arXiv cs.AI· Yulin Liu, Lai Wei, Yen-Jen Wang, Akash Sharma, Pieter Abbeel, Henrik I. Christensen, Haozhi Qi·· 6 天前AI 评分34
GOTT：基于可复用跨本体原语的物体中心灵巧操作
GOTT: Object-centric Dexterous Manipulation with a Reusable Cross-Embodiment Primitive
AI 导读
GOTT 是一个围绕单一跨本体接触获取原语构建的 reach-acquire-move 框架，可将机器人无关的物体轨迹与 reach 规格转化为多指手的稳定接触与运动跟踪。仿真与真实实验显示，GOTT 能在多种物体、臂手平台以及已见和未见手部形态上建立稳健接触，并持续提升端到端任务成功率，优于开环抓取执行。
正文 · 原文
Abstract:Foundation models and large-scale human data provide rich sources of manipulation intent, but translating this intent into multi-fingered robot behavior remains difficult. Dexterous hands still lack a reusable low-level primitive that reliably establishes contact across tasks and embodiments. We propose GOTT, a reach-acquire-move framework built around a single cross-embodiment contact-acquisition primitive. Given a robot-agnostic object trajectory and a reach specification, GOTT first brings the hand near a task-relevant contact region. The shared closed-loop primitive then establishes stable contact from this approximate initialization, and a pose-conditioned controller tracks the desired object motion. Reach specifications may come from future-aware planning, external models, or human demonstrations, while the primitive and tracking backend remain unchanged. Simulation and real-world experiments show that GOTT is able to establish robust contact across diverse objects, arm-hand platforms, and seen and unseen hand morphologies. It also consistently improves end-to-end task success over open-loop grasp execution.
| Comments: | Project page: this https URL |
| Subjects: | Robotics (cs.RO); Artificial Intelligence (cs.AI); Computer Vision and Pattern Recognition (cs.CV) |
| Cite as: | arXiv:2610.03861 [cs.RO] |
| (or arXiv:2610.03861v2 [cs.RO] for this version) | |
| https://doi.org/10.48550/arXiv.2610.03861 arXiv-issued DOI via DataCite |
Submission history
From: Yulin Liu [view email]
[v1]
Fri, 2 Oct 2026 17:58:42 UTC (8,136 KB)
[v2]
Thu, 8 Oct 2026 23:54:24 UTC (8,136 KB)
来源：arXiv cs.AI · arxiv.org