CDM: Contact Diffusion Model for Multi-Contact Point Localization

In this paper, we propose a Contact Diffusion Model (CDM), a novel learning-based approach for multi-contact point localization. We consider a robot equipped with joint torque sensors and a force/torque sensor at the base. By leveraging a diffusion model, CDM addresses the singularity where multiple pairs of contact points and forces  produce identical sensor measurements. We formulate CDM to be conditioned on past model outputs to fit this problem domain. Moreover, to effectively address the complex shape of the robot surfaces, we incorporate the signed distance field in the denoising process. Consequently, CDM can localize contacts at arbitrary locations with high accuracy. Simulation and real-world experiments demonstrate the effectiveness of the proposed method. In particular, CDM operates at 15.97ms and, in the real world, achieves an error of 0.44cm in single-contact scenarios and 1.24cm in dual-contact scenarios.

Contact : Seo Wook Han (seowook.han@kaist.ac.kr)

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Related Publications

Seo Wook Han, and Min Jun Kim, “CDM: Contact Diffusion Model for Multi-Contact Point Localization”,  ICRA 2025 [arXiv]

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