Master Thesis presentation by Gaizka Barrasa

Examiner: Jonas Sjöberg

Abstract:
The testing of autonomous vehicles presents a challenge in ensuring safety. This study addresses the challenge by developing an autonomous bicycle capable of following predefined paths. Consequently, it eliminates the requirement for human bike riders in testing scenarios involving bicycles and vehicles. Instead, they are replaced by dummies.

The study involves the development of a Kalman filter and the enhancement of the trajectory controller algorithm. The algorithms are validated in Simulink before being transformed into C-code and inserted in LabVIEW which is run on the real bicycle’s myRIO (microprocessor).

Finally, the trajectory generation, parameter acquisition (MATLAB), program execution (LabVIEW), and the initialization protocol from program launch to the achievement of autonomous motion for testing with the real bicycle are explained. Additionally, a test is presented where the bicycle tracks three constant radius circles where the developed functionalities and their repeatability are evaluated in the real bike. The result of the test is that the bike can track the reference with a maximum error of ±0.5m.

The algorithms are parameterized to be adapted for various bikes, regardless of their dimensions and characteristics.

Welcome!

Gaizka and Jonas