A Unified Complementarity-based Approach for Rigid-Body Manipulation and Motion Prediction

• URL: http://arxiv.org/abs/2602.04522v1
• Date: Wed, 04 Feb 2026 13:10:57 GMT
• Title: A Unified Complementarity-based Approach for Rigid-Body Manipulation and Motion Prediction
• Abstract summary: 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.
• Score: 12.241353619398899
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Robotic manipulation in unstructured environments requires planners to reason jointly about free-space motion and sustained, frictional contact with the environment. Existing (local) planning and simulation frameworks typically separate these regimes or rely on simplified contact representations, particularly when modeling non-convex or distributed contact patches. Such approximations limit the fidelity of contact-mode transitions and hinder the robust execution of contact-rich behaviors in real time. This paper presents a unified discrete-time modeling framework for robotic manipulation that consistently captures both free motion and frictional contact within a single mathematical formalism (Unicomp). Building on complementarity-based rigid-body dynamics, we formulate free-space motion and contact interactions as coupled linear and nonlinear complementarity problems, enabling principled transitions between contact modes without enforcing fixed-contact assumptions. For planar patch contact, we derive a frictional contact model from the maximum power dissipation principle in which the set of admissible contact wrenches is represented by an ellipsoidal limit surface. This representation captures coupled force-moment effects, including torsional friction, while remaining agnostic to the underlying pressure distribution across the contact patch. The resulting formulation yields a discrete-time predictive model that relates generalized velocities and contact wrenches through quadratic constraints and is suitable for real-time optimization-based planning. Experimental results show that the proposed approach enables stable, physically consistent behavior at interactive speeds across tasks, from planar pushing to contact-rich whole-body maneuvers.

