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  • 1.
    Alexandersson, Johan
    et al.
    Linköpings universitet, Institutionen för systemteknik, Datorteknik. Linköpings universitet, Tekniska fakulteten.
    Nordin, Olle
    Linköpings universitet, Institutionen för systemteknik, Datorteknik. Linköpings universitet, Tekniska fakulteten.
    Implementation of CAN Communication Stack in AUTOSAR2015Självständigt arbete på grundnivå (kandidatexamen), 10 poäng / 15 hpStudentuppsats (Examensarbete)
    Abstract [en]

    In the automotive industry today, embedded systems have reached a level of complexity which is not maintainable with the traditional approach of design- ing automotive embedded systems. For this purpose, many of the worlds leading automotive manufacturers have formed an alliance to apprehend this problem. This has resulted in AUTOSAR, an open standardized architecture for automotive embedded systems, which strives for increased flexibility and safety regulations. This thesis will explore the possibilities of implementing a CAN Communication stack using the AUTOSAR architecture and its corresponding methodology. As a result of this thesis, a complete AUTOSAR CAN communication stack has been implemented, as well has a simulator application with the purpose of testing its functionality. 

  • 2.
    Alexandersson, Johan
    et al.
    Linköpings universitet, Institutionen för systemteknik, Datorteknik.
    Nordin, Olle
    Linköpings universitet, Institutionen för systemteknik, Datorteknik.
    Implementation of SLAM Algorithms in a Small-Scale Vehicle Using Model-Based Development2017Självständigt arbete på avancerad nivå (masterexamen), 20 poäng / 30 hpStudentuppsats (Examensarbete)
    Abstract [en]

    As autonomous driving is rapidly becoming the next major challenge in the auto- motive industry, the problem of Simultaneous Localization And Mapping (SLAM) has never been more relevant than it is today. This thesis presents the idea of examining SLAM algorithms by implementing such an algorithm on a radio con- trolled car which has been fitted with sensors and microcontrollers. The software architecture of this small-scale vehicle is based on the Robot Operating System (ROS), an open-source framework designed to be used in robotic applications.

    This thesis covers Extended Kalman Filter (EKF)-based SLAM, FastSLAM, and GraphSLAM, examining these algorithms in both theoretical investigations, simulations, and real-world experiments. The method used in this thesis is model- based development, meaning that a model of the vehicle is first implemented in order to be able to perform simulations using each algorithm. A decision of which algorithm to be implemented on the physical vehicle is then made backed up by these simulation results, as well as a theoretical investigation of each algorithm.

    This thesis has resulted in a dynamic model of a small-scale vehicle which can be used for simulation of any ROS-compliant SLAM-algorithm, and this model has been simulated extensively in order to provide empirical evidence to define which SLAM algorithm is most suitable for this application. Out of the algo- rithms examined, FastSLAM was proven to the best candidate, and was in the final stage, through usage of the ROS package gMapping, successfully imple- mented on the small-scale vehicle.

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