Learning & Understanding Human-Centered Robotic Manipulation Strategies
Forskningsprojekt, 2020
– 2025
Human-robot collaboration is one of the most promising applications of autonomous robots. For this, robots need to interact with humans in a meaningful, flexible and adaptable manner, especially when new situations are faced. Currently, the new emerging technologies such as virtual reality and wearable devices allow capturing natural human movements of multiple users. Then, the next generation of learning methods should take advantage of and bootstrap the learning of new activities by adapting to the massive processing of information obtained from these enhanced sensors.
The goal of this PhD project is to develop semantic-based learning algorithms able to cope with a large amount of data generated from multi-modal/multi-level sensors and react to dynamically changing environments in real-time to produce robots with enhanced autonomy levels and manipulation capabilities. The massive collection of data will also contain information about the different styles of human demonstrations which will help in developing a more human-centred control solution.
Deltagare
Karinne Ramirez-Amaro (kontakt)
Chalmers, Elektroteknik, System- och reglerteknik
Maximilian Diehl
Chalmers, Elektroteknik, System- och reglerteknik
Yiannis Karayiannidis
Chalmers, Elektroteknik, System- och reglerteknik
Jonas Sjöberg
Chalmers, Elektroteknik, System- och reglerteknik
Samarbetspartners
Chalmers AI Research Centre
Gothenburg, Sweden
Finansiering
Chalmers AI-forskningscentrum (CHAIR)
Finansierar Chalmers deltagande under 2020–2025
Relaterade styrkeområden och infrastruktur
Informations- och kommunikationsteknik
Styrkeområden