BrickSim: A Physics-Based Simulator for Manipulating Interlocking Brick Assemblies
- URL: http://arxiv.org/abs/2603.16853v1
- Date: Tue, 17 Mar 2026 17:56:53 GMT
- Title: BrickSim: A Physics-Based Simulator for Manipulating Interlocking Brick Assemblies
- Abstract summary: We present BrickSim, the first real-time physics-based simulator for interlocking brick assemblies.<n>On 150 real-world assemblies, BrickSim achieves 100% accuracy in static stability prediction with an average solve time of 5 ms.<n>BrickSim is open-source, and the code is available at https://github.com/intelligent-control-lab/BrickSim.
- Score: 15.809735682998303
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Interlocking brick assemblies provide a standardized yet challenging testbed for contact-rich and long-horizon robotic manipulation, but existing rigid-body simulators do not faithfully capture snap-fit mechanics. We present BrickSim, the first real-time physics-based simulator for interlocking brick assemblies. BrickSim introduces a compact force-based mechanics model for snap-fit connections and solves the resulting internal force distribution using a structured convex quadratic program. Combined with a hybrid architecture that delegates rigid-body dynamics to the underlying physics engine while handling snap-fit mechanics separately, BrickSim enables real-time, high-fidelity simulation of assembly, disassembly, and structural collapse. On 150 real-world assemblies, BrickSim achieves 100% accuracy in static stability prediction with an average solve time of 5 ms. In dynamic drop tests, it also faithfully reproduces real-world structural collapse, precisely mirroring both the occurrence of breakage and the specific breakage locations. Built on Isaac Sim, BrickSim further supports seamless integration with a wide variety of robots and existing pipelines. We demonstrate robotic construction of brick assemblies using BrickSim, highlighting its potential as a foundation for research in dexterous, long-horizon robotic manipulation. BrickSim is open-source, and the code is available at https://github.com/intelligent-control-lab/BrickSim.
Related papers
- IR-SIM: A Lightweight Skill-Native Simulator for Navigation, Learning, and Benchmarking [59.6657632820611]
IR-SIM is a skill-native navigation simulator designed for rapid scenario construction, benchmarking, and robot learning.<n> scenarios are entirely defined by YAML configuration files that specify mobile robot kinematics, geometric collision checking, LiDAR sensing, visualization, and behavior modules.<n>The experiments showcase the convenience and versatility of IR-SIM in multiple tasks.
arXiv Detail & Related papers (2026-06-07T16:55:37Z) - FLASH: Fast Learning via GPU-Accelerated Simulation for High-Fidelity Deformable Manipulation in Minutes [15.151803709340404]
FLASH is a GPU-native simulation framework for contact-rich deformable manipulation.<n>It is built on an accurate NCP-based solver that enforces strict contact and deformation constraints.
arXiv Detail & Related papers (2026-04-19T16:07:43Z) - HSImul3R: Physics-in-the-Loop Reconstruction of Simulation-Ready Human-Scene Interactions [69.43316445143408]
We present HSImul3R, a unified framework for simulation-ready 3D reconstruction of human-scene interactions.<n>Existing methods suffer from a perception-simulation gap, leading to instability in physics engines and failure in embodied AI applications.
arXiv Detail & Related papers (2026-03-16T17:58:33Z) - SORS: A Modular, High-Fidelity Simulator for Soft Robots [5.660024841218955]
Soft robots pose unique modeling challenges due to their large nonlinear deformations, material incompressibility, and contact interactions.<n>We present SORS, a versatile, high-fidelity simulator designed to handle these complexities for soft robot applications.
arXiv Detail & Related papers (2025-12-17T21:58:46Z) - Isaac Lab: A GPU-Accelerated Simulation Framework for Multi-Modal Robot Learning [72.43357471969564]
Isaac Lab combines high-fidelity GPU parallel physics, rendering, and a modular, composable architecture for designing environments and training robot policies.<n>We highlight its application to a diverse set of challenges, including whole-body control, cross-embodiment mobility, contact-rich and dexterous manipulation, and the integration of human demonstrations for skill acquisition.<n>We believe Isaac Lab's combination of advanced simulation capabilities, rich sensing, and data-center scale execution will help unlock the next generation of breakthroughs in robotics research.
arXiv Detail & Related papers (2025-11-06T21:43:02Z) - MultiCoSim: A Python-based Multi-Fidelity Co-Simulation Framework [0.4972323953932129]
MultiCoSim is a Python-based simulation framework that enables users to define, compose, and configure simulation components.<n>CPS inherently integrate hardware, software, and physical processes.<n>Existing simulation tools often rely on rigid configurations, lack automation support, and present obstacles to portability and modularity.
arXiv Detail & Related papers (2025-06-12T16:31:39Z) - Generating Physically Stable and Buildable Brick Structures from Text [63.75381708299733]
BrickGPT is the first approach for generating physically stable assembly models from text prompts.<n>We release our dataset, StableText2Brick, containing over7,000 3D textured brick structures.
arXiv Detail & Related papers (2025-05-08T17:58:18Z) - AgentDynEx: Nudging the Mechanics and Dynamics of Multi-Agent Simulations [12.224345290091435]
We present AgentDynEx, an AI system that helps set up simulations from user-specified mechanics and dynamics.<n>A technical evaluation found that nudging enables simulations to have more complex mechanics and maintain its notable dynamics compared to simulations without nudging.
arXiv Detail & Related papers (2025-04-13T17:26:35Z) - GausSim: Foreseeing Reality by Gaussian Simulator for Elastic Objects [55.02281855589641]
GausSim is a novel neural network-based simulator designed to capture the dynamic behaviors of real-world elastic objects represented through Gaussian kernels.<n>We leverage continuum mechanics and treat each kernel as a Center of Mass System (CMS) that represents continuous piece of matter.<n>In addition, GausSim incorporates explicit physics constraints, such as mass and momentum conservation, ensuring interpretable results and robust, physically plausible simulations.
arXiv Detail & Related papers (2024-12-23T18:58:17Z) - Budget-Aware Sequential Brick Assembly with Efficient Constraint Satisfaction [63.672314717599285]
We tackle the problem of sequential brick assembly with LEGO bricks to create 3D structures.
In particular, the number of assemblable structures increases exponentially as the number of bricks used increases.
We propose a new method to predict the scores of the next brick position by employing a U-shaped sparse 3D convolutional neural network.
arXiv Detail & Related papers (2022-10-03T15:35:08Z) - Break and Make: Interactive Structural Understanding Using LEGO Bricks [61.01136603613139]
We build a fully interactive 3D simulator that allows learning agents to assemble, disassemble and manipulate LEGO models.
We take a first step towards solving this problem using sequence-to-sequence models.
arXiv Detail & Related papers (2022-07-27T18:33:09Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.