Chirag Rastogi
Papers
1
Total Citations
28
H-Index
1
About
Chirag Rastogi is a robotics researcher whose work centers on advancing autonomous ground vehicle (UGV) perception and navigation through innovative sensor fusion techniques. His primary research areas include terrain classification, vision-proprioception integration, and robust localization for mobile robots operating in complex outdoor environments. Rastogi’s most significant contribution is his development of a CNN-based method that fuses visual data with proprioceptive signals—such as wheel-terrain interaction measurements—to enable UGVs to accurately classify terrain types in real time. This approach addresses a critical limitation of vision-only systems, which can fail in low-light or obscured conditions, by leveraging the complementary strengths of both sensing modalities. His landmark 2021 paper on this topic has already garnered 28 citations, reflecting its growing influence in the field of field robotics. By improving a vehicle’s ability to distinguish between gravel, grass, pavement, and other surfaces, Rastogi’s work directly enhances the reliability of localization and mapping in unstructured environments—a key step toward deploying autonomous vehicles in agriculture, search-and-rescue, and planetary exploration.
Research Focus
Key Achievements
Top Papers
- 1