AI Agent Skills

LiLi-OM is a tightly-coupled, keyframe-based LiDAR-inertial odometry and mapping system for both solid-state-LiDAR and conventional LiDARs.

State of the art autonomous navigation scripts using Ai, Computer Vision, Lidar and GPS to control an arducopter based quad copter.

Robust Odometry and Mapping for Multi-LiDAR Systems with Online Extrinsic Calibration

Predict dense depth maps from sparse and noisy LiDAR frames guided by RGB images. (Ranked 1st place on KITTI) [MVA 2019]

Source code for the article "GroundGrid: LiDAR Point Cloud Ground Segmentation and Terrain Estimation"

LV-DOT: LiDAR-Visual Dynamic Obstacle Detection and Tracking (C++/Python/ROS)

DLL: Direct Lidar Localization

Robust Lidar Odometry System

[RA-L 2024] In Defense of LiDAR-Only Odometry Using an Effective Continuous-Time Trajectory

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

Real-time LIDAR-based Urban Road and Sidewalk detection for Autonomous Vehicles 🚗

Tightly-coupled Direct LiDAR-Inertial Odometry and Mapping Based on Cartographer3D.

Real-time people tracking using a 3D LIDAR

A LiDAR odometry pipeline for wheeled mobile robots

[T-ASE 25] SegNet4D: Efficient Instance-Aware 4D Semantic Segmentation for LiDAR Point Cloud

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