5 papers
MoS-VLA: A Vision-Language-Action Model with One-Shot Skill Adaptation
Ruihan Zhao, Tyler Ingebrand, Sandeep Chinchali +1
Vision-Language-Action (VLA) models trained on large robot datasets promise general-purpose, robust control across diverse domains and embodiments. However, existing approaches oft…
IG-MCTS: Human-in-the-Loop Cooperative Navigation under Incomplete Information
Shenghui Chen, Ruihan Zhao, Sandeep Chinchali +1
Human-robot cooperative navigation is challenging under incomplete information. We introduce CoNav-Maze, a simulated environment where a robot navigates with local perception while…
Dense Dynamics-Aware Reward Synthesis: Integrating Prior Experience with Demonstrations
Cevahir Koprulu, Po-han Li, Tianyu Qiu +5
Many continuous control problems can be formulated as sparse-reward reinforcement learning (RL) tasks. In principle, online RL methods can automatically explore the state space to…
Human-Agent Coordination in Games under Incomplete Information via Multi-Step Intent
Shenghui Chen, Ruihan Zhao, Sandeep Chinchali +1
Strategic coordination between autonomous agents and human partners under incomplete information can be modeled as turn-based cooperative games. We extend a turn-based game under i…
PEERNet: An End-to-End Profiling Tool for Real-Time Networked Robotic Systems
Aditya Narayanan, Pranav Kasibhatla, Minkyu Choi +3
Networked robotic systems balance compute, power, and latency constraints in applications such as self-driving vehicles, drone swarms, and teleoperated surgery. A core problem in t…