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)
• AdaDexGrasp: Adaptive Dexterous Grasping via 3D Visuo-Tactile Representation Fusion [60.79507611737292]
  Humans achieve stable and adaptive grasps by seamlessly integrating visual perception and tactile feedback.<n>Existing robotic grasping approaches rely on visual inputs and lack mechanisms for tactile-guided adaptation after contact.<n>We propose a unified visuo-tactile-fusion grasping framework that integrates grasp generation, feasibility prediction, and adaptive refinement.
  arXiv  Detail & Related papers  (2026-08-06T16:29:11Z)
• Seeing Touch from Motion: A Unified Modality-Aware Visuo-Tactile Policy with Tactile Motion Correlation [74.87716678195099]
  Visuo-Tactile policies leveraging optical tactile sensors have shown great promise in contact-rich manipulation.<n>Despite their advantages, extracting fine-grained contact states necessary for contact-rich manipulation remains an open challenge.<n>We propose a motion-aware tactile representation to facilitate contact-rich manipulation.
  arXiv  Detail & Related papers  (2026-06-29T08:20:18Z)
• PRIME: Physically-consistent Robotic Inertial and Motion Estimation for Legged and Humanoid Robots [6.944742823560998]
  We propose PRIME to enable accurate motion estimation from onboard kinematics in real-world deployment.<n>Our approach incorporates differentiable contact dynamics with smoothed complementarity constraints and an Anitescu-style friction model.<n> PRIME can be calibrated to provide high-quality data for downstream learning applications, including large-scale behavior modeling and robot foundation models.
  arXiv  Detail & Related papers  (2026-05-17T22:43:10Z)
• ForceFlow: Learning to Feel and Act via Contact-Driven Flow Matching [53.30290192030814]
  ForceFlow is a force-aware reactive framework built upon flow matching.<n>We show that ForceFlow achieves a 37% success rate improvement over the strong baseline ForceVLA.<n>It also exhibits accurate force signal prediction and superior performance in contact force self-regulation.
  arXiv  Detail & Related papers  (2026-05-11T13:27:00Z)
• SocialMirror: Reconstructing 3D Human Interaction Behaviors from Monocular Videos with Semantic and Geometric Guidance [49.69016078147708]
  Accurately reconstructing human behavior in close-interaction scenarios is crucial for enabling realistic virtual interactions in augmented reality.<n>We propose SocialMirror, a diffusion-based framework that integrates semantic and geometric cues to effectively address these issues.<n>SocialMirror achieves state-of-the-art performance in reconstructing interactive human meshes, demonstrating strong generalization across unseen datasets and in-the-wild scenarios.
  arXiv  Detail & Related papers  (2026-04-15T07:41:52Z)
• ComFree-Sim: A GPU-Parallelized Analytical Contact Physics Engine for Scalable Contact-Rich Robotics Simulation and Control [7.095015036485825]
  We present a GPU-parallelized analytical contact physics engine built on complementarity-free contact modeling.<n>ComFree-Sim computes contact impulses in closed form via an impedance-style prediction--correction update in the dual cone of Coulomb friction.
  arXiv  Detail & Related papers  (2026-03-12T17:14:45Z)
• 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)
• Manipulation via Force Distribution at Contact [2.3099144596725565]
  This study introduces a Force-Distributed Line Contact model in contact-rich manipulation.<n>A bi-level optimization framework is constructed, in which the lower-level solves an optimization problem for contact force computation.<n>The benefits of the FDLC in generating efficient and robust trajectories are established.
  arXiv  Detail & Related papers  (2026-02-03T10:22:36Z)
• Frictional Contact Solving for Material Point Method [11.766605623329754]
  We introduce a frictional-contact pipeline for implicit MPM that is both precise and robust.<n>The method integrates seamlessly into the implicit MPM loop and is agnostic to modeling choices, including material laws, functions, and transfer schemes.
  arXiv  Detail & Related papers  (2026-02-02T12:34:32Z)
• Interact2Ar: Full-Body Human-Human Interaction Generation via Autoregressive Diffusion Models [80.28579390566298]
  We introduce Interact2Ar, a text-conditioned autoregressive diffusion model for generating full-body, human-human interactions.<n>Hand kinematics are incorporated through dedicated parallel branches, enabling high-fidelity full-body generation.<n>Our model enables a series of downstream applications, including temporal motion composition, real-time adaptation to disturbances, and extension beyond dyadic to multi-person scenarios.
  arXiv  Detail & Related papers  (2025-12-22T18:59:50Z)
• A Decoupled Spatio-Temporal Framework for Skeleton-based Action Segmentation [89.86345494602642]
  Existing methods are limited in weak-temporal modeling capability. We propose a Decoupled Scoupled Framework (DeST) to address the issues. DeST significantly outperforms current state-of-the-art methods with less computational complexity.
  arXiv  Detail & Related papers  (2023-12-10T09:11:39Z)
• Contact-Aware Retargeting of Skinned Motion [49.71236739408685]
  This paper introduces a motion estimation method that preserves self-contacts and prevents interpenetration. The method identifies self-contacts and ground contacts in the input motion, and optimize the motion to apply to the output skeleton. In experiments, our results quantitatively outperform previous methods and we conduct a user study where our retargeted motions are rated as higher-quality than those produced by recent works.
  arXiv  Detail & Related papers  (2021-09-15T17:05:02Z)
• Fast Gravitational Approach for Rigid Point Set Registration with Ordinary Differential Equations [79.71184760864507]
  This article introduces a new physics-based method for rigid point set alignment called Fast Gravitational Approach (FGA) In FGA, the source and target point sets are interpreted as rigid particle swarms with masses interacting in a globally multiply-linked manner while moving in a simulated gravitational force field. We show that the new method class has characteristics not found in previous alignment methods.
  arXiv  Detail & Related papers  (2020-09-28T15:05:39Z)
• ContactNets: Learning Discontinuous Contact Dynamics with Smooth, Implicit Representations [4.8986598953553555]
  Our method learns parameterizations of inter-body signed distance and contact-frame Jacobians. Our method can predict realistic impact, non-penetration, and stiction when trained on 60 seconds of real-world data.
  arXiv  Detail & Related papers  (2020-09-23T14:51:08Z)
• First Steps: Latent-Space Control with Semantic Constraints for Quadruped Locomotion [73.37945453998134]
  Traditional approaches to quadruped control employ simplified, hand-derived models. This significantly reduces the capability of the robot since its effective kinematic range is curtailed. In this work, these challenges are addressed by framing quadruped control as optimisation in a structured latent space. A deep generative model captures a statistical representation of feasible joint configurations, whilst complex dynamic and terminal constraints are expressed via high-level, semantic indicators. We validate the feasibility of locomotion trajectories optimised using our approach both in simulation and on a real-worldmal quadruped.
  arXiv  Detail & Related papers  (2020-07-03T07:04:18Z)
• Euclideanizing Flows: Diffeomorphic Reduction for Learning Stable Dynamical Systems [74.80320120264459]
  We present an approach to learn such motions from a limited number of human demonstrations. The complex motions are encoded as rollouts of a stable dynamical system. The efficacy of this approach is demonstrated through validation on an established benchmark as well demonstrations collected on a real-world robotic system.
  arXiv  Detail & Related papers  (2020-05-27T03:51:57Z)

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.