TidyBot++：一個用於機器人學習的開源全向移動機械手Manipulator

TidyBot++: An Open-Source Holonomic Mobile Manipulator for Robot Learning

December 11, 2024

作者: Jimmy Wu, William Chong, Robert Holmberg, Aaditya Prasad, Yihuai Gao, Oussama Khatib, Shuran Song, Szymon Rusinkiewicz, Jeannette Bohg

cs.AI

摘要

為了充分利用最近在模仿學習方面的進展，以用於移動操作，需要收集大量人類引導的示範。本文提出了一種開源設計，用於廉價、堅固且靈活的移動操作器，可支援任意臂，從而實現廣泛的現實世界家庭移動操作任務。我們的設計關鍵在於使用動力輪轉輪，使移動底座完全全向運動，能夠獨立且同時控制所有平面自由度。這個特點使底座更靈活，簡化了許多移動操作任務，消除了非全向底座中產生複雜且耗時運動的運動學限制。我們為機器人配備了直觀的手機遠端操作界面，以便進行模仿學習的數據輕鬆獲取。在我們的實驗中，我們使用這個界面來收集數據，並展示所學習的策略能夠成功執行各種常見家庭移動操作任務。

English

Exploiting the promise of recent advances in imitation learning for mobile manipulation will require the collection of large numbers of human-guided demonstrations. This paper proposes an open-source design for an inexpensive, robust, and flexible mobile manipulator that can support arbitrary arms, enabling a wide range of real-world household mobile manipulation tasks. Crucially, our design uses powered casters to enable the mobile base to be fully holonomic, able to control all planar degrees of freedom independently and simultaneously. This feature makes the base more maneuverable and simplifies many mobile manipulation tasks, eliminating the kinematic constraints that create complex and time-consuming motions in nonholonomic bases. We equip our robot with an intuitive mobile phone teleoperation interface to enable easy data acquisition for imitation learning. In our experiments, we use this interface to collect data and show that the resulting learned policies can successfully perform a variety of common household mobile manipulation tasks.