文件列表:

CMakeLists.txt (616, 2019-03-26)
LICENSE (1075, 2019-03-26)
Project_Rubric_Unscented_Kalman_Filter.pdf (253400, 2019-03-26)
cmakepatch.txt (1102, 2019-03-26)
install-mac.sh (512, 2019-03-26)
install-ubuntu.sh (326, 2019-03-26)
set_git.sh (673, 2019-03-26)
src/ (0, 2019-03-26)
src/Eigen/ (0, 2019-03-26)
src/Eigen/Array (304, 2019-03-26)
src/Eigen/CMakeLists.txt (607, 2019-03-26)
src/Eigen/Cholesky (775, 2019-03-26)
src/Eigen/CholmodSupport (1670, 2019-03-26)
src/Eigen/Core (12826, 2019-03-26)
src/Eigen/Dense (122, 2019-03-26)
src/Eigen/Eigen (37, 2019-03-26)
src/Eigen/Eigen2Support (3295, 2019-03-26)
src/Eigen/Eigenvalues (1394, 2019-03-26)
src/Eigen/Geometry (1605, 2019-03-26)
src/Eigen/Householder (580, 2019-03-26)
src/Eigen/IterativeLinearSolvers (1594, 2019-03-26)
src/Eigen/Jacobi (645, 2019-03-26)
src/Eigen/LU (983, 2019-03-26)
src/Eigen/LeastSquares (712, 2019-03-26)
src/Eigen/MetisSupport (697, 2019-03-26)
src/Eigen/OrderingMethods (2189, 2019-03-26)
src/Eigen/PaStiXSupport (1467, 2019-03-26)
src/Eigen/PardisoSupport (864, 2019-03-26)
src/Eigen/QR (926, 2019-03-26)
src/Eigen/QtAlignedMalloc (637, 2019-03-26)
src/Eigen/SPQRSupport (930, 2019-03-26)
src/Eigen/SVD (858, 2019-03-26)
src/Eigen/Sparse (594, 2019-03-26)
src/Eigen/SparseCholesky (1433, 2019-03-26)
src/Eigen/SparseCore (1835, 2019-03-26)
src/Eigen/SparseLU (1776, 2019-03-26)
src/Eigen/SparseQR (991, 2019-03-26)
src/Eigen/StdDeque (749, 2019-03-26)
src/Eigen/StdList (682, 2019-03-26)
... ...

# Unscented Kalman Filter Project Starter Code Self-Driving Car Engineer Nanodegree Program In this project utilize an Unscented Kalman Filter to estimate the state of a moving object of interest with noisy lidar and radar measurements. Passing the project requires obtaining RMSE values that are lower that the tolerance outlined in the project rubric. This project involves the Term 2 Simulator which can be downloaded [here](https://github.com/udacity/self-driving-car-sim/releases). This repository includes two files that can be used to set up and intall [uWebSocketIO](https://github.com/uWebSockets/uWebSockets) for either Linux or Mac systems. For windows you can use either Docker, VMware, or even [Windows 10 Bash on Ubuntu](https://www.howtogeek.com/249966/how-to-install-and-use-the-linux-bash-shell-on-windows-10/) to install uWebSocketIO. Please see the uWebSocketIO Starter Guide page in the classroom within the EKF Project lesson for the required version and installation scripts. Once the install for uWebSocketIO is complete, the main program can be built and ran by doing the following from the project top directory. 1. mkdir build 2. cd build 3. cmake .. 4. make 5. ./UnscentedKF Tips for setting up your environment can be found in the classroom lesson for the EKF project. Note that the programs that need to be written to accomplish the project are src/ukf.cpp, src/ukf.h, tools.cpp, and tools.h The program main.cpp has already been filled out, but feel free to modify it. Here is the main protocol that main.cpp uses for uWebSocketIO in communicating with the simulator. INPUT: values provided by the simulator to the c++ program ["sensor_measurement"] => the measurment that the simulator observed (either lidar or radar) OUTPUT: values provided by the c++ program to the simulator ["estimate_x"] <= kalman filter estimated position x ["estimate_y"] <= kalman filter estimated position y ["rmse_x"] ["rmse_y"] ["rmse_vx"] ["rmse_vy"] --- ## Other Important Dependencies * cmake >= 3.5 * All OSes: [click here for installation instructions](https://cmake.org/install/) * make >= 4.1 (Linux, Mac), 3.81 (Windows) * Linux: make is installed by default on most Linux distros * Mac: [install Xcode command line tools to get make](https://developer.apple.com/xcode/features/) * Windows: [Click here for installation instructions](http://gnuwin32.sourceforge.net/packages/make.htm) * gcc/g++ >= 5.4 * Linux: gcc / g++ is installed by default on most Linux distros * Mac: same deal as make - [install Xcode command line tools](https://developer.apple.com/xcode/features/) * Windows: recommend using [MinGW](http://www.mingw.org/) ## Basic Build Instructions 1. Clone this repo. 2. Make a build directory: `mkdir build && cd build` 3. Compile: `cmake .. && make` 4. Run it: `./UnscentedKF` ## 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](https://google.github.io/styleguide/cppguide.html) 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](https://github.com/udacity/CarND-Mercedes-SF-Utilities) 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 in the classroom for instructions and the project rubric. ## How to write a README A well written README file can enhance your project and portfolio. Develop your abilities to create professional README files by completing [this free course](https://www.udacity.com/course/writing-readmes--ud777).

近期下载者：

相关文件：

评论：[我要评论] [举报此文件]

收藏者：