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Best practices, conventions, and tricks for ROS
Multi-Modal Sensor Fusion and Object Tracking for Autonomous Racing
The C++ Core Guidelines are a set of tried-and-true guidelines, rules, and best practices about coding in C++
The official repository of the ICCV2023 paper "Neural Video Depth Stabilizer" (NVDS).
This is an open source Kalman filter C++ library based on Eigen3 library for matrix operations. The library has generic template based classes for most of Kalman filter variants including: (1) Kalm…
3D LiDAR Object Detection & Tracking using Euclidean Clustering, RANSAC, & Hungarian Algorithm
This package is used to calculate the translation and rotation matrix between camera and laser coordinate, and then fuse the point cloud with image color.
A ROS 2 package to transform and combine multiple PointCloud2 topics.
VPGNet: Vanishing Point Guided Network for Lane and Road Marking Detection and Recognition (ICCV 2017)
Official implementation of our ECCV paper "StretchBEV: Stretching Future Instance Prediction Spatially and Temporally"
A list of robotics companies using the Robot Operating System (ROS and ROS 2).
An Extended Kalman Filter that tracks a bicycle's position and velocity using LiDAR and radar measurements, for the Udacity Self-Driving Car Engineer Nanodegree.
Robot obstacle avoidance with reinforcement learning
Light-weight camera LiDAR calibration package for ROS using OpenCV and PCL (PnP + LM optimization)
Calibrate the extrinsic parameters between Livox LiDAR and camera
This repository is used for automatic calibration between high resolution LiDAR and camera in targetless scenes.
Real-time object detection with ROS, based on YOLOv5 and PyTorch (基于 YOLOv5的ROS实时对象检测)
Mobile Sensing and Robotics Course - 2020/21 By Prof. C. Stachniss
A complete ROS interface for running YOLOv5 inference
Solving the Traveling Salesman Problem using Self-Organizing Maps
Behavior Trees Library in C++. Batteries included.
My project and task solutions for Udacity's Self-driving Car Engineer Nanodegree
This is another attempt using Frenet Frame OTG for the Udacity ND path planning project (dynamic street scenarios)
My solution to the Udacity Self-Driving Car Engineer Nanodegree Path Planning Project.
My solution for udacity path planning project. This makes the car drive > 20 miles without collision without constraint violation