6 papers
Robots Influencing Humans to Reveal their Goals during Collaboration and Competition
Debasmita Ghose, Oz Gitelson, Michal Lewkowicz +3
We propose a unified strategy for fast goal inference in human-robot interaction. The core idea is to drive the human toward Critical Decision Points (CDPs)-states where competing…
ShelfAware: Real-Time Semantic Localization in Quasi-Static Environments with Low-Cost Sensors
Shivendra Agrawal, Jake Brawer, Ashutosh Naik +2
Many indoor workspaces are quasi-static: their global geometric layout is stable, but local semantics change continually, producing repetitive geometry, dynamic clutter, and percep…
Towards Zero-Shot Coordination between Teams of Agents: The N-XPlay Framework
Ava Abderezaei, Chi-Hui Lin, Joseph Miceli +4
Zero-shot coordination (ZSC) -- the ability to collaborate with unfamiliar partners -- is essential to making autonomous agents effective teammates. Existing ZSC methods evaluate c…
Eyes on the Game: Deciphering Implicit Human Signals to Infer Human Proficiency, Trust, and Intent
Nikhil Hulle, Stéphane Aroca-Ouellette, Anthony J. Ries +3
Effective collaboration between humans and AIs hinges on transparent communication and alignment of mental models. However, explicit, verbal communication is not always feasible. U…
Towards A Natural Language Interface for Flexible Multi-Agent Task Assignment
Jake Brawer, Kayleigh Bishop, Bradley Hayes +1
Task assignment and scheduling algorithms are powerful tools for autonomously coordinating large teams of robotic or AI agents. However, the decisions these system make often rely…
That's Mine! Learning Ownership Relations and Norms for Robots
Zhi-Xuan Tan, Jake Brawer, Brian Scassellati
The ability for autonomous agents to learn and conform to human norms is crucial for their safety and effectiveness in social environments. While recent work has led to frameworks…