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Learning Force-Reactive Humanoid Loco-Manipulation

Paper recorded by Signals 4 on 2026-10-26 in cs.AI. Abstract reproduced from arXiv; link to the original below.

Published 2026-10-26 on arXiv · recorded by Signals 4 on 2026-10-27

Category: cs.AI · 人工智能 · first seen 2026-10-27

Abstract

Many everyday tasks require controlling contact force as well as motion. On a humanoid, this force must often be coordinated across both hands and the whole body, and cannot be specified by kinematic trajectories alone. Therefore, we present FLORE, a framework for learning force-reactive humanoid loco-manipulation. We collect robot-free demonstrations using two force-sensing UMI-style handheld gri

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#143 most recent of 960 cs.AI papers we have recorded · ↑ newer: Center-of-Mass Interpretation of Evolution Strategies · ↓ older: Patient-specific rubric-based evaluation of large language models acro
Cite this page: Learning Force-Reactive Humanoid Loco-Manipulation: the #143 most recent of 960 cs.AI papers we have recorded (as of 2026-10-26). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/learning-force-reactive-humanoid-loco-manipulation.html
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