Rishi Mohan
Papers
2
Total Citations
9
H-Index
2
About
Rishi Mohan’s research lies at the intersection of autonomous robotics, motion planning, and human–robot interaction, with a focus on enabling robots to operate safely and predictably in dynamic, human-centered environments. His work addresses two critical challenges: robust sensor planning under occlusion and collision-free trajectory generation with deadlock prevention. In his 2019 paper on optimal sensor planning, Mohan introduced a probabilistic optimization framework to handle dynamic occlusions in robotic workspaces, improving detection reliability in uncertain environments. His 2020 work on collision-free trajectory planning proposed an adaptive virtual target approach that prevents deadlocks while guiding robots along predefined paths—a key requirement for human-acceptable autonomous movement. Though early in his career, with his most-cited papers garnering 4–5 citations each, Mohan’s contributions are foundational for advancing safe, predictable robot navigation in shared spaces. His research is particularly relevant for applications in manufacturing, service robotics, and autonomous vehicles, where robots must seamlessly integrate with human workflows.
Research Focus
Key Achievements
Top Papers
- 1
- 2