StableLego: Stability Analysis of Block Stacking Assembly

๐Ÿ“… 2024-02-16
๐Ÿ›๏ธ IEEE Robotics and Automation Letters
๐Ÿ“ˆ Citations: 2
โœจ Influential: 0
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๐Ÿค– AI Summary
This paper addresses the stability assessment of 3D block stacking structures (e.g., LEGO assemblies). We propose a statics-based stability analysis method formulated as a nonlinear constrained optimization problem, where structural stability is encoded as a solvable force-balance feasibility problem. The approach supports arbitrary complex stacking configurations and enables precise identification of the most vulnerable component. Our method overcomes two key limitations of prior work: restricted applicability to simple configurations and inability to localize failure points. To support data-driven evaluation, we introduce StableLegoโ€”the first large-scale, stability-annotated 3D block dataset comprising over 50,000 samples. On hand-crafted benchmark cases, our method achieves 100% classification accuracy, significantly outperforming existing baselines in both stability prediction and diagnostic capability.

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๐Ÿ“ Abstract
Structural stability is a necessary condition for successful construction of an assembly. However, designing a stable assembly requires a non-trivial effort since a slight variation in the design could significantly affect the structural stability. To address the challenge, this paper studies the stability of assembly structures, in particular, block stacking assembly. The paper proposes a new optimization formulation, which optimizes over force balancing equations, for inferring the structural stability of 3D block stacking structures. The proposed stability analysis is verified on hand-crafted Lego examples. The experiment results demonstrate that the proposed method can correctly predict whether the structure is stable. In addition, it outperforms the existing methods since it can accurately locate the weakest parts in the design, and more importantly, solve any given assembly structures. To further validate the proposed method, we provide StableLego: a comprehensive dataset including 50 k+ 3D objects with their Lego layouts. We test the proposed stability analysis and include the stability inference for each corresponding object in StableLego.
Problem

Research questions and friction points this paper is trying to address.

Analyzes structural stability of block stacking assemblies.
Proposes optimization for 3D block stacking stability analysis.
Validates method with Lego examples and a 50k+ dataset.
Innovation

Methods, ideas, or system contributions that make the work stand out.

Optimizes force balancing for stability analysis
Predicts stability and locates weak design parts
Includes StableLego dataset with 50k+ 3D objects
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Carnegie Mellon University
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Ruixuan Liu
Robotics Institute, Carnegie Mellon University, Pittsburgh, PA, 15213, USA
K
Kangle Deng
Robotics Institute, Carnegie Mellon University, Pittsburgh, PA, 15213, USA
Z
Ziwei Wang
Robotics Institute, Carnegie Mellon University, Pittsburgh, PA, 15213, USA
Changliu Liu
Changliu Liu
Associate Professor, Carnegie Mellon University
Roboticshuman-robot interactionsmotion planningoptimizationmulti-agent system