEEE/RSJ Intl. Conference on Intelligent Robots and Systems}, month = {October}, year = {2012}, address = {Algarve, Portugal}, pages = {272--279} }

This work was supported primarily by the DARPA Maximum Mobility and Manipulation Seedling project, with continued support by the ARL/GDRS RCTA project under Cooperative Agreement Number W911NF- 0–2−0016. The second author was funded by an Intelligence Community Postdoctoral Research Fellowship HM1582–08–1−0034.

Copyright YEAR 2012. Reprinted from Proceedings of the 2012 IEEE/RSJ Intl. Conference on Intelligent Robots and Systems, pages 272-279.

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Date Posted: 05 November 2013

This document has been peer reviewed.