Skill ディレクトリ

AI Agent のための再利用可能な Skill を見つける。

タスクで実際の GitHub Skill を検索し、利用前に Stars、Trust、監査、カテゴリ、インストール経路を確認できます。

すべての推奨は、リポジトリ、監査、インストール経路に明確につながっています。

[ICRA 2025 Best Paper] MAC-VO: Metrics-aware Covariance for Learning-based Stereo Visual Odometry

921
Stars
70/100
信頼
カテゴリ: robotics-iot監査

[ICRA 2022] An opensource framework for cooperative detection. Official implementation for OPV2V.

824
Stars
62/100
信頼
カテゴリ: robotics-iot監査

ICRA 2019 "Self-supervised Sparse-to-Dense: Self-supervised Depth Completion from LiDAR and Monocular Camera"

653
Stars
65/100
信頼
カテゴリ: robotics-iot監査

🌟 SHINE-Mapping: Large-Scale 3D Mapping Using Sparse Hierarchical Implicit Neural Representations (ICRA 2023)

487
Stars
62/100
信頼
カテゴリ: robotics-iot監査

Estimation of 2D odometry based on planar laser scans. Useful for mobile robots with innacurate base odometry. For full description of the algorithm, please refer to: Planar Odometry from a Radial Laser Scanner. A Range Flow-based Approach. ICRA 2016 Available at: http://mapir.isa.uma.es/mapirwebsite/index.php/mapir-downloads/papers/217

474
Stars
61/100
信頼
カテゴリ: robotics-iot監査

[ICRA'23] The official Implementation of "Structure PLP-SLAM: Efficient Sparse Mapping and Localization using Point, Line and Plane for Monocular, RGB-D and Stereo Cameras"

470
Stars
63/100
信頼
カテゴリ: robotics-iot監査

ICRA 2018 "Sparse-to-Dense: Depth Prediction from Sparse Depth Samples and a Single Image" (Torch Implementation)

444
Stars
59/100
信頼
カテゴリ: robotics-iot監査

(ICRA 2019) Visual-Odometric On-SE(2) Localization and Mapping

410
Stars
61/100
信頼
カテゴリ: robotics-iot監査

SSL_SLAM2: Lightweight 3-D Localization and Mapping for Solid-State LiDAR (mapping and localization separated) ICRA 2021

367
Stars
63/100
信頼
カテゴリ: robotics-iot監査

[ICRA 2022] CaTGrasp: Learning Category-Level Task-Relevant Grasping in Clutter from Simulation

340
Stars
63/100
信頼
カテゴリ: robotics-iot監査

FastFlowNet: A Lightweight Network for Fast Optical Flow Estimation (ICRA 2021)

328
Stars
59/100
信頼
カテゴリ: robotics-iot監査

Pytorch code for ICRA'22 paper: "Single-Shot Multi-Object 3D Shape Reconstruction and Categorical 6D Pose and Size Estimation"

326
Stars
59/100
信頼
カテゴリ: robotics-iot監査