技能目录

为 AI Agent 发现可复用技能。

按任务搜索真实的 GitHub 技能,并在使用前查看 Stars、信任、审计、分类和安装路径。

每个推荐都保留与其仓库、审计和安装路径的明确关联。

搜索结果: iros

英文目录

SOTA fast and robust ground segmentation using 3D point cloud (accepted in RA-L'21 w/ IROS'21)

584
Stars
71/100
信任
分类: robotics-iot审计

(IROS 2020, ECCVW 2020) Official Python Implementation for "3D Multi-Object Tracking: A Baseline and New Evaluation Metrics"

1.8K
Stars
68/100
信任
分类: ml-automation审计

[IROS 2021] BundleTrack: 6D Pose Tracking for Novel Objects without Instance or Category-Level 3D Models

686
Stars
71/100
信任
分类: robotics-iot审计

[IROS'25] Source code for "RayFronts: Open-Set Semantic Ray Frontiers for Online Scene Understanding and Exploration"

131
Stars
70/100
信任
分类: robotics-iot审计

[RAL' 25 & IROS‘ 25] MapEval: Towards Unified, Robust and Efficient SLAM Map Evaluation Framework.

473
Stars
65/100
信任
分类: robotics-iot审计

[IROS 2024] MPPI (Model Predictive Path-Integral) Controller for a Swerve Drive Robot

243
Stars
67/100
信任
分类: robotics-iot审计

[IROS 2025] A Robust Tightly-Coupled RGBD-Inertial and Legged Odometry Fusion SLAM for Dynamic Legged Robotics

139
Stars
69/100
信任
分类: robotics-iot审计

Antipodal Robotic Grasping using GR-ConvNet. IROS 2020.

657
Stars
60/100
信任
分类: robotics-iot审计

[IROS 2024] 📈 RISE: 3D Perception Makes Real-World Robot Imitation Simple and Effective

154
Stars
64/100
信任
分类: robotics-iot审计

[IROS 25] Leveraging Semantic Graphs for Efficient and Robust LiDAR SLAM

146
Stars
65/100
信任
分类: robotics-iot审计

[IROS 2020] se(3)-TrackNet: Data-driven 6D Pose Tracking by Calibrating Image Residuals in Synthetic Domains

423
Stars
59/100
信任
分类: robotics-iot审计

This is a monocular dense mapping system corresponding to IROS 2018 "Quadtree-accelerated Real-time Monocular Dense Mapping"

365
Stars
63/100
信任
分类: robotics-iot审计