Design and implement MPC path tracking controller on embedded platform

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Type vacature
Graduation assignment
Capgemini Engineering
Automotive Engineering, Mechanical Engineering, Electrical Engineering, ICT
Software, Testen, Automated Driving, Monitoring

Model predictive control is an advanced control method that is used to control a process while satisfying a set of constraints. In the field of autonomous driving it is widely used as a path tracking control technique. Different implementation of MPC exist for the path tracking problem, such as linear MPC, non-linear MPC, lateral and longitudinal MPC as two separate problems, lateral and longitudinal combined MPC etc.

At Capgemini Engineering we are testing an Automated Valet Parking system in a Hardware-in-the-loop environment. The autonomous driving software we are using is Autoware.Auto. Currently, there is an MPC controller running as part of Autoware.Auto in a ROS2/C++ environment on a Linux based machine. Our whish is to have a similar MPC implementation, but implemented on an automotive grade ECU platform, such as the MicroAutobox II. Therefore, the implementation of the MPC controller will have to be done in MATLAB/Simulink.      

    1. Assignment

The goal of the assignment is to build an MPC path tracking controller in MATLAB/Simulink that is to be implemented on an automotive grade ECU platform. The assignment includes:

  • Find a reference implementation in another programming language, such as python or C++, which can serve as the starting point for implementation in MATLAB/Simulink. On platforms like Github several opensource initiatives are availabe.
  • Develop the algorithm in MATLAB/Simulink without using any paid toolboxes
  • Compile the model and implement it on the automotive ECU platform
  • Test the path tracking controller with the complete setup, where it will replace the Autoware.Auto MPC implementation running in ROS2
  • Benchmark performance to Stanley Path tracking controller
    1. Technical aspects
  •  Python, C++, MATLAB/Simulink dSPACE Scalexio, “Hardware In the Loop” (HIL) setup, dSPACE MicroAutobox/other platform.
  •  Development is done using MATLAB/Simulink, knowledge of python, C++, ROS or Autoware is expected as well as experience with Control Systems design.
  • Strong mathematical background
    1. Other:

Level of the assignment: This assignment can be done by a HBO+/WO (master) student, where the assignment can be adjusted according to the educational direction/level.

Educational direction: Automotive, Mechanical, Electrical, Computer science.

Contact persons: Jeroen Schutte - or Lucas Raemakers -

Duration of assignment: 4-6 months, standard HBO/WO graduation period, including research, implementation, thesis writing.

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