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

Brahayam Pontón, Stefan Schaal, Ludovic Righetti

Research output: Chapter in Book/Report/Conference proceedingChapter


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 developing a SOC algorithm based on risk-sensitive control, that includes the dynamics of an observer in such a way that the control law explicitly depends 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.

Original languageEnglish (US)
Title of host publicationSpringer Proceedings in Advanced Robotics
PublisherSpringer Science and Business Media B.V.
Number of pages16
StatePublished - 2020

Publication series

NameSpringer Proceedings in Advanced Robotics
ISSN (Print)2511-1256
ISSN (Electronic)2511-1264

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Electrical and Electronic Engineering
  • Mechanical Engineering
  • Engineering (miscellaneous)
  • Artificial Intelligence
  • Computer Science Applications
  • Applied Mathematics


Dive into the research topics of 'On the Effects of Measurement Uncertainty in Optimal Control of Contact Interactions'. Together they form a unique fingerprint.

Cite this