Gaussian mixtures-based learning algorithms are suitable strategies for trajectory learning and skill acquisition, in the context of programming by demonstration (PbD). Input streams other than visual information, as used in most applications up to date, reveal themselves as quite useful in trajectory learning experiments where visual sources are not available. In this work we have used force/torque feedback through a haptic device for teaching a teleoperated robot to empty a rigid container. Structure vibrations and container inertia appeared to considerably disrupt the sensing process, so a filtering algorithm had to be devised. Moreover, some input variables seemed much more relevant to the particular task to be learned than others, which lead us to analyze the training data in order to select those relevant features through principal component analysis and a mutual information criterion. Then, a batch version of GMM/GMR [1], [2] was implemented using different training datasets (original, pre-processed data through PCA and MI). Tests where the teacher was instructed to follow a strategy compared to others where he was not lead to useful conclusions that permit devising the new research stages. ; Peer Reviewed ; Postprint (author’s final draft)
Sharpening haptic inputs for teaching a manipulation skill to a robot
2010-01-01
Sonstige
Elektronische Ressource
Englisch
Àrees temàtiques de la UPC::Informàtica::Robòtica , GMM , GMR , Intelligent robots , Robot learning , Robot programming , Robots -- Design and construction , Robots -- Kinematics , intelligent robots robot programming telerobotics robot learning , mutual information , Robots -- Disseny i construcció , Robots -- Sistemes de control , Robots -- Cinemàtica , Classificació INSPEC::Automation::Robots::Robot programming
DDC: | 629 |
Hot skills Sharpening up your skill set with Apache
British Library Online Contents | 2005
Simplify the robot programming through an action-and-skill manipulation framework
BASE | 2021
|Human-Multi-Robot Teleoperation for Cooperative Manipulation Tasks using Wearable Haptic Devices
BASE | 2017
|Demonstrative educational haptic manipulator robot: a teaching aid in Mechatronics
BASE | 2021
|