English

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

Robotics 2026-02-05 v1

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.

Keywords

Cite

@article{arxiv.2602.04522,
  title  = {A Unified Complementarity-based Approach for Rigid-Body Manipulation and Motion Prediction},
  author = {Bingkun Huang and Xin Ma and Nilanjan Chakraborty and Riddhiman Laha},
  journal= {arXiv preprint arXiv:2602.04522},
  year   = {2026}
}

Comments

18 pages, 7 figures

R2 v1 2026-07-01T09:35:52.679Z