Robohub.org
 

Teaching robots the physics of sliding and pushing objects


by
16 June 2016



share this:

Robot learns to push object and identifies patch friction model. Source: YouTube

Robot learns to push object and identifies patch friction model. Source: YouTube



The Manipulation Lab at the CMU Robotics Institute proposes a computational model that relates an applied robot action to the resultant object motion. Their research won the Best Conference Paper Award at ICRA 2016.

Understanding the mechanics of manipulation is essential for robots to autonomously interact with the physical world. One of the common manipulation scenarios involves pushing objects in a plane subject to dry friction. We propose a planar friction (force-motion) model that relates an applied robot action to the resultant object motion.

The robot randomly pokes the object of known shape with a point finger to collect force-motion data. We then optimize a convex polynomial friction representation with physics-based constraints. Based on the representation, we demonstrate applications of stable pushing and dynamic sliding simulation.

The robot randomly pokes the object of known shape with a point finger to collect force-motion data. We then optimize a convex polynomial friction representation with physics-based constraints. Based on the representation, we demonstrate applications of stable pushing and dynamic sliding simulation.

The difficulty lies in that the contact between the object and supporting surface is an area-to-area contact with unknown pressure distribution. We don’t know which part of the area is supporting how much weight nor do we know the coefficient of friction. This makes object motion hard to predict. The key observation is the space of generalized friction force forms a convex set based on the principle of maximum dissipation (a generalized Coulomb’s friction law) [1]. The boundary of such set is termed as limit surface [2]. The geometry of such surface, albeit convex, can be complicated. Fortunately, we have shown that level sets of sum of squares convex polynomials turn out to be good geometric approximations. Another advantage is the model is very data-efficient, i.e., model identification only requires few force and velocity data collected by the robot pushing the object with a point finger. There are some additional nice provable properties of the models, and with these properties, we are able to perform applications including stable pushing and free sliding dynamics simulation.

[1] J. J. Moreau, “Unilateral contact and dry friction in finite freedom dynamics,” in Nonsmooth Mechanics and Applications, pp. 1–82, Springer, 1988.

[2] S. Goyal, A. Ruina, and J. Papadopoulos, “Planar sliding with dry friction. Part 1. Limit surface and moment function,” Wear, vol. 143, pp. 307–330, 1991.

Paper: A Convex Polynomial Force-Motion Model for Planar Sliding: Identification and Application: Jiaji Zhou, Robert Paolini, James Bagnell, Matthew T. Mason

Read the award winning paper here



tags: ,


Jiaji Zhou is a PhD student in the Robotics Institute of Carnegie Mellon University.
Jiaji Zhou is a PhD student in the Robotics Institute of Carnegie Mellon University.

            AUAI is supported by:



Subscribe to Robohub newsletter on substack



Related posts :

Watch the ICRA keynote and plenary talks

  16 Sep 2026
If you missed the conference you can catch up on IEEE TV.

Building and programming autonomous robots at the York Micromaze Hackathon

and   11 Sep 2026
From 25–27 August, UK RAS STEPS members came together for a three-day Micromaze Robot Hackathon.

Robotics roadmaps from around the world spotlight of the month: United States of America

US robotics researchers and industry are looking for a cohesive national robotics strategy.

Could robots help tackle loneliness? BBC’s Ann Droid raises questions about the future of care

  07 Sep 2026
While the series exaggerates what robots can currently do, some of the technology it depicts is already being tested.

Exploring the Moon will require rovers that can think for themselves – an upcoming NASA mission will test whether they can

  04 Sep 2026
NASA is planning to send three small rovers to the Moon to autonomously compute how to best explore a patch of ground.

Surviving the paper deluge: Notes from an ICRA panel on publishing, LLMs, and the future of peer review

Experts discuss peer-review challenges and possibilities for reshaping the process.

When expressive humanoid robots are awkward, people become wary – new brain study

  31 Aug 2026
People become more suspicious of a humanoid robot that makes errors, especially when the robot is an expressive conversation partner.



AUAI is supported by:







Subscribe to Robohub newsletter on substack




 















©2026.05 - Association for the Understanding of Artificial Intelligence