Manipulation via Force Distribution at Contact

TL;DR

This paper introduces a Force-Distributed Line Contact (FDLC) model for contact-rich manipulation, demonstrating its advantages over point contact models in generating efficient, robust trajectories with lower control effort.

Contribution

The study proposes the FDLC model and a bi-level optimization framework, enhancing contact modeling accuracy and trajectory optimization in manipulation tasks.

Findings

FDLC enables force distribution along contact lines.

FDLC reduces control effort in manipulation.

FDLC improves robustness of trajectories.

Abstract

Efficient and robust trajectories play a crucial role in contact-rich manipulation, which demands accurate mod- eling of object-robot interactions. Many existing approaches rely on point contact models due to their computational effi- ciency. Simple contact models are computationally efficient but inherently limited for achieving human-like, contact-rich ma- nipulation, as they fail to capture key frictional dynamics and torque generation observed in human manipulation. This study introduces a Force-Distributed Line Contact (FDLC) model in contact-rich manipulation and compares it against conventional point contact models. A bi-level optimization framework is constructed, in which the lower-level solves an optimization problem for contact force computation, and the upper-level optimization applies iLQR for trajectory optimization. Through this framework, the limitations of point contact are demon- strated, and the benefits of the FDLC in generating efficient and robust trajectories are established. The effectiveness of the proposed approach is validated by a box rotating task, demonstrating that FDLC enables trajectories generated via non-uniform force distributions along the contact line, while requiring lower control effort and less motion of the robot.