TidyBot++: An Open-Source Holonomic Mobile Manipulator for Robot Learning
Abstract
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.
Community
Project page: https://tidybot2.github.io
Docs: https://tidybot2.github.io/docs
Code: https://github.com/jimmyyhwu/tidybot2
This is an automated message from the Librarian Bot. I found the following papers similar to this paper.
The following papers were recommended by the Semantic Scholar API
- DexMimicGen: Automated Data Generation for Bimanual Dexterous Manipulation via Imitation Learning (2024)
- Versatile Demonstration Interface: Toward More Flexible Robot Demonstration Collection (2024)
- Learning to Look Around: Enhancing Teleoperation and Learning with a Human-like Actuated Neck (2024)
- WildLMa: Long Horizon Loco-Manipulation in the Wild (2024)
- ARMADA: Augmented Reality for Robot Manipulation and Robot-Free Data Acquisition (2024)
- LEGATO: Cross-Embodiment Imitation Using a Grasping Tool (2024)
- Self-Improving Autonomous Underwater Manipulation (2024)
Please give a thumbs up to this comment if you found it helpful!
If you want recommendations for any Paper on Hugging Face checkout this Space
You can directly ask Librarian Bot for paper recommendations by tagging it in a comment:
@librarian-bot
recommend
Models citing this paper 0
No model linking this paper
Datasets citing this paper 0
No dataset linking this paper
Spaces citing this paper 0
No Space linking this paper
Collections including this paper 0
No Collection including this paper