# CDM: Contact Diffusion Model for Multi-Contact Point Localization

arXiv: https://arxiv.org/abs/2502.06109 · HTML: https://mlsanity.com/paper/2502.06109/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Placed in Diffusion and flow policies for robotics, one of 14 directions in Diffusion models.
- Builds on 14 of its 39 references that are in the map.
- First posted on arXiv 10 Feb 2025.

## Placed in

- Diffusion models / [Diffusion and flow policies for robotics](https://mlsanity.com/diffusion/diffusion-and-flow-policies-for-robotics/)

## Builds on (most cited first, 14 of 14)

- [Denoising Diffusion Probabilistic Models](https://mlsanity.com/paper/2006.11239/) (2020)
- [U-Net: Convolutional Networks for Biomedical Image Segmentation](https://mlsanity.com/paper/1505.04597/) (2015)
- [Denoising Diffusion Implicit Models](https://mlsanity.com/paper/2010.02502/) (2020)
- [Score-Based Generative Modeling through Stochastic Differential Equations](https://mlsanity.com/paper/2011.13456/) (2020)
- [Diffusion Policy: Visuomotor Policy Learning via Action Diffusion](https://mlsanity.com/paper/2303.04137/) (2023)
- [FiLM: Visual Reasoning with a General Conditioning Layer](https://mlsanity.com/paper/1709.07871/) (2017)
- [Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains](https://mlsanity.com/paper/2006.10739/) (2020)
- [Understanding Diffusion Models: A Unified Perspective](https://mlsanity.com/paper/2208.11970/) (2022)
- [Deep Medial Fields](https://mlsanity.com/paper/2106.03804/) (2021)
- [Model-free Friction Observers for Flexible Joint Robots with Torque Measurements](https://mlsanity.com/paper/1907.00553/) (2019)
- [A Passivity-based Nonlinear Admittance Control with Application to Powered Upper-limb Control under Unknown Environmental Interactions](https://mlsanity.com/paper/1904.08833/) (2019)
- [A Reachability Tree-Based Algorithm for Robot Task and Motion Planning](https://mlsanity.com/paper/2303.03825/) (2023)
- [Proprioceptive Sensor-Based Simultaneous Multi-Contact Point Localization and Force Identification for Robotic Arms](https://mlsanity.com/paper/2303.03903/) (2023)
- [Online Multi-Contact Feedback Model Predictive Control for Interactive Robotic Tasks](https://mlsanity.com/paper/2403.08302/) (2024)

## Abstract (arXiv)

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 account for the time-dependent characteristics of the multi-contact scenarios. 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.