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‎index.html

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<li><a href="publications/simple-gradients"> Gradients of the Simple simulator.</a></li>
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<li><a href="publications/parallel-clqr"> Parallelized constrained Riccati solver for real-time nonlinear MPC.</a></li>
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<li><a href="publications/loik-solver"> Low complexity differential inverse kinematics solver.</a></li>
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<li><a href="https://arxiv.org/abs/2304.06372"> Analysis of contact models in robotics.</a></li>
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<li><a href="publications/contact-models"> Analysis of contact models in robotics.</a></li>
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<li><a href="https://hal.science/hal-04438175/"> About limitations and extensions of RaiSim simulator.</a></li>
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<li><a href="publications/constrainedABA"> Constrained Articulated Body Algorithms (IEEE T-RO 2024) </a></li>
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<li><a href="https://hal.science/hal-04726386/"> A data-driven contact estimation method for wheeled-biped robots.</a></li>
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<li><a href="publications/pv-osimr"> Optimal complexity OSIM/Delassus algorithm. (IEEE RA-L 2024)</a></li>
2020
<li><a href="publications/lcaba"> Constrained Articulated Body Algorithm for Closed Loop Mechanisms.</a></li>
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<li><a href="publications/gjk-acceleration"> GJK++: Leveraging Acceleration Methods for Faster Collision Detection. (IEEE T-RO 2024)</a></li>
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</ul>
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</body>
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‎publications/contact-models/index.html

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<!DOCTYPE html>
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<html>
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<head>
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<meta charset="utf-8">
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<meta name="description"
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content="Analysis of contact models in robotics">
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<meta name="keywords" content="Contact Models, Robotics, Physics Simulation, Contact Mechanics">
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<title>Analysis of Contact Models in Robotics</title>
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More Research
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Simple Gradients
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Contact Simulation
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</a>
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<a class="navbar-item" href="https://quentinll.github.io/projects/diffsim/">
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Differentiable System Identification
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GJK++: accelerated collision detection
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Differentiable Collision Detection
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<h1 class="title is-1 publication-title">Contact Models in Robotics: a Comparative Analysis</h1>
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<div class="is-size-5 publication-authors">
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<span class="author-block">
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<a href="https://quentinll.github.io">Quentin Le Lidec</a>,</span>
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<span class="author-block">
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<a href="https://manifoldfr.github.io/">Wilson Jallet</a>,</span>
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<span class="author-block">
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<a href="https://lmontaut.github.io">Louis Montaut</a>,</span>
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<span class="author-block">
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<a href="https://www.di.ens.fr/~laptev/">Ivan Laptev</a>,</span>
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<span class="author-block">
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<a href="https://cordeliaschmid.github.io/">Cordelia Schmid</a>,</span>
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<span class="author-block">
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<a href="https://jcarpent.github.io">Justin Carpentier</a></span>
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</div>
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<div class="is-size-5 publication-authors">
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<span class="author-block">All authors are with INRIA Willow.</span>
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<span>Paper</span>
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<a href="https://arxiv.org/abs/2304.06372"
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<i class="ai ai-arxiv"></i>
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<span>arXiv</span>
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</a>
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<span class="link-block">
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<a href="https://github.com/Simple-Robotics/ContactBench"
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<i class="fab fa-github"></i>
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<span>Code</span>
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<img src="./static/images/solo_final_figure.png" alt="Contact Models Analysis" style="width:60%">
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<h2 class="title is-3">Abstract</h2>
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Physics simulation is ubiquitous in robotics. Whether in model-based approaches (e.g., trajectory optimization), or model-free algorithms (e.g., reinforcement learning), physics simulators are a central component of modern control pipelines in robotics. Over the past decades, several robotic simulators have been developed, each with dedicated contact modeling assumptions and algorithmic solutions. In this article, we survey the main contact models and the associated numerical methods commonly used in robotics for simulating advanced robot motions involving contact interactions. In particular, we recall the physical laws underlying contacts and friction (i.e., Signorini condition, Coulomb's law, and the maximum dissipation principle), and how they are transcribed in current simulators. For each physics engine, we expose their inherent physical relaxations along with their limitations due to the numerical techniques employed. Based on our study, we propose theoretically grounded quantitative criteria on which we build benchmarks assessing both the physical and computational aspects of simulation. We support our work with an open-source and efficient C++ implementation of the existing algorithmic variations. Our results demonstrate that some approximations or algorithms commonly used in robotics can severely widen the reality gap and impact target applications. We hope this work will help motivate the development of new contact models, contact solvers, and robotic simulators in general, at the root of recent progress in motion generation in robotics.
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<h2 class="title is-3">Benchmarks</h2>
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We compared various contact models and solvers. Timing statistics
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(mean and standard deviation in microseconds) for solving contact forces with warm-start (Left) and without warm-start (Right) are averaged over a full trajectory.
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<image src="./static/images/timings_ws.png" alt="Computational time with warm-start." style="width:100%"></image>
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<image src="./static/images/timings_cs.png" alt="Computational time without warm-start." style="width:100%">
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<h2 class="title is-3">Related Links</h2>
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This work heavily relies on the <a href="https://github.com/stack-of-tasks/pinocchio">Pinocchio</a> and <a href="https://github.com/coal-library/coal">Coal</a> libraries.
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<h2 class="title is-3">BibTeX</h2>
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<pre><code>@article{lelidec2024contact,
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title={Contact models in robotics: a comparative analysis},
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author={Le Lidec, Quentin and Jallet, Wilson and Montaut, Louis and Laptev, Ivan and Schmid, Cordelia and Carpentier, Justin},
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journal={IEEE Transactions on Robotics},
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year={2024},
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publisher={IEEE}
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}</code></pre>
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