aiqbench analysis
M3-Tele represents a significant advancement in robot learning by unifying multimodal perception with compliant whole-body control, directly addressing bottlenecks in collecting high-quality data for downstream policy models. The framework's integration of tactile and force sensing notably enhances stability during contact-rich tasks, which is critical for training robust diffusion policies and other ML architectures used in robotics.
M3-Tele: A Unified Multimodal Teleoperational Framework for Compliant Whole-Body Mobile Manipulation
arXiv:2609.07859v1 Announce Type: new Abstract: Executing contact-rich tasks efficiently requires the seamless integration of whole-body coordination and physical compliance regulation. However, existing teleoperation and data-collection frameworks often overlook the joint consideration of multimodal perception and coordinated whole-body operation. This limitation can reduce the efficiency and quality of demonstration collection, thereby affecting the effectiveness of downstream policy learning. In this work, we present \textbf{M3-Tele}: A Unified \underline{M}ultimodal \underline{Tele}operational Framework for Compliant Whole-Body \underline{M}obile \underline{M}anipulation, enabling stable physical interaction and capturing aligned visual, tactile, force, and proprioceptive observations during task execution. Extensive experiments demonstrate that the proposed framework significantly improves contact-rich teleoperation performance. The proposed controller reduces the force tracking error from 4.132~N to 0.346~N, the contact loss from 2.46 to 0.02 events per trial and the tactile deformation error by 65\%. User studies across four mobile manipulation tasks also verify the reliability and usability of the proposed system. Furthermore, Diffusion Policy experiments highlight the value of joint tactile and force sensing.
Abstract:Executing contact-rich tasks efficiently requires the seamless integration of whole-body coordination and physical compliance regulation. However, existing teleoperation and data-collection frameworks often overlook the joint consideration of multimodal perception and coordinated whole-body operation. This limitation can reduce the efficiency and quality of demonstration collection, thereby affecting the effectiveness of downstream policy learning. In this work, we present \textbf{M3-Tele}: A Unified \underline{M}ultimodal \underline{Tele}operational Framework for Compliant Whole-Body \underline{M}obile \underline{M}anipulation, enabling stable physical interaction and capturing aligned visual, tactile, force, and proprioceptive observations during task execution. Extensive experiments demonstrate that the proposed framework significantly improves contact-rich teleoperation performance. The proposed controller reduces the force tracking error from 4.132~N to 0.346~N, the contact loss from 2.46 to 0.02 events per trial and the tactile deformation error by 65\%. User studies across four mobile manipulation tasks also verify the reliability and usability of the proposed system. Furthermore, Diffusion Policy experiments highlight the value of joint tactile and force sensing.
Robotics (cs.RO)
arXiv:2609.07859 [cs.RO]
(or arXiv:2609.07859v1 [cs.RO] for this version)
https://doi.org/10.48550/arXiv.2609.07859 Focus to learn more arXiv-issued DOI via DataCite (pending registration)
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