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
Our partner institutions current offer two courses that have a strong focus on robotics at Master’s level, although it is worth noting that students with a wide variety of backgrounds… Read more
NCCR Robotics publishes open source software and datasets, please see below for a list and links to where they can be downloaded. Feature Tracking Analysis for Event Cameras Scaramuzza’s… Read more
Looking for publications? You might want to consider searching on the EPFL Infoscience site which provides advanced publication search capabilities.
Modern wearable robots are not yet intelligent enough to fully satisfy the demands of endusers, as they lack the sensor fusion algorithms needed to provide optimal assistance and react quickly to perturbations or changes in user intentions. Sensor fusion applications such as intention detection have been emphasized as a major challenge for both robotic orthoses and prostheses. In order to better examine the strengths and shortcomings of the field, this paper presents a review of existing sensor fusion methods for wearable robots, both stationary ones such as rehabilitation exoskeletons and portable ones such as active prostheses and full-body exoskeletons. Fusion methods are first presented as applied to individual sensing modalities (primarily electromyography, electroencephalography and mechanical sensors), and then four approaches to combining multiple modalities are presented. The strengths and weaknesses of the different methods are compared, and recommendations are made for future sensor fusion research.
Our brain-actuated wheelchair uses shared control to couple the user input with the contextual information about the surroundings in order to perform natural manoeuvres both safely and efficiently. In this study, we investigate the feasibility of using our brain–controlled wheelchair with patients in a rehabilitation clinic. Both user and system performance metrics are analysed. We find that the driving performance of a motor-disabled patient at the clinic is comparable with the performance of four healthy subjects. All five participants were able to complete the driving task successfully.