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Cognitive Processing

, Volume 16, Supplement 1, pp 293–297 | Cite as

Dual filtering in operational and joint spaces for reaching and grasping

  • Léo LopezEmail author
  • Jean-Charles Quinton
  • Youcef Mezouar
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Abstract

To study human movement generation, as well as to develop efficient control algorithms for humanoid or dexterous manipulation robots, overcoming the limits and drawbacks of inverse-kinematics-based methods is needed. Adequate methods must deal with high dimensionality, uncertainty, and must perform in real time (constraints shared by robots and humans). This paper introduces a Bayesian filtering method, hierarchically applied in the operational and joint spaces to break down the complexity of the problem. The method is validated in simulation on a robotic arm in a cluttered environment, with up to 51 degrees of freedom.

Keywords

Bayesian filtering Reaching Operational space  Joint space Grasping 

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Copyright information

© Marta Olivetti Belardinelli and Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  • Léo Lopez
    • 1
    Email author
  • Jean-Charles Quinton
    • 1
    • 2
  • Youcef Mezouar
    • 2
    • 3
  1. 1.Pascal InstituteClermont UniversityClermont-FerrandFrance
  2. 2.Pascal InstituteCNRS (UMR 6602)AubiereFrance
  3. 3.Pascal InstituteIFMAAubiereFrance

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