Master Thesis Proposal:Precise Localization

Teoresi è una società internazionale di servizi di ingegneria, nata a Torino nel 1987.
Siamo specializzati nel supportare le aziende nella realizzazione di progetti che utilizzano tecnologie all'avanguardia, dalla guida autonoma alle nanotecnologie applicate all’ambito medicale. Il nostro approccio innovativo prevede una stretta collaborazione con i reparti di Ricerca e Sviluppo dei principali marchi industriali. Realizziamo soluzioni chiavi in mano accelerando il time-to-market del cliente. Teoresi è una delle 10 aziende selezionate da Amazon per collaborare allo sviluppo di nuovi prodotti basati sull’interazione vocale di Alexa.

Siamo sempre alla ricerca di persone di talento da inserire nel nostro team. In Teoresi diamo valore agli aspetti innovativi di ogni sfida progettuale , al lavoro di squadra, alla diversità e e ci piace pensare liberi da confini, non solo geografici. Siamo costantemente aggiornati sui progressi tecnologici, dando priorità alle persone e alla sostenibilità ambientale. Il nostro team multidisciplinare e la nostra presenza globale ci permettono di offrire opportunità di carriera internazionali e di soddisfare le esigenze di un mercato in costante evoluzione. Crediamo che la proattività e la curiosità per l'apprendimento continuo siano essenziali in un contesto di squadra e ci impegniamo a generare innovazione in tutto ciò che facciamo.
Se condividi i nostri valori e ti interessa far parte di un'azienda orientata al futuro, continua a leggere e candidati!

Description

Teoresi is looking for talented young people interested to develop a thesis project in the company.
In this case we introduces a master thesis proposal that focus on precise localization using low power microcontroller and sensors.

Company Teoresi Group -> Teoresi S.p.A. | Italy

Job requirements

Topic Characteristics: ADAS and autonomous driving cover many different technologies: vision and artificial intelligent algorithm, embedded high efficient C++ code, planning algorithms, new control algorithms, simulation and unity assets design, Navigation, Human-Machine-Interface, Connectivity. In urban scenario an accurate outdoor localization for autonomous machine involve a lot of different sensors. Currently, the main approach is to use an Inertial Measurement Unit (IMU) with GPS and Inertial Navigation System (INS). The integration of a lot of different sensors in the same package is not an easy task. Currently, on the market there are a lot of different all in one package but most solutions are very expensive. Moreover also the software part, usually based on custom implementation of Kalman filtering algorithms, is hardware dependent and will be not provided by the seller. Accordingly precise customization based on system architecture are difficult to implement. This thesis proposal focus on develop a precise localization ECU based on low power microprocessor. The work consist both in the study of hardware setup and in the development of a software stack based on provided API.

Methodology:

The goal of this work is defined by these step:

- Hardware Setup and Study: o The precise localization ECU is based on a low-power STM32 Nucleo board with IMU, INS, and GNSS extended module. The first part of the thesis consist in the study of the hardware (interconnection, setup, API software, limits etc.).

- Precise localization Algorithm identification: o Identify the best precise algorithm for each sensors is essential for the next steps. The final goal is to combine data provided by all the sensors to find the best methodology to have a precise localization also in difficult situation.

- Quality comparison with an expensive platform o The result of the work is compared with an expensive platform. The goal is not to have the same performance but to understand the limits of a low cost and low power platform.

- Integration in a real target o The last step is the integration of the platform in an autonomous driving framework and to test it in an outdoor scenario with a real autonomous vehicle.

Toolchain: C++ Unity Matlab Simulink

Preferential position requirements

At the end of the project, and after the graduation, there could be the opportunity to be included in the company, through a paid internship. Interested parties are invited to respond to the following add by uploading their CV, or to send an email to job@teoresigroup.com, referring to the add (TeoTESI_PLocal_201904) and attaching the detailed CV with the course of study and exams taken. The opportunity offered is to work in a young and dynamic environment, able to recognize and reward the best professionals. Under current legislation, the job offer is intended to be extended to both sexes (Law 903/77).

Education

Laurea tradizionale o specialistica

Career level

Laureando / neolaureato