7 papers
Learning to Assist: Collaborative VLAs for Implicit Human-Robot Collaboration
Leo Xu, Letian Li, Alex Cuellar +1
Human-robot collaboration (HRC) combines the complementary strengths of humans and robots to improve task efficiency. However, many existing collaborative systems rely on hand-engi…
Hide-and-Seek in Trajectories: Discovering Failure Signals for VLA Runtime Monitoring
Seongheon Park, Wendi Li, Changdae Oh +4
Vision-Language-Action (VLA) models enable robots to follow natural language instructions and generalize across diverse tasks, but they remain vulnerable to execution failures that…
Multi-Cycle Spatio-Temporal Adaptation in Human-Robot Teaming
Alex Cuellar, Michael Hagenow, Julie Shah
Effective human-robot teaming is crucial for the practical deployment of robots in human workspaces. However, optimizing joint human-robot plans remains a challenge due to the diff…
Analyzing Reluctance to Ask for Help When Cooperating With Robots: Insights to Integrate Artificial Agents in HRC
Ane San Martin, Michael Hagenow, Julie Shah +2
As robot technology advances, collaboration between humans and robots will become more prevalent in industrial tasks. When humans run into issues in such scenarios, a likely future…
REALM: Real-Time Estimates of Assistance for Learned Models in Human-Robot Interaction
Michael Hagenow, Julie A. Shah
There are a variety of mechanisms (i.e., input types) for real-time human interaction that can facilitate effective human-robot teaming. For example, previous works have shown how…
Versatile Demonstration Interface: Toward More Flexible Robot Demonstration Collection
Michael Hagenow, Dimosthenis Kontogiorgos, Yanwei Wang +1
Previous methods for Learning from Demonstration leverage several approaches for a human to teach motions to a robot, including teleoperation, kinesthetic teaching, and natural dem…