ATTENTION/WARNING - NE PAS DÉPOSER ICI/DO NOT SUBMIT HERE

Ceci est la version de TEST de DIAL.mem. Veuillez ne pas soumettre votre mémoire sur ce site mais bien à l'URL suivante: 'https://thesis.dial.uclouvain.be'.
This is the TEST version of DIAL.mem. Please use the following URL to submit your master thesis: 'https://thesis.dial.uclouvain.be'.
 

Predictive control of grip force and learning of different object dynamics in collision task

Guiot, Laurane
(2016)

Files

Guiot_77111100_2016.pdf
  • Open access
  • Adobe PDF
  • 4.01 MB
Download

Details

Supervisors
Lefèvre, Philippe ; Thonnard, Jean-Louis
Faculty
Ecole polytechnique de Louvain
Degree label
Master [120] : ingénieur civil biomédical
Abstract
The objective of the work is to investigate experimentally the grip force adjustment and learning during bimanual passive collisions using a virtual environment created by the Kinarm End point robot. Different objects dynamics will be used such as soft or stiff objects in order to provide different impact intensities of collisions.