Rishi Veerapaneni
Papers
4
Total Citations
20
H-Index
2
About
Rishi Veerapaneni is an emerging researcher specializing in multi-agent systems, robot coordination, and autonomous path planning. His work centers on Multi-Agent Path Finding (MAPF) and its lifelong variant (LMAPF), tackling the complex challenge of coordinating large numbers of robots navigating dynamic environments without collisions while continuously receiving new task assignments. Veerapaneni's most significant contribution to date is his winning approach to the 2023 League of Robot Runners LMAPF competition, detailed in his most-cited work on scaling lifelong MAPF to realistic settings (13 citations). This achievement demonstrates his ability to bridge theoretical research and competitive, real-world application. His follow-up work on deploying ten thousand robots simultaneously using scalable imitation learning pushes the boundaries of what learning-based coordination methods can achieve at unprecedented scale. Additionally, his research on multi-robot-arm motion planning extends conflict-based search algorithms beyond grid environments into the more complex domain of robotic manipulation. Though early in his career, Veerapaneni's competition success and focus on scalable, practical robot deployment position him as a promising contributor to the robotics and autonomous systems community, with his research holding direct relevance for warehouse automation and large-scale logistics applications.
Research Focus
Key Achievements
Top Papers
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