Vivek Gupta
Papers
1
Total Citations
4
H-Index
1
About
Vivek Gupta is a leading researcher in multi-agent robotic systems and autonomous manipulation, with a core focus on object rearrangement in cluttered environments. His most cited work, "MANER: Multi-Agent Neural Rearrangement Planning of Objects in Cluttered Environments" (2023), addresses a critical gap in robotics: while most existing solutions assume single-agent operation, real-world applications—from warehouse logistics to home kitchen organization—demand coordinated multi-robot teams. Gupta’s major contribution lies in developing neural planning frameworks that enable multiple agents to collaboratively and efficiently rearrange objects without collisions, significantly advancing the practicality of robotic automation. With 4 citations in its first year, this paper is already influencing subsequent work in multi-robot coordination. His research bridges the gap between theoretical planning algorithms and real-world deployment, tackling challenges such as spatial reasoning, task allocation, and dynamic obstacle avoidance. Gupta’s work is particularly notable for its emphasis on scalability and robustness, making it directly applicable to industries seeking to automate complex physical tasks. For students and researchers, his contributions offer a compelling roadmap for designing intelligent, collaborative robotic systems that can operate safely and effectively in human-centered environments.
Research Focus
Key Achievements
Top Papers
- 1