Mixed-Initiative Dialog for Human-Robot Collaborative Manipulation
This is experimental HTML to improve accessibility. We invite you to report rendering errors. Use Alt+Y to toggle on accessible reporting links and Alt+Shift+Y to toggle off. Learn more about this project and help improve conversions. HTML conversions sometimes display errors due to content that did not convert correctly from the source. This paper uses the following packages that are not yet supported by the HTML conversion tool. Feedback on these issues are not necessary; they are known and are being worked on. Authors: achieve the best HTML results from your LaTeX submissions by following these best practices. Effective robotic systems for long-horizon human-robot collaboration must adapt to a wide range of human partners, whose physical behavior, willingness to assist, and understanding of the robot’s capabilities may change over time. This demands a tightly coupled communication loop that grants both agents the flexibility to propose, accept, or decline requests as they coordinat
Mixed-Initiative Dialog for Human-Robot Collaborative Manipulation Albert Yu &Chengshu Li &Luca Macesanu &Arnav Balaji &Ruchira Ray &Ray Mooney &Roberto Martín-Martín Albert Yu 1 , Chengshu Li 2 , Luca Macesanu 1 , Arnav Balaji 1 , Ruchira Ray 1 , Raymond Mooney 1 , and Roberto Martín-Martín 1 1 UT Austin, 2 Stanford albertyu@utexas.edu Abstract Effective robotic systems for long-horizon human-robot collaboration must adapt to a wide range of human partners, whose physical behavior, willingness to assist, and understanding of the robot’s capabilities may change over time. This demands a tightl
Explore this link on the map →related reading
- Interaction Models: A Scalable Approach to Human-AI Collaboration - Thinking Machines Labthinkingmachines.ai
- Scalable Multi-Robot Collaboration with Large Language Models: Centralized or Decentralized Systems?arxiv.org
- [2109.01115] Learning Language-Conditioned Robot Behavior from Offline Data and Crowd-Sourced Annotationarxiv.org
- Moving Out: Physically-grounded Human-AI Collaborationlive-robotics-uva.github.io
- [2301.02555] “No, to the Right” – Online Language Corrections for Robotic Manipulation via Shared Autonomyar5iv.labs.arxiv.org
- Teaching Robots to Listen and Think Harderxn--1xa.com
- SayCan: Grounding Language in Robotic Affordancessay-can.github.io
- Helix: A Vision-Language-Action Model for Generalist Humanoid Controlfigure.ai
- Continual Skill and Task Learning via Dialoguearxiv.org
- State of Robot Learning, December 2025vedder.io
- A Steerable Model with Emergent Capabilitiespi.website
- Language Models can Solve Computer Tasksarxiv.org