Current work

Radar Sensor Plugin for Game Engine Based
Autonomous Vehicle Simulators

Simulations play an important role in developing autonomous vehicles and verifying their safe operation. They also enable basic research in sensor fusion by low-cost experimentation with different design decisions, like the number and location of various sensors on vehicles. Apart from industrial simulation tools, researchers have been using game engine based simulators, mainly to generate training data for artificial intelligence systems and to test their decision making in virtual worlds. These open source simulators currently support camera and lidar sensors, but lack a radar implementation. Automotive radars serve important driving assistance functions today and they will evolve into imaging radar systems for autonomous vehicles. Therefore we need to be able to simulate them in the same environment together with other sensors. In this project, we aim to develop a generic radar sensor plugin using a raytracing method, and to integrate it to CARLA, which is an autonomous driving simulator based on Unreal Game Engine.

Available after May 2020


Design, Analysis and Simulation of
Microscale Solid-Wave Gyroscopes

In this thesis, we focus on MEMS solid-wave gyroscopes operated in rate-integrating mode. In parallel to the miniaturization efforts of shell-type resonators, we address design and fabrication problems by analysis and simulation. We investigate vibrations of axisymmetric resonators using a shell theory and 2.5D elasticity. We employ classical finite element method and spectral methods. We describe effects of geometric imperfections on gyroscope dynamics and use mode-coupling to model vibration sensitivity. We also detail computations of temperature sensitivities of gyroscope parameters. We then formulate and solve example shape optimization problems based on these analyses. Lastly, we introduce thermomechanical noise squeezing to reduce angle random walk.


theme: modified minimal