cuvslam-onboard

cuvslam-onboard is an Embedded, IoT & robotics skill for AI agents, published by nvidia-isaac in the cuVSLAM repository on GitHub. Skillspace rates cuvslam-onboard D (66/100) and it passed the safety scan; the rating is based on static analysis only.

Build, install, and run NVIDIA cuVSLAM and PyCuVSLAM from source or wheels. Covers environment setup, dataset preparation, and running examples for all tracking modes (stereo, mono, mono-depth, stereo-inertial, multi-camera) and SLAM (mapping, localization, loop closure). Use when asked to: build cuVSLAM, install PyCuVSLAM, set up cuVSLAM environment, run cuVSLAM examples, prepare KITTI/EuRoC/TUM datasets, run visual odometry, set up live camera tracking (RealSense/ZED/OAK-D/Orbbec), run cuVSLAM in Docker, or use cuVSLAM C++ tools.

Grade
D
Quality
66 / 100
Safety
Passed
GitHub stars
1,714

Unproven: rated by static analysis only, not yet compared head-to-head.

Our two independent classifiers differ on this skill's category, so treat the placement as provisional.

This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.

View source on GitHubnvidia-isaac/cuVSLAM

Our review

Architecture
84 / 100
Maturity
Structured: ships references or scripts
Security scan
No issues found
License
Not declared. Check the repository before reusing it.
Adoption
Adopted by 0 other repositories, in 0 collections

Not checked yet

  • Not judged on the rubric yet (not a contender in its category)
  • No blind task eval yet
  • Scope (portable / vendor / repo-internal) not assessed; only the top of each category is read for scope
  • Sibling files (scripts, references) not fetched; security scan covers SKILL.md only

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