Pulkit Goyal
Papers
1
Total Citations
1
H-Index
1
About
Pulkit Goyal is an emerging researcher at the intersection of robotics, computer vision, and machine learning, with a primary focus on autonomous navigation and world modeling. His most notable work, "X-MOBILITY: End-to-End Generalizable Navigation via World Modeling" (2025), addresses one of robotics' most persistent challenges: developing navigation systems that generalize across diverse and cluttered real-world environments. By bridging the gap between classical and learning-based approaches, Goyal's research proposes end-to-end frameworks that leverage world models to enable robots to reason about their surroundings more robustly, overcoming the brittleness that has long plagued prior methods. Though still early in its citation trajectory with 1 citation to date, X-MOBILITY represents a timely contribution to the rapidly evolving field of generalizable embodied AI, tackling limitations in both rule-based planning systems and data-hungry neural approaches. Goyal's work reflects a broader trend toward unified, scalable architectures for robot autonomy. Researchers and students working on mobile robotics, sim-to-real transfer, or foundation models for embodied agents will find his contributions a valuable entry point into next-generation navigation research.
Research Focus
Key Achievements
Top Papers
- 1X-MOBILITY: End-to-End Generalizable Navigation via World Modeling1 citations · 2025