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MOBILE ROBOTS

CODE 106956
ACADEMIC YEAR 2022/2023
CREDITS
  • 5 cfu during the 1st year of 10635 ROBOTICS ENGINEERING (LM-32) - GENOVA
  • SCIENTIFIC DISCIPLINARY SECTOR ING-INF/04
    TEACHING LOCATION
  • GENOVA
  • SEMESTER 2° Semester
    TEACHING MATERIALS AULAWEB

    AIMS AND CONTENT

    LEARNING OUTCOMES

    The class first develops the kinematic modeling and motorization of mobile robots, illustrated by the full study of the differential drive robot. Then localization based on the Extended Kalman Filter is addressed, is illustrated by a lab which uses real data and presents a tuning methodology. Observability issues are also addressed, with practical examples. Planning methods applicable to mobile robots are studied, in particular potential field methods and the Rapidly exploring Random Tree. Control then focuses on direct applications to mobile robots: static and dynamic feedback control and Lyapunov based control, illustrated on the case of the differential drive robot.

    AIMS AND LEARNING OUTCOMES

    The students will be able to tackle real problems in mobile robotics. In kinematic modeling and in localization, their experience will involve practical knowledge and, in localization, hands on experience with real data.

    PREREQUISITES

    The prerequisites of the class are essentially mathematical. They are described in a PDF document available to students on Aulaweb.

    SYLLABUS/CONTENT

    • Modeling of wheeled Robots: Constraint equations, Classification of robots using degrees of mobility and steerability, Posture kinematic model, Configuration kinematic model, Motorisation of wheels.
    • Localization: Relative localization using odometry, Absolute localization, Localization sensors, Localization using extended Kalman filtering.
    • Control: Controllability and stabilization, static and dynamic feedback linearization, nonlinear control based on Lyapunov functions.
    • Practical Work: The students will study various control laws in simulation. They will also implement a Kalman filter-based localization algorithm using data recorded with a real robot.

    RECOMMENDED READING/BIBLIOGRAPHY

    • “Theory of robot control”, Carlos Canudas de Wit, Bruno Siciliano, Georges Bastin, Springer Science & Business Media, 2012 - 392 pages.
    • PDF documents provided by the teacher.

    TEACHERS AND EXAM BOARD

    Exam Board

    GAETAN GARCIA (President)

    MARCO BAGLIETTO

    ANTONIO SGORBISSA (President Substitute)

    ENRICO SIMETTI (President Substitute)

    LESSONS

    Class schedule

    All class schedules are posted on the EasyAcademy portal.

    EXAMS

    EXAM DESCRIPTION

    The exam is based on exercises that remain fairly close to class examples and homework examples. The exam typically is a mix of questions that must be solved by calculation, and questions that must not. The exam also contains questions that are meant to evaluate the knowledge gained from the labs.

    ASSESSMENT METHODS

    Final exam 100%, but as stated above, the exam contains questions to evaluate the understanding of the labs.

    Exam schedule

    Date Time Location Type Notes

    FURTHER INFORMATION

    Teacher’s email address: gaetan.garcia@ec-nantes.fr