Robots in the future will not be simple machines only capable of repeating basic actions: they will adapt to unexpected changes and learn all kinds of task. In order to program robots able to learn very complex tasks, we first try to understand how humans manage to accomplish them. Our aim is thus to study watchmaking through its training process, as an excellent example of high dexterity tasks. Furthermore, watchmaking requires fine tuned hand coordination, which is essential in learning collaborative robot manipulation.
Call for Participants!
We are looking for students and experts in watchmaking for non-invasive tests. If you are interested in participating, please check our Participants page to learn more.
Progress in Motor Control Conference, 2019, Amsterdam
Aude Billard gave a keynote on the most recent SAHR results and Kunpeng Yao presented a poster.
IROS Demonstration on October 1st 2019!
We presented the experimental setup that we have developed to measure human bimanual dexterity in watchmaking tasks in the workshop The Intelligence of Touch.
This project is conducted by the Learning Algorithms and Systems Laboratory (LASA) at the EPFL.
The human data collection is undertaken in collaboration with the participants from ETVJ (École Technique de la Vallée de Joux).
This project is supported through an ERC Advanced Grant, project ID: 741945, funded by the European Commission.
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