Collaborative Human-Humanoid Carrying Using Vision and Haptic Sensing
| Autor: | Abderrahmane Kheddar, Pierre Gergondet, Antoine Bussy, Andrea Cherubini, Don Joven Agravante |
|---|---|
| Přispěvatelé: | Interactive Digital Humans (IDH), Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier (LIRMM), Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM), Joint Robotics Laboratory [Japan] (CNRS-AIST JRL), National Institute of Advanced Industrial Science and Technology (AIST)-Centre National de la Recherche Scientifique (CNRS), IEEE, European Project: 288533,EC:FP7:ICT,FP7-ICT-2011-7,ROBOHOW.COG(2012), Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS), Joint Robotics Laboratory (CNRS-AIST JRL ) |
| Jazyk: | angličtina |
| Rok vydání: | 2014 |
| Předmět: |
0209 industrial biotechnology
Computer science business.industry 020208 electrical & electronic engineering Physical Human-Robot Interaction 02 engineering and technology Physical interaction Visual servoing Robot control 020901 industrial engineering & automation Haptic sensing 0202 electrical engineering electronic engineering information engineering Robot [INFO.INFO-RB]Computer Science [cs]/Robotics [cs.RO] Computer vision Artificial intelligence business Humanoid robot Haptic technology |
| Zdroj: | 31st IEEE International Conference on Robotics and Automation ICRA: International Conference on Robotics and Automation ICRA: International Conference on Robotics and Automation, May 2014, Hong Kong, China. pp.607-612, ⟨10.1109/ICRA.2014.6906917⟩ ICRA |
| Popis: | International audience; We propose a framework for combining vision and haptic information in human-robot joint actions. It consists of a hybrid controller that uses both visual servoing and impedance controllers. This can be applied to tasks that cannot be done with vision or haptic information alone. In this framework, the state of the task can be obtained from visual information while haptic information is crucial for safe physical interaction with the human partner. The approach is validated on the task of jointly carrying a flat surface (e.g. a table) and then preventing an object (e.g. a ball) on top from falling off. The results show that this task can be successfully achieved. Furthermore, the framework presented allows for a more collaborative setup, by imparting task knowledge to the robot as opposed to a passive follower. |
| Databáze: | OpenAIRE |
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