Is Linear Feedback on Smoothed Dynamics Sufficient for Stabilizing Contact-Rich Plans?

TL;DR

This paper investigates whether linear feedback controllers based on smoothed contact dynamics are sufficient for stabilizing complex contact-rich manipulation plans, through extensive empirical analysis on robotic manipulation tasks.

Contribution

It provides a detailed analysis of linear controller synthesis using contact smoothing and introduces baselines for open-loop and feedback control in contact-rich manipulation.

Findings

LQR often insufficient for stabilization in contact-rich tasks

Contact smoothing enables effective open-loop planning

Empirical validation on over 300 trajectories

Abstract

Designing planners and controllers for contact-rich manipulation is extremely challenging as contact violates the smoothness conditions that many gradient-based controller synthesis tools assume. Contact smoothing approximates a non-smooth system with a smooth one, allowing one to use these synthesis tools more effectively. However, applying classical control synthesis methods to smoothed contact dynamics remains relatively under-explored. This paper analyzes the efficacy of linear controller synthesis using differential simulators based on contact smoothing. We introduce natural baselines for leveraging contact smoothing to compute (a) open-loop plans robust to uncertain conditions and/or dynamics, and (b) feedback gains to stabilize around open-loop plans. Using robotic bimanual whole-body manipulation as a testbed, we perform extensive empirical experiments on over 300 trajectories and analyze why LQR seems insufficient for stabilizing contact-rich plans. The video summarizing this paper and hardware experiments is found here: https://youtu.be/HLaKi6qbwQg?si=_zCAmBBD6rGSitm9.