byarpitg1304· 10 skills
Comprehensive best practices for robot perception systems covering cameras, LiDARs, depth sensors, IMUs, and multi-sensor setups. Use this skill when working with RGB image processing, depth maps, point clouds, sensor calibration (intrinsic, extrinsic, hand-eye), object detection, semantic segmentation, 3D reconstruction, visual servoing, or perception pipeline optimization. Trigger whenever the user mentions OpenCV, Open3D, PCL, RealSense, ZED, OAK-D, camera calibration, AprilTags, ArUco markers, stereo vision, RGBD, point cloud filtering, ICP registration, coordinate transforms, camera intrinsics, distortion correction, image undistortion, sensor streaming, frame synchronization, or any computer vision task in a robotics context. Also covers multi-camera rigs, time synchronization across sensors, perception latency budgets, and production deployment of perception pipelines.
$npx -y skills add arpitg1304/robotics-agent-skills --skill robot-perceptionInstalls into the current project.
Run `npx skills use "https://github.com/arpitg1304/robotics-agent-skills" --skill "arpitg1304/robotics-agent-skills/robot-perception"` and follow the generated skill instructions now. Read its complete output, redirecting it to a temporary file first if necessary. Resolve relative paths from the supporting-files directory it provides.
Use the skills in "https://github.com/arpitg1304/robotics-agent-skills" that are relevant to the current task. Run `npx skills add "https://github.com/arpitg1304/robotics-agent-skills"` and select the relevant skills, then follow their instructions.