Kenny Chour
Papers
2
Total Citations
21
H-Index
2
About
Kenny Chour is a researcher advancing the frontiers of autonomous multi-agent systems and motion planning. His work centers on two key challenges: enabling persistent autonomy for drone swarms and solving complex pathfinding problems in high-dimensional spaces. In his highly cited 2023 paper, "An agent-based modeling framework for the multi-UAV rendezvous recharging problem" (18 citations), Chour developed a novel framework that allows multiple unmanned aerial vehicles to coordinate rendezvous for recharging, addressing a critical bottleneck in long-duration drone operations. His equally innovative work on "Informed Steiner Trees: Sampling and Pruning for Multi-Goal Path Finding in High Dimensions" (3 citations) introduces a powerful hybrid approach that interleaves sampling-based motion planning with minimum spanning tree pruning techniques. This method enables efficient navigation through complex environments with multiple objectives, a fundamental problem in robotics and autonomous systems. Chour's contributions are particularly notable for bridging theoretical algorithm design with practical deployment challenges, offering scalable solutions for real-world multi-robot coordination. His research has significant implications for applications ranging from search-and-rescue missions to environmental monitoring, where persistent, coordinated autonomous operations are essential.
Research Focus
Key Achievements
Top Papers
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