Computer Vision Skill

SkillDev tools

Specialized skill for robot vision including feature detection, tracking, and camera calibration

Instructions available. Your AI can read the instructions. Execution depends on the setup they require.

Add ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.

Then ask your AI: use the Computer Vision Skill skill

What this skill tells your AI

The instructions your AI receives, as published by a5c-ai/babysitter in library/specializations/robotics-simulation/skills/computer-vision/SKILL.md and read by ahel’s review.

Overview

Expert skill for robot vision applications including camera calibration, feature detection and tracking, stereo vision, and visual servoing.

Capabilities

  • Implement camera intrinsic calibration (pinhole, fisheye)
  • Configure stereo camera calibration and rectification
  • Set up camera-LiDAR extrinsic calibration
  • Implement feature detection (ORB, SIFT, SURF, SuperPoint)
  • Configure optical flow tracking (Lucas-Kanade, Farneback)
  • Implement depth estimation from stereo
  • Set up visual servoing pipelines
  • Configure image undistortion and rectification
  • Implement ArUco/AprilTag marker detection
  • Set up hand-eye calibration

Target Processes

  • robot-calibration.js
  • visual-slam-implementation.js
  • object-detection-pipeline.js
  • digital-twin-development.js

Dependencies

  • OpenCV
  • cv_bridge
  • image_geometry
  • camera_calibration

Usage Context

This skill is invoked when processes require camera calibration, feature detection, visual tracking, or image processing for robot vision applications.

Output Artifacts

  • Camera calibration files (YAML)
  • Stereo calibration parameters
  • Feature detection configurations
  • Visual servoing controllers
  • Image processing pipelines
  • Marker detection configurations

Signals

GitHub stars
2k
Forks
112
Last commit
Sep 2026
Advanced
Item type
skill
Key
computer-vision-skill
Source
github.com/a5c-ai/babysitter