Conference
Whole-body Model-Predictive Control applied to the HRP-2 Humanoid
| العنوان: | Whole-body Model-Predictive Control applied to the HRP-2 Humanoid |
|---|---|
| المؤلفون: | Koenemann, J, del Prete, Andrea, Tassa, Yuval, Todorov, E, Stasse, Olivier, Bennewitz, M, Mansard, Nicolas |
| المساهمون: | University of Freiburg Freiburg, Équipe Mouvement des Systèmes Anthropomorphes (LAAS-GEPETTO), 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), Google UK, Google Inc., University of Washington Seattle, ANR-13-CORD-0002,ENTRACTE,Comprendre et plannifier l'action anthropomorphe(2013), European Project: 608849,EC:FP7:ICT,FP7-2013-NMP-ICT-FOF,EUROC(2014), European Project |
| المصدر: | IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2015) ; https://hal.science/hal-01137021 ; IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2015), Sep 2015, Hamburg, Germany. 8p |
| بيانات النشر: | HAL CCSD |
| سنة النشر: | 2015 |
| المجموعة: | Université Toulouse III - Paul Sabatier: HAL-UPS |
| مصطلحات موضوعية: | [INFO.INFO-RB]Computer Science [cs]/Robotics [cs.RO] |
| جغرافية الموضوع: | Hamburg, Germany |
| الوصف: | International audience ; Controlling the robot with a permanently-updated optimal trajectory, also known as model predictive control, is the Holy Grail of whole-body motion generation. Before obtaining it, several challenges should be faced: computation cost, non-linear local minima, algorithm stability, etc. In this paper, we address the problem of applying the updated optimal control in real-time on the physical robot. In particular, we focus on the problems raised by the delays due to computation and by the differences between the real robot and the simulated model. Based on the optimal-control solver MuJoCo, we implemented a complete model-predictive controller and we applied it in real-time on the physical HRP-2 robot. It is the first time that such a whole-body model predictive controller is applied in real-time on a complex dynamic robot. Aside from the technical contributions cited above, the main contribution of this paper is to report the experimental results of this premìère implementation. |
| نوع الوثيقة: | conference object |
| اللغة: | English |
| Relation: | info:eu-repo/grantAgreement/EC/FP7/608849/EU/European Robotics Challenges/EUROC; hal-01137021; https://hal.science/hal-01137021; https://hal.science/hal-01137021/document; https://hal.science/hal-01137021/file/MuJoCo%20on%20HRP2.pdf |
| الاتاحة: | https://hal.science/hal-01137021 https://hal.science/hal-01137021/document https://hal.science/hal-01137021/file/MuJoCo%20on%20HRP2.pdf |
| Rights: | info:eu-repo/semantics/OpenAccess |
| رقم الانضمام: | edsbas.AEF6D651 |
| قاعدة البيانات: | BASE |
| الوصف غير متاح. |