How to install FCL on Ubuntu with all dependencies?

Follow the README steps: install Eigen and libccd from source, optionally Octomap for octree support, then use cmake to generate makefiles and compile. Be aware that libccd must be compiled from GitHub due to bug fixes.

FCL vs Bullet Physics for robotics simulation?

FCL focuses specifically on proximity queries (collision, distance) with flexibility for arbitrary meshes, while Bullet is a full physics engine with simulation capabilities. Choose FCL for dedicated collision detection in custom pipelines, or Bullet for integrated physics.

How to perform continuous collision detection with FCL?

Use the ContinuousCollisionRequest and ContinuousCollisionResult structures, providing goal transforms for moving objects via the continuousCollide function, as demonstrated in the README code snippets.

Does FCL work with Python?

No, FCL is a C++ library with no native Python bindings. You would need to use external wrappers or create your own, which adds complexity for Python-centric projects.

What's the performance impact of using FCL's broadphase on large meshes?

FCL's Dynamic AABB tree significantly reduces complexity from O(n²) to near O(n log n) for many objects, but initial setup and tree updates can be costly for dynamically changing scenes with thousands of triangles.

Can FCL calculate contact normals accurately?

Yes, FCL optionally returns contact points and normals for collision and continuous collision queries, though this adds computational overhead compared to binary collision results.

flexible-collision-library

NOASSERTIONC++0.7.0

A C++ library for collision detection, distance computation, and proximity queries between 3D geometric models.

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What is flexible-collision-library?

FCL (Flexible Collision Library) is a C++ library for performing proximity queries on 3D geometric models, including collision detection, distance computation, and tolerance verification. It solves the problem of efficiently determining spatial relationships between objects in applications like robotics and simulation, supporting various shapes from primitives to meshes.

Target Audience

Developers and researchers in robotics, physics simulation, computer graphics, and CAD software who need reliable and performant spatial query capabilities.

Value Proposition

Developers choose FCL for its comprehensive feature set—including continuous collision detection and broadphase acceleration—coupled with its flexibility in handling arbitrary triangle meshes without topological constraints, all through a well-documented C++ API.

Overview

Flexible Collision Library

Use Cases

Best For

Robotics applications requiring collision checking for motion planning

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Physics engines needing accurate distance computation between complex shapes

Simulation software verifying clearance tolerances between components

Computer graphics tools detecting intersections in 3D modeling

VR/AR systems performing real-time proximity queries

CAD software analyzing spatial relationships of assemblies

Not Ideal For

Projects exclusively working with 2D geometries, as FCL is designed for 3D collision detection.
Teams seeking a plug-and-play solution without managing dependencies like Eigen and libccd.
Real-time game engines requiring sub-millisecond collision queries at high frame rates, where FCL's broadphase might introduce overhead.
Environments relying on non-C++ languages (e.g., Python or JavaScript) without external bindings, due to FCL's native C++ interface.

Pros & Cons

Pros

Flexible Geometry Handling

Requires only triangle lists without special topological constraints, making it easy to integrate with arbitrary 3D models from various sources.

Comprehensive Shape Support

Handles primitives like boxes and spheres, as well as complex shapes like meshes and octrees via Octomap, covering a wide range of use cases in robotics and simulation.

Efficient Broadphase Acceleration

Uses spatial data structures like Dynamic AABB trees to avoid O(n²) complexity in multi-object scenarios, improving performance for large scenes.

Rich Query Types

Provides collision detection, distance computation, tolerance verification, and continuous collision detection, offering a complete suite for proximity analysis.

Cons

Dependency Management Overhead

Requires manual installation of Eigen and libccd, and for octree support, Octomap, which complicates the build process compared to all-in-one libraries.

C++-Only Interface

Lacks native bindings for other languages, limiting accessibility for teams using Python, Java, or web-based ecosystems without additional effort.

Complex Configuration Setup

Setting up collision managers and understanding request/result structures, as shown in the code examples, can be non-trivial for newcomers to spatial queries.

Frequently Asked Questions

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