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Developing an embodied gait on a compliant quadrupedal robot

Jonas Degrave (UGent) , Ken Caluwaerts (UGent) , Joni Dambre (UGent) and Francis wyffels (UGent)
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Abstract
Incorporating the body dynamics of compliant robots into their controller architectures can drastically reduce the complexity of locomotion control. An extreme version of this embodied control principle was demonstrated in highly compliant tensegrity robots, for which stable gait generation was achieved by using only optimized linear feedback from the robot's sensors to its actuators. The morphology of quadrupedal robots has previously been used for sensing and for control of a compliant spine, but never for gait generation. In this paper, we successfully apply embodied control to the compliant, quadrupedal Oncilla robot. As initial experiments indicated that mere linear feedback does not suffice, we explore the minimal requirements for robust gait generation in terms of memory and nonlinear complexity. Our results show that a memory-less feedback controller can generate a stable trot by learning the desired nonlinear relation between the input and the output signals. We believe this method can provide a very useful tool for transferring knowledge from open loop to closed loop control on compliant robots.
Keywords
Extreme Learning Machines, embodiment, Robotics, Neural Network, LOCOMOTION, FRAMEWORK

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Please use this url to cite or link to this publication:

MLA
Degrave, Jonas, et al. “Developing an Embodied Gait on a Compliant Quadrupedal Robot.” IEEE International Conference on Intelligent Robots and Systems, IEEE, 2015, pp. 4486–91.
APA
Degrave, J., Caluwaerts, K., Dambre, J., & wyffels, F. (2015). Developing an embodied gait on a compliant quadrupedal robot. IEEE International Conference on Intelligent Robots and Systems, 4486–4491. IEEE.
Chicago author-date
Degrave, Jonas, Ken Caluwaerts, Joni Dambre, and Francis wyffels. 2015. “Developing an Embodied Gait on a Compliant Quadrupedal Robot.” In IEEE International Conference on Intelligent Robots and Systems, 4486–91. IEEE.
Chicago author-date (all authors)
Degrave, Jonas, Ken Caluwaerts, Joni Dambre, and Francis wyffels. 2015. “Developing an Embodied Gait on a Compliant Quadrupedal Robot.” In IEEE International Conference on Intelligent Robots and Systems, 4486–4491. IEEE.
Vancouver
1.
Degrave J, Caluwaerts K, Dambre J, wyffels F. Developing an embodied gait on a compliant quadrupedal robot. In: IEEE International Conference on Intelligent Robots and Systems. IEEE; 2015. p. 4486–91.
IEEE
[1]
J. Degrave, K. Caluwaerts, J. Dambre, and F. wyffels, “Developing an embodied gait on a compliant quadrupedal robot,” in IEEE International Conference on Intelligent Robots and Systems, Hamburg, Germany, 2015, pp. 4486–4491.
@inproceedings{6968346,
  abstract     = {{Incorporating the body dynamics of compliant robots into their controller architectures can drastically reduce the complexity of locomotion control. An extreme version of this embodied control principle was demonstrated in highly compliant tensegrity robots, for which stable gait generation was achieved by using only optimized linear feedback from the robot's sensors to its actuators. The morphology of quadrupedal robots has previously been used for sensing and for control of a compliant spine, but never for gait generation. In this paper, we successfully apply embodied control to the compliant, quadrupedal Oncilla robot. As initial experiments indicated that mere linear feedback does not suffice, we explore the minimal requirements for robust gait generation in terms of memory and nonlinear complexity. Our results show that a memory-less feedback controller can generate a stable trot by learning the desired nonlinear relation between the input and the output signals. We believe this method can provide a very useful tool for transferring knowledge from open loop to closed loop control on compliant robots.}},
  author       = {{Degrave, Jonas and Caluwaerts, Ken and Dambre, Joni and wyffels, Francis}},
  booktitle    = {{IEEE International Conference on Intelligent Robots and Systems}},
  isbn         = {{978-1-4799-9994-1}},
  issn         = {{2153-0858}},
  keywords     = {{Extreme Learning Machines,embodiment,Robotics,Neural Network,LOCOMOTION,FRAMEWORK}},
  language     = {{eng}},
  location     = {{Hamburg, Germany}},
  pages        = {{4486--4491}},
  publisher    = {{IEEE}},
  title        = {{Developing an embodied gait on a compliant quadrupedal robot}},
  year         = {{2015}},
}

Web of Science
Times cited: