3 citations · 6 across the 7 of their papers we have counts for
7 papers
Video2Sim2Real: Full-Stack Autonomous Dexterous Skill Acquisition from a Single Human Video
Yunhai Han, Jianuo Qiu, Linhao Bai +14
Human manipulation videos are a convenient and intuitive source for robot learning. However, directly transferring human dexterity to robots remains challenging due to perception e…
Mixed-Initiative Human-Robot Teaming under Suboptimality with Online Bayesian Adaptation
Manisha Natarajan, Chunyue Xue, Sanne van Waveren +2
For effective human-agent teaming, robots and other artificial intelligence (AI) agents must infer their human partner's abilities and behavioral response patterns and adapt accord…
Diffusion-Reinforcement Learning Hierarchical Motion Planning in Multi-agent Adversarial Games
Zixuan Wu, Sean Ye, Manisha Natarajan +1
Reinforcement Learning (RL)-based motion planning has recently shown the potential to outperform traditional approaches from autonomous navigation to robot manipulation. In this wo…
Learning Models of Adversarial Agent Behavior under Partial Observability
Sean Ye, Manisha Natarajan, Zixuan Wu +3
The need for opponent modeling and tracking arises in several real-world scenarios, such as professional sports, video game design, and drug-trafficking interdiction. In this work,…
Diffusion Models for Multi-target Adversarial Tracking
Sean Ye, Manisha Natarajan, Zixuan Wu +1
Target tracking plays a crucial role in real-world scenarios, particularly in drug-trafficking interdiction, where the knowledge of an adversarial target's location is often limite…
Adversarial Search and Tracking with Multiagent Reinforcement Learning in Sparsely Observable Environment
Zixuan Wu, Sean Ye, Manisha Natarajan +3
We study a search and tracking (S&T) problem where a team of dynamic search agents must collaborate to track an adversarial, evasive agent. The heterogeneous search team may only h…
Human-Robot Team Coordination with Dynamic and Latent Human Task Proficiencies: Scheduling with Learning Curves
Ruisen Liu, Manisha Natarajan, Matthew Gombolay
As robots become ubiquitous in the workforce, it is essential that human-robot collaboration be both intuitive and adaptive. A robot's quality improves based on its ability to expl…