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Offer Description PHD MSCA COFUND BEST The proposed PhD project is entitled: “Autonomous Collision Avoidance Guidance for Low-Thrust Spacecraft: A Combined Pontryagin Principle and Learning-Based
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and machine-learning algorithms for conflict detection, collision avoidance, flight-path planning, and rerouting under uncertain and dynamic maritime traffic conditions. Develop perception- and
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frameworks such as PyTorch or TensorFlow. Experience in autonomous navigation, path planning, trajectory optimisation, conflict detection, or collision avoidance. Experience in model predictive control
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; - Integrate collision detection and avoidance mechanisms between the robot, products and boxes, ensuring product integrity during picking and packing; - Test, validate and tune the developed solutions in a
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combines lidar, radar, RGB cameras and thermal cameras and adapts when one or more sensors degrade, for field robots in GPS-denied environments - Control and collision avoidance for quadrotor drones
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encompass a much broader range of phenomena, including aerodynamic coupling between drones, perception and collision avoidance, communication effects arising from information sharing, and mechanical