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2d_lidar_undistortion

A ros package used to correct motion distortion of a 2D LIDAR. 2D激光雷达运动畸变校正

a-loam-noted

advanced_lane_detection

Advanced lane detection using computer vision

apollo

An open autonomous driving platform

apollo-11

Original Apollo 11 Guidance Computer (AGC) source code for the command and lunar modules.

ardupilot

ArduPlane, ArduCopter, ArduRover source

attention-ocr

Visual Attention based OCR

autoware

Open-source software for urban autonomous driving.

awesome-ocr

Links to awesome OCR projects

carnd-advanced-lane-lines

cartographer

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

cbsh2

Improved Heuristics for Multi-Agent Path Finding with Conflict-Based Search

cpp_primer_answers

《C++ Primer》第五版中文版习题答案

ctpn

Detecting Text in Natural Image with Connectionist Text Proposal Network

ctw-baseline

Baseline methods for [CTW dataset](https://ctwdataset.github.io/)

darknet

Convolutional Neural Networks

deepgtav

A plugin for GTAV that transforms it into a vision-based self-driving car research environment.

diaryofliuii

我的日记

dynamic_robot_localization

Dynamic Robot Localization

easy_mcl

ROS package that runs a simplified grid-based MCL.

ethzasl_icp_mapping

3D mapping tools for robotic applications

exploration

firmware

PX4 Pro Autopilot Software

fuse

The fuse stack provides a general architecture for performing sensor fusion live on a robot. Some possible applications include state estimation, localization, mapping, and calibration.

grid_map

Universal grid map library for mobile robotic mapping

hdl_graph_slam

3D LIDAR-based Graph SLAM

houseexpo

HouseExpo: A Large-scale 2D Indoor Layout Dataset

humanoid_navigation

ROS stack with footstep planning and localization for humanoid robots: http://wiki.ros.org/humanoid_navigation

jqtools

基于Qt开发的小工具包

kalman-and-bayesian-filters-in-python

Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filters, and more. All exercises include solutions.