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In this project, the goal is to develop a new method (using computer vision and machine learning techniques) for robotic navigation in which goals can be specified at a much higher level of
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. These projects will utilize the lab’s Qualisys motion capture system and Crazyflie mini quadcopters. A passion for robotics including hard- and software design for quadcopters and motion capture is desirable
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are central to the development of products and ideas such as wearables, on-body robotics, and exertion systems. The goal is to address key questions around the design of embodied integration and to jump-start
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The multi-agent path finding problem (MAPF) asks us to find a collision-free plan for a team of moving agents. Such problems appear in many application settings (including robotics, logistics
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, from swarm robotics to mesh networks. The prototypical model system for the investigation of self-organised task allocation are social insect colonies, such as bees and ants. They are able to distribute
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of the common first year: Aerospace engineering Chemical engineering Civil engineering Electrical and computer systems engineering Environmental engineering Materials engineering Mechanical engineering Robotics
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systems and swarm robotics. The project builds on well established computational and mathematical modelling techniques to achieve its aims. Departure points will be agent-based simulations, optimisation