Implicit Contact Diffuser: Sequential Contact Reasoning with Latent Point Cloud Diffusion
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Abstract (arXiv)
Long-horizon contact-rich manipulation has long been a challenging problem, as it requires reasoning over both discrete contact modes and continuous object motion. We introduce Implicit Contact Diffuser (ICD), a diffusion-based model that generates a sequence of neural descriptors that specify a series of contact relationships between the object and the environment. This sequence is then used as guidance for an MPC method to accomplish a given task. The key advantage of this approach is that the latent descriptors provide more task-relevant guidance to MPC, helping to avoid local minima for contact-rich manipulation tasks. Our experiments demonstrate that ICD outperforms baselines on complex, long-horizon, contact-rich manipulation tasks, such as cable routing and notebook folding. Additionally, our experiments also indicate that methodshort can generalize a target contact relationship to a different environment. More visualizations can be found on our website hrefhttps://implicit-contact-diffuser.github.io/https://implicit-contact-diffuser.github.io
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 49 of its 64 references that are in the map. First posted on arXiv 21 Oct 2024.
Builds on
49 of 64 references.
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Citing papers per year: 2025: 1.
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