SensorFusion-UKF

激光雷达和毫米波雷达数据融合基于无迹卡尔曼滤波算法c++工程项目

基于无迹卡尔曼滤波，改成ROS协议下的

#你需要配置ROS环境以及C++编译

Unscented Kalman Filter Project Starter Code

Self-Driving Car Engineer Nanodegree Program

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Dependencies

• cmake >= v3.5

• make >= v4.1

• gcc/g++ >= v5.4

Basic Build Instructions

1. Clone this repo.

2. Make a build directory: mkdir build && cd build

3. Compile: cmake .. && make

4. Run it: ./UnscentedKF path/to/input.txt path/to/output.txt. You can find

   some sample inputs in 'data/'.

   • eg. ./UnscentedKF ../data/sample-laser-radar-measurement-data-1.txt output.txt

Editor Settings

We've purposefully kept editor configuration files out of this repo in order to

keep it as simple and environment agnostic as possible. However, we recommend

using the following settings:

• indent using spaces

• set tab width to 2 spaces (keeps the matrices in source code aligned)

Code Style

Please stick to Google's C++ style guide as much as possible.

Generating Additional Data

This is optional!

If you'd like to generate your own radar and lidar data, see the

utilities repo for

Matlab scripts that can generate additional data.

Project Instructions and Rubric

This information is only accessible by people who are already enrolled in Term 2

of CarND. If you are enrolled, see the project page

for instructions and the project rubric.