Budapest University of Technology and Economics, Faculty of Electrical Engineering and Informatics

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    Autonomous Robots and Vehicles

    A tantárgy neve magyarul / Name of the subject in Hungarian: Autonóm robotok és járművek

    Last updated: 2018. augusztus 30.

    Budapest University of Technology and Economics
    Faculty of Electrical Engineering and Informatics
    Electrical Engineering MSc program
    MSc degree program 
    Intelligent robots and vehicles secondary specialization block
    Course ID Semester Assessment Credit Tantárgyfélév
    VIIIMA12 1 2/1/0/v 4  
    3. Course coordinator and department Dr. Kiss Bálint,
    4. Instructors

    Dr. Béla Lantos, prof. emeritus, Department of Control Engineering and Information Technology

    dr. Bálint Kiss, associate professor, Department of Control Engineering and Information Technology

    dr. Emese Gincsainé Szádeczky-Kardoss, associate professor, Department of Control Engineering and Information Technology

    5. Required knowledge Mathematics, Physics, Informatics, Control engineering
    6. Pre-requisites
    Kötelező:
    NEM ( TárgyEredmény( "BMEVIIIA358" , "jegy" , _ ) >= 2
    VAGY
    TárgyEredmény( "BMEVIIIM127" , "jegy" , _ ) >= 2
    VAGY
    TárgyEredmény("BMEVIIIA358", "FELVETEL", AktualisFelev()) > 0
    VAGY
    TárgyEredmény("BMEVIIIM127", "FELVETEL", AktualisFelev()) > 0)
    VAGY Szak("6N-MA") VAGY Szak("6NAMAR") //KJK AVCE

    A fenti forma a Neptun sajátja, ezen technikai okokból nem változtattunk.

    A kötelező előtanulmányi rendek grafikus formában itt láthatók.

    7. Objectives, learning outcomes and obtained knowledge

    The subject summarizes the theoretical and practical fundamentals of the modeling, control and intelligent architectural realization methods of robotic and autonomous systems. The subject provides concepts and system engineering background for maintenance and development engineers of such systems. Robotized manufacturing cells, widely used robot structures and the typical programming methodology of robotic arms are presented. Robot modeling, navigation and motion planning methods are studied. Special emphasis is put on the real-time control methods of robot arms and mobile platforms. Possibilities of the cooperation of wheeled and legged mobile robots are enumerated. Current control end navigation challenges are overviewed.

    Students successfully completed the course requirements will have an in-depth understanding of the modelling, real-time control and navigation solutions employed in robotics so that he or she can can creatively employ and complement them as necessary in the case industrial applications (e.g. automotive and robotics).

    8. Synopsis
    1. Fundamentals in mechanics (1 week)
    Controlled mechanism, trajectory, task, end effector. Levels of the control hierarchy, PTP and CP control, coordinated motion. Internal and external sensors. Unmanned aerial, ground and underwater vechicles.
      
    2. Navigation methods of autonomous systems (2 weeks)
    Orientation parameterization in navigation systems: elementary rotations, Rodriguez formula, Euler and RPY angles, homogeneous transformations. Navigation similarity of vehicles (car-like, aerial, marine). Sensors of navigation systems: differential GPS, 3D accelerometers, gyroscope, state estimation.
     
    3. Dynamical models of mechanical systems (2 weeks)
    Kinematic and potential energies, inertia tensors, Lagrange and Newton-Euler equations. Recursive an symbolical calculation of dynamical models.
     
     4. Geometric and kinematic models of robot arms (1 week)
    Denavit-Hartenberg convention. Robot transformation graph. Direct and inverse geometry problems and their solutions. Differential motion, partial translational and rotational velocities, Jacobian matrix. Position, velocity and acceleration algorithms. Motion planning of redundant robot arms.
      
    5. Control of robot arms (2 weeks)
    Control of free motion: decentralized cascade joint level control, computed torque methods. Transformation of static forces and torques, Hybrid position and force control.
     
    6. Robot programming languages and real-time implementation (1 week)
    Architecture of robot programming languages: structured, task-based, model-based and cooperative languages, distributed systems. Path planning in joint space and in task space, realization of motion primitives. Real-time operating systems for control realization. 
     
    7. Robot programming and robot controller systems (1 week)
    Robot cell design, robot control software environments, robot simulation in virtual environments. Case studies
     
    8. Motion planning and tracking control of mobile robots (2 weeks)
    Kinematic model of mobile robots, reference robot, tracking control using state feedback techniques. Time optimal motion plnanning (Reeds-Sheepp, Dubbins, diferentially driven robots). Environment mapping, obstacle avoidance algorithms (potential fields, behavior based strategies).
     
    9. Intelligent actuators and their application in automotive control (2 weeks)
    Intelligent actuators on a car: suspension systems, steering systems, break systems, and their integrated control. Increasing intelligence for autonomous behavior.
    9. Method of instruction The subject has two contact hours of lectures and one contact hour of practice session each week. Practice session include the study of application examples, solution of numerical examples, and implementation of algorithms.
    10. Assessment
    a. During the period of classes: successful midterm exam (at least pass grade). The result of the midterm exam count for the exam grade with up to 20%. Requirement for signature: the result of the midterm exam is at least 2 (pass).

    b. During the period of exams: no exam is possible without the signature. The exam is written composed of theoretical questions and exercises. 

    c. Early exam: not available
    11. Recaps The mid-term can be repeated once during the period of classes and once during the repeat period.
    12. Consultations Available on request.
    13. References, textbooks and resources

    Lantos-Kiss-Harmati: Autonomous robots and vehicles handouts (electronically)

    Lantos-Márton: Nonlinear Control of Vehicles and Robots (Springer, 2011)

    Somló-Lantos-Cat: Advanced robot control (Akadémiai Kiadó, 1997)

    14. Required learning hours and assignment
    Contact hours42
    Preparation for contact hours15
    Preparation for the midterm15
    Preparation for the exam48
    Total workload120
    15. Syllabus prepared by

    Dr. Béla Lantos, prof. emeritus, Department of Control Engineering and Information Technology

    dr. habil. István Harmati, associate professor, Department of Control Engineering and Information Technology

    dr. Bálint Kiss, associate professor, Department of Control Engineering and Information Technology