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Autonomous Robots

, Volume 43, Issue 5, pp 1187–1205 | Cite as

Kinematic optimization for bipedal robots: a framework for real-time collision avoidance

  • Arne-Christoph HildebrandtEmail author
  • Simon Schwerd
  • Robert Wittmann
  • Daniel Wahrmann
  • Felix Sygulla
  • Philipp Seiwald
  • Daniel Rixen
  • Thomas Buschmann
Article
  • 214 Downloads

Abstract

Bipedal locomotion is more than dynamically stable walking. The redundant kinematic design of humanoid robots allows for complex motions in complex scenarios. One challenge of current robotic research is the exploitation of the capacities of redundant robots in real-time applications. In this paper, we present and evaluate methods for real-time motion generation of redundant robots. The proposed methods are based on a model-predictive approach. We propose and compare methods for optimization of robot motions defined by parameterized task-space trajectories and for redundancy resolution. The approaches are successfully combined in a novel algorithm. The methods are introduced with the help of a minimal model. It shows their applicability for a wide range of complex robotic systems. We apply and validate their effectiveness and their real-time character in several experiments with different environments with the humanoid robot Lola.

Keywords

Bipedal walking Autonomous navigation Kinematic optimization Real-time motion generation Collision avoidance 

Notes

Acknowledgements

We would like to acknowledge the DAAD and the Deutsche Forschungsgemeinschaft (DFG—Project BU 2736/1-1) for their support of this project.

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Technical University of MunichGarchingGermany

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