Our main goal is to develop intelligent yet human-in-command robots that can collaborate with humans and assists them in their daily activities. We have a multidisciplinary approach, spanning theoretical, technical, and practical dimensions of modern collaborative systems. From the one hand, the HRI² research focuses on the development of advanced control frameworks for mobile and fixed-base collaborative robots and wearable assistive devices to boost their interaction autonomy. From the other hand, we develop cutting edge techniques and kinodynamic models to anticipate human socio-physical states. The development of intelligent interfaces with multimodal sensory processing capabilities is also central to the HRI² lab's strategic vision, with the aim to create timely and comforting (ergonomic) robot actions in response to human intentions and environmental variations.
Human-Robot Interfaces and Interaction (HRI²)
- Openings
- Post Doc on machine learning for human monitoring and activity recognition
- Technician Positions on Vision-based Human Intention Estimation and Activity Recognition using Machine Learning
- Two Fellow researcher positions on: Learning by demonstration and foundation models for robot programming and control in in dynamic and unpredictable environments
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