Visual Predictive Control Strategy for Mobile Manipulators
| Autor: | Bildstein, H, Durand-Petiteville, A, Cadenat, Viviane |
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| Přispěvatelé: | Équipe Robotique, Action et Perception (LAAS-RAP), Laboratoire d'analyse et d'architecture des systèmes (LAAS), Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Université de Toulouse (UT)-Institut National des Sciences Appliquées (INSA)-Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université de Toulouse (UT)-Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT), Universidade Federal de Pernambuco [Recife] (UFPE) |
| Rok vydání: | 2022 |
| Předmět: | |
| Zdroj: | European Control Conference (ECC 2022) European Control Conference (ECC 2022), Jul 2022, Londres, United Kingdom. ⟨10.23919/ECC55457.2022.9838241⟩ |
| DOI: | 10.23919/ecc55457.2022.9838241 |
| Popis: | International audience; This work aims at designing a visual predictive control (VPC) scheme for a mobile manipulator. It consists in combining image-based visual servoing with model predictive control to benefit from the advantages of both control structures. Two challenges are addressed in this paper: the choice of the visual features and the closed-loop stability. The first ones rely on image moments to improve the end effector positioning precision. The second one is tackled through a terminal constraint coupled with suitable input constraints to reduce the computational burden. Simulation results using ROS and Gazebo validate the proposed approach. |
| Databáze: | OpenAIRE |
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