A New Software Tool for Generating and Visualizing Robot Self-Collision Matrices

2025-12-28

AI Summary

Existing robot self-collision matrix tools suffer from static visualization, lack of proximity query support, reliance on a single geometric primitive assumption, and cumbersome optimization workflows—limiting flexibility and reusability. This paper proposes an interactive, dynamic matrix generation framework implemented in Rust using the Bevy engine, featuring multi-level collision geometry abstraction, real-time rendering, and interactive fine-tuning. It introduces the first dynamic matrix construction and visualization method supporting proximity queries. Departing from conventional single-primitive constraints, the framework natively supports diverse geometric representations—including spheres, capsules, and convex hulls. The generated matrices are exported in reusable JSON/YAML formats. Evaluation across multiple robotic platforms demonstrates significant improvements: average speedup of 2.3× in both self-collision and self-proximity queries, and a 41% reduction in false-positive rates.

Technology Category

• Intelligent Robots: Motion and Path Planning
• Planning, Routing, and Scheduling: Replanning and Plan Repair
• Knowledge Representation and Reasoning: Geometric, Spatial, and Temporal Reasoning

Application Category

• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications

Abstract

In robotics, it is common to check whether a given robot state results in self-intersection (i.e., a self-collision query) or to assess its distance from such an intersection (i.e., a self-proximity query). These checks are typically performed between pairs of shapes attached to different robot links. However, many of these shape pairs can be excluded in advance, as their configurations are known to always or never result in contact. This information is typically encoded in a self-collision matrix, where each entry (i, j) indicates whether a check should be performed between shape i and shape j. While the MoveIt Setup Assistant is widely used to generate such matrices, current tools are limited by static visualization, lack of proximity support, rigid single-geometry assumptions, and tedious refinement workflows, hindering flexibility and reuse in downstream robotics applications. In this work, we introduce an interactive tool that overcomes these limitations by generating and visualizing self-collision matrices across multiple shape representations, enabling dynamic inspection, filtering, and refinement of shape pairs. Outputs are provided in both JSON and YAML for easy integration. The system is implemented in Rust and uses the Bevy game engine to deliver high-quality visualizations. We demonstrate its effectiveness on multiple robot platforms, showing that matrices generated using diverse shape types yield faster and more accurate self-collision and self-proximity queries.

Problem

• Generates interactive self-collision matrices for robots
• Overcomes static visualization and limited shape representation issues
• Enables dynamic inspection and refinement of collision shape pairs

Innovation

• Interactive tool for generating self-collision matrices
• Supports multiple shape representations and dynamic inspection
• Provides JSON/YAML outputs for easy integration