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 :

Humanoid robots can sprint and box – but the real test is doing the laundry

  12 Oct 2026
No robot system can yet reliably handle the whole laundry process. Even folding remains a challenge.

Robot Talk Episode 165 – Robots behind the research, with Kushant Patel

  09 Oct 2026
In the latest episode of the Robot Talk podcast, Claire chatted to Kushant Patel from Brookhaven National Laboratory about robots that work in scientific facilities, such as particle accelerators.

What three days building a robot taught me

and   07 Oct 2026
The brief sounded simple: build a small autonomous robot, then make it survive increasingly difficult mazes. Simple... right? Until you actually have to build one.

Research could guide the future design of social robots

  05 Oct 2026
Giving robot companions animal-like or anime-style faces and voices could maximise their emotional appeal to users, according to new research which could help guide the growing field of social robotics.

Robot Talk Episode 164 – Accelerating robot learning, with Michelle Lu

  02 Oct 2026
In the latest episode of the Robot Talk podcast, Claire chatted to Michelle Lu from Vsim Technology about using simulation and artificial intelligence to teach robots new skills.

Robotics and automation? Informal reflections on familiar terms

IEEE experts reflect on what is meant by the term "robotics and automation".

Small, medium or large, a robotic fish maintains its swimming ability

  28 Sep 2026
Researchers at EPFL and New York University have developed a robotic fish that can be made in various sizes for studying shallow creeks to open water.


↑


AUAI is supported by:







Subscribe to Robohub newsletter on substack




 















©2026.05 - Association for the Understanding of Artificial Intelligence