arXiv:2605.30569 · v2

Any-ttach: Quick End-effector Swapping Enables Manipulation Dexterity with Simplicity

首次提交 2026-05-29 05:00

版本更新 2026-11-01 10:36

雷达观测 2026-11-04 23:43

摘要

Robotic manipulation dexterity is often pursued by building increasingly complex high-DoF multifingered hands. While many robotic hands are designed to replicate the morphology of human hands, the functional role of human hands suggests a different perspective: much of their complexity may exist to enable tool use and tool making. This observation motivates Any-ttach, a tool-centric manipulation system that leverages mechanical modularity and treats autonomous end-effector swapping as a pathway towards dexterity. Any-ttach combines: 1) a low-cost standardized interface with passive self-locking and mechanically triggered release mechanism; 2) a unified object-centric manipulation framework supporting kinesthetic teaching trajectory replay, human demonstration retargeting, and policy learning; and 3) hierarchical planning and execution system for tools and skills for multi-tool long-horizon tasks. We demonstrated 15 heterogeneous end-effector modules supported by our system, spanning different robotic fingers, everyday tools (including articulated tools such as scissors), and unconventional end-effectors through the same interface. Experiments demonstrate reliable autonomous swapping, automatic integration to new tools, and broad manipulation capability across different skill sources. Two multi-tool application demonstrations, comprising seven tool--skill steps across two tasks, further illustrate the autonomous composition of end-effector exchange and heterogeneous manipulation skills. These results show that end-effector swapping can expand manipulation capability without concentrating increasing complexity entirely in a single end-effector. More details and videos are available at https://any-ttach.github.io/.

作者备注：8 pages, 5 figures. Submitted to IEEE Robotics and Automation Letters