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3d-boundingbox

PyTorch implementation for 3D Bounding Box Estimation Using Deep Learning and Geometry

3d_cnn_tensorflow

KITTI data processing and 3D CNN for Vehicle Detection

3d_navigation

Global and local path planner plugins for ROS move_base which move the robot in 2D (x,y,angle) but avoid collisions using full 3D data (robot meshes and environment octomap).

3dpatrolling

3D Multi-Robot Patrolling with a Two-Level Coordination Strategy

agv

a simple agv

apollo

An open autonomous driving platform

apollo_perception_ros

Object detection / tracking / fusion based on Apollo r3.0.0 perception module in ROS

approxmvbb

Fast algorithms to compute an approximation of the minimal volume oriented bounding box of a point cloud in 3D.

ar_track_alvar

MOVED TO https://github.com/ros-perception/ar_track_alvar

aruco_ros

Software package and ROS wrappers of the Aruco Augmented Reality marker detector library

augmentedunreality

Augmented reality for Unreal Engine 4

autonomous-drifting

Autonomous Drifting using Reinforcement Learning

autoware

Open-source software for self-driving vehicles

autoware_ros

autoware 源码注释解析，会进行一些顺手的代码修改

aws-robomaker-sample-application-deepracer

Use AWS RoboMaker and demonstrate running a simulation which trains a reinforcement learning (RL) model to drive a car around a track

blam

boost

The Boost C++ Libraries

boost_opencv

A cascade classifier with OpenCV

box_detection_with_realsense

Detection of a electrical panel door using a Intel Realsense camera and Opencv and SciKit learn.

buildvpn

图文教程搭建一个vpn翻墙

calibration_camera_lidar

从autoware分离出来的相机雷达联合标定ros包

camera-lidar-joint-calibration

A sample way to jointly calibrate camera and lidar

car_geometric_planner

Use Reeds-Shepp and Dubin curves for path generation for car model

carnd-capstone

This is the final project of the Udacity Self-Driving Car Engineer Nanodegree program. In this project, I designed the most modules and integrate them all together as an autonomous vehicle system in ROS framework to enable our car Carla drive around the test track in Simulator. Carla will load the base waypoints from the simulator and adapts the desired velocity of waypoints according to the traffic light color detected by camera. Then it will interpret all the information to commands of throttle, braking and steering to realize the lateral and longitudinal control through the Drive-By-Wire module. I implemented the modules/nodes waypoint_updater, twist_controller and traffic light detector in Python on my own and adapts the waypoint_follower from [Autoware](https://github.com/autowarefoundation/autoware), which is written in C++. I used transfer learning with Keras API to detect the traffic light color. I retrain the VGG16 Model twice on my small simulator dataset and get a fine result.

cartographer

Cartographer is a system that provides real-time simultaneous localization and mapping (SLAM) in 2D and 3D across multiple platforms and sensor configurations.

centernet

Object detection, 3D detection, and pose estimation using center point detection:

cloud_to_map

Algorithm that converts point cloud data into an occupancy grid

cornernet-lite

cpfl-autoware

clone CPFL/Autoware

cppad

A C++ Algorithmic Differentiation Package: Home Page