NCCR Robotics is a consortium of robotics laboratories across Switzerland, working on robots for improving the quality of life and to strengthen robotics in Switzerland and worldwide. Newsletter
NCCR Robotics publishes open source software and datasets, please see below for a list and links to where they can be downloaded. Robogen RoboGen™ is an open source platform… Read more
NCCR Robotics supports and promotes seminars and talks by invited speakers in the partner institutions. addd Diego Pardos talk from Feb 2017 RI Seminar: Davide Scaramuzza : Micro… Read more
Looking for publications? You might want to consider searching on the EPFL Infoscience site which provides advanced publication search capabilities.
Predicting the grasping function during reach-to-grasp motions is essential for controlling a prosthetic hand or a robotic assistive device. An early accurate prediction increases the usability and the comfort of a prosthetic device. This work proposes an electromyographic-based learning approach that decodes the grasping intention at an early stage of reach-to-grasp motion, i.e. before the final grasp/hand pre-shape takes place. Superficial electrodes and a Cyberglove were used to record the arm muscle activity and the finger joints during reach-to-grasp motions. Our results showed a 90% accuracy for the detection of the final grasp about 0.5 s after motion onset. This paper also examines the effect of different objects’ distances and different motion speeds on the detection time and accuracy of the classifier. The use of our learning approach to control a 16-degrees of freedom robotic hand confirmed the usability of our approach for the real-time control of robotic devices.