SOURCE-LINKED INTELLIGENCE

Intuitive interaction for robots among humans

CORDIS · observation · Publication date unknown

ated risks, take appropriate actions and continuously reassess. I will reach this goal by developing an innovative approach across the boundaries of Motion Planning, Multi-Robot Task Assignment and Machine Learning. In INTERACT I propose a holistic view on the interaction of mobile robots and humans, where I will consider multiple spatio-temporal granularities ranging from individual interactions to the interaction of a robot fleet with humans in a city, and from short term (local) to long term (global) effects of the interaction. Robots will use past experience to learn local and global intuition models of their interaction with the environment. These intuition models will be integrated in novel uncertainty-aware optimization methods to compute safe interaction-aware trajectories, task assignments and routes for mobile robots. INTERACT will lay the foundation for intuitive multi-robot interaction, make it possible for teams of mobile robots to safely interact in human-centric environments and enable a new level of automation in factories and cities. Multi-robot systems, Motion p

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recordType

award

status

SIGNED

region

EU

value

1499999

unit

EUR