Master ThesisIDSC-EF-28

Constraints estimation for aggressivemaneuvers on driverless go-karts

MotivationA crucial aspect in robotics is to have a fast and reliable localization. In this thesis we want to implement local estimation of the boundaries of the track for an driverless go-kart. This will enable modern control strategies (such as MPC or GLC planning) to leverage real time knowledge of the boundaries and obstacle location in the decision making process. In order to operate safely close to limits the estimation needs to be reliable, robust, and ideally fail-safe.

Tasks

Improve the current global localization algorithm (see https://github.com/idsc-frazzoli/retina/issues/353 ).

Develop a boundaries estimation pipeline.

This task can be carried out with different sensors (LIDAR, rgb, event-based, and infrared cameras) depending on personal interests.

Integrating the developed pipeline with the preexisting MPCC (Model Predictive Contouring Controller).

Benchmarking the proposed solution with already existinglocalization algorithms.

Extra: include also dynamic obstacle in the framework.

Expected outcome

Appropriate documentation of all the experiments showing theability to turn good theoretical models into working code.

Contact: Use the link http://bit.ly/frazzoli to apply.

Prerequisites

Nice to have (or willing to learn about) :

Recursive Estimation, Computer Vision, Object detection, Git, ObjectOriented Programming (we are open to any language).