Mobile ALOHA: Learning Bimanual Mobile Manipulation with Low-Cost Whole-Body Teleoperation

Zipeng Fu, Tony Z. Zhao, Chelsea Finn
1/4/2024
cs.ROcs.AIcs.CV

No official code found. Best implementation: MarkFzp/mobile-aloha (4,452 stars, MIT, last commit 2024-06-22). 1 more below.

Abstract

Imitation learning from human demonstrations has shown impressive performance in robotics. However, most results focus on table-top manipulation, lacking the mobility and dexterity necessary for generally useful tasks. In this work, we develop a system for imitating mobile manipulation tasks that are bimanual and require whole-body control. We first present Mobile ALOHA, a low-cost and whole-body teleoperation system for data collection. It augments the ALOHA system with a mobile base, and a whole-body teleoperation interface. Using data collected with Mobile ALOHA, we then perform supervised behavior cloning and find that co-training with existing static ALOHA datasets boosts performance on mobile manipulation tasks. With 50 demonstrations for each task, co-training can increase success rates by up to 90%, allowing Mobile ALOHA to autonomously complete complex mobile manipulation tasks such as sauteing and serving a piece of shrimp, opening a two-door wall cabinet to store heavy cooking pots, calling and entering an elevator, and lightly rinsing a used pan using a kitchen faucet. Project website: https://mobile-aloha.github.io

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Code Implementations(2)

MarkFzp/mobile-alohaCommunity66%
MIT

Mobile ALOHA: Learning Bimanual Mobile Manipulation with Low-Cost Whole-Body Teleoperation

4,452733CMake, ShellJul 4, 20232 years agoMIT
imitation-learningrobotics
Stazsans/mobile-aloha-srCommunity63%

Mobile ALOHA: Learning Bimanual Mobile Manipulation with Low-Cost Whole-Body Teleoperation

11CMake, ShellDec 12, 202510 months ago

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Cite this paper

@article{fu2024mobile,
  title  = {Mobile ALOHA: Learning Bimanual Mobile Manipulation with Low-Cost Whole-Body Teleoperation},
  author = {Zipeng Fu and Tony Z. Zhao and Chelsea Finn},
  year   = {2024},
  eprint = {2401.02117},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2401.02117v1}
}

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