Learning from Humans for Proactive Assistance in Human-Robot Collaborative Transport
We focus on human-robot collaborative transport, a challenging task of broad relevance spanning logistics, manufacturing, and the home, in which a user and a robot work together to relocate a large or heavy object. To act as an effective partner, the robot should reduce the user's effort by contributing to efficient relocation of the object while remaining physically responsive to them. Prior work often addresses these capabilities separately, producing robots that may move the object efficiently but resist user input, or accommodate the user but depend on continuous guidance. Our key insight is that obstacle-constrained collaborative transport requires integrating predictions of human co...
| Authors | Elvin Yang, Christoforos Mavrogiannis |
|---|---|
| Primary category | cs.RO |
| Published | 21 September 2026 |
| Last updated at source | 21 September 2026 |
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