{"categories":[{"label":"Scientific/Engineering","url":"https://skillfed.io/packages/category/scientific-engineering/6"}],"enrichment":{"capability":"Coal provides collision detection, distance computation, and contact analysis for 3D geometric objects, with Python bindings for prototyping and integration into robotics frameworks.","skillfed_tags":["robotics","collision-detection","geometry"],"use_cases":["Motion planning for humanoid robots: check collisions between planned trajectories and obstacles or the robot itself.","Physics simulation: detect contacts and compute contact patches for constraint-based rigid body dynamics.","Grasp planning: compute distances and contact points between gripper and object geometries.","Path validation: validate collision-free paths in high-dimensional configuration spaces during planning.","Proximity queries: compute lower bounds on distances between objects for safety margins in real-time control."],"what_it_does":"Coal is a collision detection and distance computation library for 3D rigid bodies, forked and substantially rewritten from the Flexible Collision Library (FCL) since 2015 and renamed in 2024. It implements optimized GJK and EPA algorithms for narrow-phase collision detection, supports safety margins, computes contact points and patches, and handles a wide range of geometries including primitives (boxes, spheres, capsules, ellipsoids, cones), convex meshes, bounding volume hierarchies, height fields, and octrees.\n\nThe library is used in robotics frameworks like Pinocchio, the Humanoid Path Planner, and the Simple simulator. It provides Python bindings for prototyping and integration, making it accessible to researchers and engineers who need fast, reliable collision queries without implementing low-level geometric algorithms. The package requires six compiled dependencies (cmeel, cmeel-assimp, cmeel-boost, cmeel-octomap, cmeel-qhull, eigenpy) and is actively maintained with wheels for modern Python versions on macOS and Linux.","worth_installing":"Yes, if you need collision detection and distance computation for robotics or 3D geometric applications. Coal offers state-of-the-art GJK/EPA performance, is actively maintained, has no known vulnerabilities, and integrates well with established robotics frameworks. The medium install friction (compiled dependencies) is manageable via conda. Not necessary if you only need basic bounding-box overlap checks or are already embedded in a framework that provides collision detection."},"id":"coal-library","links":{"html":"https://skillfed.io/packages/coal-library","md":"https://skillfed.io/packages/coal-library.md","pypi":"https://pypi.org/project/coal-library/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2025-02-12","license_spdx":"BSD-3-Clause","license_treatment":"permissive","name":"coal-library","python_support":"supports_current","summary":"An extension of the Flexible Collision Library"},"popularity":{"monthly_downloads":180243,"position":10148,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"3.0.1"}