Racing: Obstacle Avoidance (MS)

Racing: Obstacle Avoidance (MS)

At the MPC lab we have developed a learning MPC for racing. In the current framework the vehicle runs several laps on a race track improving its lap time at each lap. The goal of this project is to extend this framework to take into account the presence of other vehicles on the race track.

Firstly, the student should expand the control logic to take into account static obstacles. Afterwards, it would be necessary to build a predictive model for the target vehicles using date collected from experience, this would allow to consider other vehicles on the track in the optimization. 

Prerequisite: Solid control background and programming skills (C, Python, Matlab). Good optimization or machine learning background.

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