At the end of this page, you can find the full list of publications and patents. All papers are also available on arXiv.

Vision Language Action models often fail at execution time due to distractor objects and physical obstructions. StageCraft is a training-free approach that uses vision-language model reasoning over policy rollout videos and success labels to identify which objects to reposition before execution, preventing anticipated failures. It improves performance by roughly 40% across three real-world task domains, adapting its interventions to the strength of the underlying policy.
Kartikay Milind Pangaonkar, Prabin Rath, Omkar Patil, Nakul Gopalan
2026 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
StageCraft: Execution Aware Mitigation of Distractor and Obstruction Failures in VLA Models
Kartikay Milind Pangaonkar, Prabin Rath, Omkar Patil, Nakul Gopalan
2026 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
PokeNet: Learning Kinematic Models of Articulated Objects from Human Observations
Anmol Gupta, Weiwei Gu, Omkar Patil, Jun Ki Lee, Nakul Gopalan
2026 IEEE International Conference on Robotics and Automation (ICRA)
Factorizing Diffusion Policies for Observation Modality Prioritization
Omkar Patil, Prabin Rath, Kartikay Pangaonkar, Eric Rosen, Nakul Gopalan
2026 IEEE International Conference on Robotics and Automation (ICRA)
XMoP- Whole-Body Control Policy for Zero-shot Cross-Embodiment Neural Motion Planning
Prabin Kumar Rath, Nakul Gopalan
2025 IEEE International Conference on Robotics and Automation (ICRA)
Learning Temporally Composable Task Segmentations with Language
Divyanshu Raj, Omkar Patil, Weiwei Gu, Chitta Baral, Nakul Gopalan
2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
Hardware-Software Co-Design for Path Planning by Drones
Ayushi Dube, Omkar Patil, Gian Singh, Nakul Gopalan, Sarma Vrudhula
2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
Interactive Visual Task Learning for Robots
Weiwei Gu, Anant Sah, Nakul Gopalan
In Proceedings of The 38th Annual AAAI Conference on Artificial Intelligence