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On the Effects of Measurement Uncertainty in Optimal Control of Contact Interactions

2016

Conference Paper

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Stochastic Optimal Control (SOC) typically considers noise only in the process model, i.e. unknown disturbances. However, in many robotic applications involving interaction with the environment, such as locomotion and manipulation, uncertainty also comes from lack of precise knowledge of the world, which is not an actual disturbance. We analyze the effects of also considering noise in the measurement model, by devel- oping a SOC algorithm based on risk-sensitive control, that includes the dynamics of an observer in such a way that the control law explicitly de- pends on the current measurement uncertainty. In simulation results on a simple 2D manipulator, we have observed that measurement uncertainty leads to low impedance behaviors, a result in contrast with the effects of process noise that creates stiff behaviors. This suggests that taking into account measurement uncertainty could be a potentially very interesting way to approach problems involving uncertain contact interactions.

Author(s): Ponton, B and Schaal, S. and Righetti, L.
Book Title: The 12th International Workshop on the Algorithmic Foundations of Robotics WAFR
Year: 2016

Department(s): Autonomous Motion, Movement Generation and Control
Bibtex Type: Conference Paper (inproceedings)

Address: Berkeley, USA
URL: https://arxiv.org/abs/1605.04344

BibTex

@inproceedings{ponton_effects_2016,
  title = {On the {Effects} of {Measurement} {Uncertainty} in {Optimal} {Control} of {Contact} {Interactions}},
  author = {Ponton, B and Schaal, S. and Righetti, L.},
  booktitle = {The 12th {International} {Workshop} on the {Algorithmic} {Foundations} of {Robotics} {WAFR}},
  address = {Berkeley, USA},
  year = {2016},
  url = {https://arxiv.org/abs/1605.04344}
}