Compliant Sphere Lattice Contact: Distributed Contact Modeling for Sphere-Based Robot Representations

• URL: http://arxiv.org/abs/2608.00263v1
• Date: Fri, 31 Jul 2026 20:11:14 GMT
• Title: Compliant Sphere Lattice Contact: Distributed Contact Modeling for Sphere-Based Robot Representations
• Abstract summary: Sphere-based robot representations satisfy the first requirement by enabling fast collision checking and differentiable geometry.<n>We introduce Compliant Sphere Lattice Contact (CSLC), a distributed contact model that operates on sphere representations.<n>When pressed against an object, the lattice deforms to produce a spatially distributed contact patch that improves the physical accuracy of sphere-based contact.
• Score: 43.70638147331953
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Contact planning in robotics requires models that are both computationally efficient and physically accurate. Sphere-based robot representations satisfy the first requirement by enabling fast collision checking and differentiable geometry, but sacrifice physical accuracy by relying on point contact which cannot capture contact patch area, pressure distributions, rotational stiffness, or frictional moments. We introduce Compliant Sphere Lattice Contact (CSLC), a distributed contact model that operates natively on sphere representations by modeling the robot interface as a compliant lattice of surface spheres connected through anchor and lateral springs. When pressed against an object, the lattice deforms to produce a spatially distributed contact patch that improves the physical accuracy of sphere-based contact. We validate CSLC across two independent solvers and show preliminary results demonstrating contact patch formation and improved grasp stability.

Related papers

• DyG$^2$T: Modeling Object Dynamics with 3D Gaussian Temporal-Spatial Particle Graph Transformer [86.4618122245946]
  DyG$2$T is a dynamics modeling framework that infers object motion trajectories by spatially completing and temporally discriminating Key Point representations.<n>Experiments on both synthetic and real-world datasets demonstrate that DyG$2$T achieves accurate dynamics modeling and reasoning.
  arXiv  Detail & Related papers  (2026-08-19T03:44:28Z)
• Beyond Binary: Sim-to-Real Dexterous Manipulation with Physics-Grounded Contact Representation [51.463992799813816]
  A primary bottleneck in contact-rich manipulation is the difficulty of collecting real-world data.<n>We introduce Center-of-Pressure, an effective tactile representation grounded in physical principles.<n>We evaluate CoP on two blind, challenging contact-rich manipulation tasks.
  arXiv  Detail & Related papers  (2026-05-27T17:59:02Z)
• Unified Complementarity-Based Contact Modeling and Planning for Soft Robots [13.597188299981312]
  This letter presents a unified complementarity-based framework for soft-robot contact modeling and planning.<n>We develop a robust Linear Complementarity Problem (LCP) model tailored to discretized soft robots.<n>We also introduce a kinematically guided warm-start strategy that enables dynamic trajectory optimization through contact.
  arXiv  Detail & Related papers  (2026-02-24T19:37:36Z)
• Semantic-Contact Fields for Category-Level Generalizable Tactile Tool Manipulation [82.63833405368159]
  Generalizing tool manipulation requires both semantic planning and precise physical control.<n>We propose Semantic-Contact Fields (SCFields), a unified 3D representation fusing visual semantics with dense contact estimates.<n> Experiments on scraping, crayon drawing, and peeling demonstrate robust category-level generalization.
  arXiv  Detail & Related papers  (2026-02-14T16:05:08Z)
• A Unified Complementarity-based Approach for Rigid-Body Manipulation and Motion Prediction [12.241353619398899]
  This paper presents a mathematical model for robotic manipulation that consistently captures both free motion and frictional contact within a single formalism (Unicomp)<n> Experimental results show that the proposed approach enables physically consistent behavior at interactive speeds across tasks, from pushing to contact-rich whole-body maneuvers.
  arXiv  Detail & Related papers  (2026-02-04T13:10:57Z)
• Tactile Estimation of Extrinsic Contact Patch for Stable Placement [64.06243248525823]
  We present the design of feedback skills for robots that must learn to stack complex-shaped objects on top of each other. We estimate the contact patch between a grasped object and its environment using force and tactile observations.
  arXiv  Detail & Related papers  (2023-09-25T21:51:48Z)
• Nonrigid Object Contact Estimation With Regional Unwrapping Transformer [16.988812837693203]
  Acquiring contact patterns between hands and nonrigid objects is a common concern in the vision and robotics community. Existing learning-based methods focus more on contact with rigid ones from monocular images. We propose a novel hand-object contact representation called RUPs, which unwraps the roughly estimated hand-object surfaces as multiple high-resolution 2D regional profiles.
  arXiv  Detail & Related papers  (2023-08-27T11:37:26Z)
• Integrated Object Deformation and Contact Patch Estimation from Visuo-Tactile Feedback [8.420670642409219]
  We propose a representation that jointly models object deformations and contact patches from visuo-tactile feedback. We propose a neural network architecture to learn a NDCF, and train it using simulated data. We demonstrate that the learned NDCF transfers directly to the real-world without the need for fine-tuning.
  arXiv  Detail & Related papers  (2023-05-23T18:53:24Z)
• Stability-driven Contact Reconstruction From Monocular Color Images [7.427212296770506]
  Physical contact provides additional constraints for hand-object state reconstruction. Existing methods optimize the hand-object contact driven by distance threshold or prior from contact-labeled datasets. Our key idea is to reconstruct the contact pattern directly from monocular images, and then utilize the physical stability criterion in the simulation to optimize it.
  arXiv  Detail & Related papers  (2022-05-02T12:23:06Z)
• Elastic Tactile Simulation Towards Tactile-Visual Perception [58.44106915440858]
  We propose Elastic Interaction of Particles (EIP) for tactile simulation. EIP models the tactile sensor as a group of coordinated particles, and the elastic property is applied to regulate the deformation of particles during contact. We further propose a tactile-visual perception network that enables information fusion between tactile data and visual images.
  arXiv  Detail & Related papers  (2021-08-11T03:49:59Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.