The goal of this project is to create a kalman filter to estimate the state of a moving object of interest with noisy lidar and radar measurements.

The project includes following steps:

• Completion of the project template C++ sorce code in order to build an Extended Kalman Filter (EKF) by applying the general processing flow as described in the class lessons
• Testing of the EKF code with input data generated by the Term 2 Simulator
• Visualizion of the EKF output in a Jupyter notebook adopted from the provided in the Sensor Fusion utility repo

• README.md - This file.
• src/ folder:
  • project C++ souce code files
  • CMakeLists.txt - cmake input file to generate the project Makefile. It was moved to the src folder and adopted to generate an Eclipse project - thanks to Eclipse IDE profile repo for provided instructions.
• data/ folder:
  • ekf-visualization.ipynb - an IPython notebook for the output data visualization and analysis.
  • ekf_pos_output.txt - output data file generated by the project code
  • ekf_position.png - the output image generated by the notebook

The project code was built and executed on a Linux VMware guest. The simulator was running on a Windows host with a port forwarding setup as instructed here

1. Make a build directory: mkdir build && cd build
2. Compile the code: cmake ../src/ && make (Please note that CMakeList.txt file is located in folder src/)
3. Run the code: ./ExtendedKF

The source file main.cpp was modified to store the output data records in a text file ekf_pos_output.txt in the following format: est_px est_py est_vx est_vy meas_px meas_py gt_px gt_py gt_vx gt_vy RMSE(0) RMSE(1) RMSE(2) RMSE(3)

After processing the output file in the ekf-visualization.ipynb notebook the object position estimates look as following:

The below table shows the position and velocity acccuracy of the last 10 estimates:

When executed on Linux VM, an error "Segmentation fault (core dumped)" is reported after h.onDisconnection() call. The issue is still unsolved. I blame it on the environment and appreciate any inputs/hints that might help to resolve it.