Project description
Autonomous systems are intelligent agents—such as robots, vehicles, or drones—that can sense their environment, make decisions, and act independently. When multiple such agents work together, cooperative autonomous systems emerge. These systems hold transformative potential in applications like robotics, environmental monitoring, smart transportation, warehouse automation, and disaster response.
Through cooperation and coordination, autonomous agents can accomplish tasks that are too complex, unsafe, or large-scale for a single agent to handle alone. This research area lies in the intersection of control theory, robotics, artificial intelligence, and signal processing, and is a key enabler of future intelligent infrastructure.
This project will focus on the development of novel control, coordination, and decision-making algorithms for multiple autonomous agents—such as robots (robotic manipulators, drones, or vehicles)—that work together to achieve common goals in dynamic, uncertain environments.
Duties
The PhD student will carry out research in the area of cooperative autonomous systems. The successful candidate will explore topics such as:
Multi-agent reinforcement learning
Distributed control and estimation
Multi-agent planning and cooperation
Communication-aware coordination strategies
Learning-based control in networked systems
Resilience and safety in multi-agent systems
Applications in robotics, autonomous driving, healthcare, smart mobility and sensor networks
More Details and Where to apply
https://uu.varbi.com/en/what:job/type:job/jobID:824182
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