Nachiketa Rajpurohit
Papers
1
Total Citations
7
H-Index
1
About
Nachiketa Rajpurohit is a researcher whose work lies at the intersection of multi-robot systems, reinforcement learning, and autonomous exploration. His most-cited paper, "Reinforcement Learning for Multi-robot Field Coverage Based on Local Observation" (2020, 7 citations), addresses a fundamental challenge in robotics: enabling teams of autonomous mobile robots to efficiently cover unknown or hazardous environments using only local sensory information. This work has direct applications in disaster response, environmental monitoring, and industrial inspection, where centralized control is impractical. By developing decentralized reinforcement learning strategies, Rajpurohit contributes to making multi-robot coordination more scalable and robust. His research is particularly relevant for students and engineers interested in practical, real-world deployment of swarm robotics. While his citation count is still growing, the foundational nature of his work—tackling field coverage with limited communication—positions him as a promising voice in the field of distributed autonomous systems.
Research Focus
Key Achievements
Top Papers
- 1