Minimal Representation for the Control of the Adept Quattro with Rigid Platform via Leg Observation Considering a Hidden Robot Model - Archive ouverte HAL
Communication Dans Un Congrès Année : 2013

Minimal Representation for the Control of the Adept Quattro with Rigid Platform via Leg Observation Considering a Hidden Robot Model

Résumé

Previous works on the Gough-Stewart (GS) platform have shown that its visual servoing using the observation of its leg directions was possible by observing only three of its six legs but that the convergence to the desired pose was not guarantied. This can be explained by considering that the visual servoing of the leg direction of the GS platform was equivalent to controlling another robot, the 3-UPS that has assembly modes and singular configurations different from those of the GS platform. Considering this hidden robot model allowed the simplification of the singularity analysis of the mapping between the leg direction space and the Cartesian space. In this paper, the work on the definition of the hidden robot models involved in the visual servoing using the observation of the robot leg directions is extended to another robot, the Adept Quattro. It will be shown that the hidden robot model is completely different from the model involved in the control of the GS platform. Therefore, the results obtained for the GS platform are not valuable for this robot. The hidden robot has assembly modes and singular configurations different from those of the Quattro. An accuracy analysis is performed to show the importance of the leg selection. All these results are validated on a Quattro simulator created using ADAMS/Controls and interfaced with Matlab/Simulink.
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Dates et versions

hal-00839839 , version 1 (25-06-2019)

Identifiants

  • HAL Id : hal-00839839 , version 1

Citer

Victor Rosenzveig, Sébastien Briot, Philippe Martinet. Minimal Representation for the Control of the Adept Quattro with Rigid Platform via Leg Observation Considering a Hidden Robot Model. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2013), Nov 2013, Tokyo Big Sight, Japan. ⟨hal-00839839⟩
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