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Point cloud processing

Skill a5c-ai/babysitter/library/specializations/robotics-simulation/skills/point-cloud-processing

Specialized skill for 3D point cloud processing and analysis using PCL and Open3DFrom its SKILL.md

Install
npx -y skills add a5c-ai/babysitter --skill point-cloud-processing

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

SKILL.md

1.7 KB, 287 tokens by cl100k_base, as published. Nobody here has run it

Point Cloud Processing Skill

Overview

Expert skill for processing, analyzing, and manipulating 3D point cloud data using PCL (Point Cloud Library) and Open3D.

Capabilities

  • Implement point cloud filtering (voxel grid, statistical outlier, passthrough)
  • Configure ground plane segmentation (RANSAC, SAC)
  • Implement clustering algorithms (Euclidean, DBSCAN)
  • Set up surface reconstruction (Poisson, ball pivoting)
  • Configure feature extraction (FPFH, SHOT, PFH)
  • Implement registration algorithms (ICP, NDT, GICP)
  • Set up octree and KD-tree spatial indexing
  • Process organized and unorganized point clouds
  • Implement point cloud downsampling strategies
  • Configure LiDAR-camera fusion

Target Processes

  • lidar-mapping-localization.js
  • object-detection-pipeline.js
  • sensor-fusion-framework.js
  • synthetic-data-pipeline.js

Dependencies

  • PCL (Point Cloud Library)
  • Open3D
  • pcl_ros
  • laser_geometry

Usage Context

This skill is invoked when processes require 3D point cloud manipulation, LiDAR data processing, surface reconstruction, or point cloud registration tasks.

Output Artifacts

  • Point cloud processing pipelines
  • Filter chain configurations
  • Registration parameters
  • Segmentation algorithms
  • Feature extraction configurations
  • Fusion pipeline code

What ships with it: 1 file

695 B alongside SKILL.md

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