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

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arxiv 2412.10447 v1 pith:NIEJO62X submitted 2024-12-11 cs.RO cs.AIcs.CVcs.LG

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

classification cs.RO cs.AIcs.CVcs.LG
keywords mobilemanipulationlearningtasksbasedatadesignenable
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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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.

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Cited by 3 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. KinDER: A Physical Reasoning Benchmark for Robot Learning and Planning

    cs.RO 2026-04 unverdicted novelty 7.0

    KinDER is a new open-source benchmark that demonstrates substantial gaps in current robot learning and planning methods for handling physical constraints.

  2. ModPack: An Extensible Teleoperation Interface for Bimanual Mobile Manipulation

    cs.RO 2026-07 conditional novelty 6.0

    A modular backpack-based teleoperation interface enables bimanual mobile manipulation with haptic feedback and active perception across multiple robot platforms.

  3. Uni-NaVid: A Video-based Vision-Language-Action Model for Unifying Embodied Navigation Tasks

    cs.RO 2024-12 unverdicted novelty 6.0

    Uni-NaVid unifies diverse embodied navigation tasks into one video-based vision-language-action model trained on 3.6 million samples from four sub-tasks, achieving state-of-the-art performance on benchmarks and real-w...