This research develops scalable motion-planning algorithms that enable large teams of robots to work together safely and efficiently. By combining machine learning with search algorithms, the work delivers both speed and reliability, supporting applications from automated warehouses to disaster response, infrastructure repair, and future space exploration.

The speaker develops a decentralised communication framework for collaborative robots (cobots). By removing the central server and enabling robots to communicate directly through estimating unknown variables, the system reduces cost, time, and memory use. This foundation supports efficient task allocation for applications like delivery and firefighting.

My research develops fault-tolerant, cooperative control algorithms for multi-drone formations carrying shared payloads. By detecting motor failures, restoring lost force, and autonomously reconfiguring drone positions, the system reduces load disturbances by up to 90%. These methods enable safer, more reliable drone-assisted rescue and delivery operations in hazardous conditions.