Introduction to Problem based Learning – The AAU Way

1. Introduction to Problem based Learning – The AAU Way Program: • Monday : Structure, teaching task's, courses, • Tuesday : The Aalborg model - trying it out, PBL/Project Work and Assessment • Wednesday : Supervision Coffee break's at ap. 10.00 and 14.00 - Lunch at 12.00

2. Introduction to Problem based Learning – The AAU Way Program for to day, Structure, teaching task's, courses : • Welcome • Introduction and short presentation • Structure and conditions • Teaching task's • Courses • Exercises

3. Welcome to Aalborg University Structure of Aalborg University

4. University Senate Rectorate Faculty of Humanities Faculty of Engi- neering and Sc. Faculty of Social Science Departments Study Programmes Structure of Aalborg University

5. Secretary and labs Research Teaching University Senate Rectorate Faculty of Humanities Faculty of Engi- neering and Sc. Faculty of Social Science Structure of Aalborg University Institute of Elec- tronic Systems Study Programmes

6. Project work Course activities Secretary and labs Research Teaching University Senate Rectorate Faculty of Humanities Faculty of Engi- neering and Sc. Faculty of Social Science Structure of Aalborg University Institute of Elec- tronic Systems Computer Eng. Electronic and .

7. Working tasks for VIP’s

8. Study board for Electronics and Information Technology

9. Controlling the studies Study Regulations: • General regulations

10. 4.6. INTELLIGENT AUTONOMOUS SYSTEMS Objectives and contents of the specialisation The objectives of the specialisation in Intelligent Autonomous Systems are summarised asfollows: to provide students with knowledge in modelling of mechanical systems such as spacecraft, ships, and mobile robots, enable the student to apply modern methods of control to problems related to autonomous systems, to analyse methods of state observation, parameter estimation and sensor fusion in mechanical systems, to provide students with a comprehension of supervisory control, fault-tolerant control and fault detection, to let students analyse software architectures for autonomous systems. The courses include necessary general theoretical topics within process control for autonomous systems but modules are also made available in scientific communication andproficiency in English language for those who need it. Controlling the studies Study Regulations: • General regulations • Sector’s, lines or specialization’s • Objectives and content

11. SPRING Semester – Intelligent Autonomous Systems THEME: Modelling and Control PERIOD: 1 February - 30 June PURPOSE: To give knowledge and comprehension of optimal and robust control theory. To give the students the ability to analyse modern control methods for multi input/multi output systems. To give students the ability to apply modelling methods and control synthesis for advanced mechanical systems. CONTENTS: The project is based on a problem of control and supervision of an autonomous system. Themodel of the mechanical system has to be derived. The vital part of the project is the choiceof the set of actuators and sensors for onboard application. Different control strategies haveto be investigated and compared. The supervisor system responsible for autonomy onboardhas to be designed. The chosen solution has to be implemented on a real time platform andtested, either by the computer simulations or dedicatedhardware. COURSES: Courses will be given in the field of modelling of mechanical systems, supervisory and fault tolerant control, and modern control theory. EXAM: The external oral examination is based on the prepared project documentation. Each studentis marked according to the 13-scale. Controlling the studies Study Regulations: • General regulations • Sector’s, lines or specialization’s • Objectives and content • Specific semesters • Theme

12. Model based tracking for navigation • Background • As part of an ongoing research project (with Computer Science AAU andThe Danish Institute of Agricultural Sciences) an autonomous vehicle isdeveloped which navigates autonomously in the field. The aim is toreduce the inputs to the field and monitor the growth of the individual plants, thereby providing obvious environmental and economicadvantages over more traditional farming. • Purpose • It is important in such applications to both navigate accurately in the fieldbut also to be able to identify individual plants. The aim in this project is touse perspective images captures from a camera mounted on the front ofthe vehicle to provide estimates of structure of the crop rows as well as position of the individual plants. The focus will not be on the imageanalysis but on sensor fusion with non-vision sensors mounted on thevehicle e.g. wheel encoders, differential GPS as well as integration ofinformation about the known structure of the field. • The aim is to use all available information on the autonomous vehicle inorder to achieve the best possible estimates of the vehicle and individualplant position (in the order of cm). • Methods • The project will include: • Modeling of vehicle system and plant pattern in the cameraimage • Prediction of the crop structure based on the systemmodels as well as previous measurements (images and • data from sensors) • Estimation of vehicle position and orientation as well asplant position • Algorithms are simulated in the laboratory on simplesetup. • If possible the algorithms are applied to data acquired inthe field. Controlling the studies Study Regulations: • General regulations • Sector’s, lines or specialization’s • Objectives and content • Specific semesters • Theme • Projects

13. Study related courses (SE): Fault Detection and Automated Systems Modelling of Mechanical Systems Controller Structures Modelling of Mechanical Systems II Engineering Responsibilities Project related courses (PE): Robust Control Optimal Control Supervisory Control Neural Networks and Fuzzy Logic Project Management and Team Building Controlling the studies Study Regulations: • General regulations • Sector’s, lines or specialization’s • Objectives and content • Specific semesters • Theme • Projects • Courses

14. Controlling the studies Study Regulations: • General regulations • Sector’s, lines or specialization’s • Objectives and content • Specific semesters • Theme • Projects • Courses • Semester group

15. Teaching task’s Structure of a semester: Study courses and lectures Project courses lectures seminar Lecturer/instructor Examination 50% - 33% Examinor Lecturer/instructor Project Supervisor: Advisor and facilitator 50% - 67% Examinor/censor Examination

16. Course Description • Optimal Control Theory • Purpose: • To give the students knowledge in optimal control and practical experience with optimal control strategies based on minimisation of a performance index. • Contents: • Dynamic programming • LQ control • Introduction of reference and disturbance conditions • Introduction of integral conditions • Use of observer, LQG control • The position of closed loop poles • Prerequisites: Analogue and Digital Control (FP6-4, PR6-1, PR6-2), Stochastic systems(FP6-3, FP8-5) • Duration: 1 module • Category: Project theme course (PE- course) Courses • Description

17. Courses • Description • Placed in a timetable for the semester

20. Courses • Description • Placed in a timetable for the semester • Syllabus

21. Courses Each lesson/lecture (Mini module): • Duration 3 hours 45 minutes (½ day) • 2 lectures app. 45 min each • Exercises in groups, app. 2 hours • The lecturer is now instructor The purpose of the combination of lectures/exercises is to increase the comprehension of the curriculum

22. Courses What kind of exercises would you chose? • Promote comprehension and methodical ness How will you act as instructor during the exercises in the groups? • Ask questions about how they have made their solution • Make sure that they have understood the basic principles of the problems

23. Courses Differences between project course (PE) and study course (SE) • Examination • PE has no formal examination by the lecturer, it is examined during the project examination by the supervisor • SE is examined by the lecturer, normally as a written examination (passed/non passed) • Exercises • PE is used in the project, exercises is examples • In SE the student must learn to solve examination exercises

24. Lunch until 12.45

25. Course exercise • Think of an engineering subject you all know something about • Suppose that you have to do a course on that subject • Make a short exercise that will learn the students the major point of a specific part of your course

26. Course exercise continued For one group at a time do: • Give your exercise to the other three groups who starts solving it • Prepare how you will instruct the groups during their problem solving • After 5-10 minutes of problem solving 2 persons from your group enters each of the other groups and starts acting as an instructor