Problem Statement : To implement Centralized and Decentralized approaches to multi agent path finding for different types of multi agent environment.
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- A possible interesting future work can be to explore hybrid approaches that combine the strengths of both centralized and decentralized methods
- We could use a centralized method for high level planning and a decentralized method for low level control This could potentially provide the best of both worlds optimal solutions and scalability
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Dong Hyun Shim, Hyo Jin Kim, and Shankar Sastry. Decentralized nonlinear model predictive control of multiple flying robots. In Decision and Control, 2003. Proceedings. 42nd IEEE Conference on, vol ume 4, pages 3621 3626. IEEE, 2003.
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Javier Alonso Mora, Tobias Naegeli , Roland Siegwart, and Paul Beardsley. Collision avoidance for aerial vehicles in multi agent scenarios. Autonomous Robots, 39(1):101 121, 2015
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Michael Neunert , Cedric de Crousaz , Fadri Furrer , Mina Kamel, Foad Farshidian , Roland Siegwart, and Jonas Buchli . Fast nonlinear model predictive control for unified trajectory optimization and tracking. In Robotics and Automation (ICRA), 2016 IEEE International Conference on, pages 1398 1404. IEEE, 2016.
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Ashwin Bose. Multi agent path planning. Master’s thesis, Ecole Centrale de Nantes, 2022.