Papers
2
Total Citations
8
H-Index
2
About
Sohan Rudra is a robotics researcher whose work bridges autonomous navigation, embodied AI, and adaptive planning under uncertainty. His most impactful contributions center on two key areas: object-goal navigation for dynamic environments and the design of robust autonomous ground vehicles. In his 2023 paper, Rudra introduced a novel contextual bandit framework for learning to plan in environments with probabilistic goal configurations—a significant advance over traditional object-nav systems that assume static targets. By enabling robots to adaptively search for and navigate toward objects whose locations are uncertain, his work pushes embodied AI beyond constrained lab settings toward real-world deployment. His 2019 paper on the Eklavya 6.0 autonomous vehicle demonstrated practical engineering excellence, detailing the design and validation of a three-wheeled differential drive robot capable of GPS-based navigation and lane following. This work earned recognition through participation in the Autonomous Navigation Challenge. With over 8 citations across his most-cited papers, Rudra’s research is gaining traction among scholars interested in modular, learning-driven approaches to mobile robotics. His contributions are particularly relevant for students and researchers working at the intersection of reinforcement learning, planning under uncertainty, and field robotics.
Research Focus
Key Achievements
Top Papers
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