Daniel Morgan
Papers
1
Total Citations
187
H-Index
1
About
Daniel Morgan is a leading figure in the field of multi-agent robotics, with a core focus on the guidance, navigation, and control of large-scale autonomous swarms. His most influential contribution is a groundbreaking distributed algorithm that simultaneously solves the optimal assignment and collision-free trajectory generation for swarms of hundreds to thousands of agents. This work, detailed in his highly cited 2016 paper (187 citations), overcomes the critical challenges of limited communication and computation in real-world systems, enabling robust reconfiguration of massive robotic teams. By integrating a variable-swarm auction for task assignment with sequential convex programming for trajectory optimization, Morgan’s research provides a scalable, practical framework that has become a cornerstone for modern swarm robotics. His achievements are particularly notable for bridging the gap between theoretical optimality and the constraints of physical hardware, making him a key contributor to the future of autonomous collective systems.
Research Focus
Key Achievements
Top Papers
- 1