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About Autonomous Mobile Robots

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You arrived at the "Autonomous Mobile Robots" course page. Updates will follow without warning. See date of "last update".
This web-page is maintained by Toto van Inge, Faculty of Science, University of Amsterdam.
Find information of previous years on Autonomous Mobile Robots.

Introduction

The official description of course 5062NECO6Y can be found (in Dutch) here. Also a Blackboard portal is available for lecture documents and assignments.

The AMR instructors are:
Toto van Inge
Nour Hussein

Content

This course gives an introduction in the fundamentals of mobile robotics, spanning the mechanical, motor, sensory, perceptual, and cognitive layers the field comprises. The focus will be on the mechanisms that allow a mobile robot to move through a real world environment to perform its tasks. It synthesizes material from the fields of kinematics, control theory, signal analysis, computer vision, information theory, artificial intelligence and probability theory.

Useful Software

is the robot simulator V-REP PRO. For the educational version go here.

For a short introduction go to Virtual Robot Experimentation Platform USER MANUAL. More specific the BubbleRob tutorial.

Schedule

The official schedule is found in datanose.

Students, who were not able to attend a lecture, can catch up by listing to the recordings of Arnoud's lectures (in Dutch). Download Lecturnity Player and listen to lecture, synchronized with the sheets.

Remark: For the assignments not only a solution is expected, but also a rational. The experiments performed to solve the given problem should be described in a lab report, which will be graded based on the following criteria.

This is also the Reading guide.

  • Week 6:
    • Chapter 1, 2 - Introduction, Locomotion Concepts
    • Chapter 3 - Mobile Robots Kinematics
  • Week 7:
    • Chapter 4.1 Sensors for Mobile Robots
    • Chapter 4.2 Fundamentals of Computer Vision
  • Week 8:
    • Chapter 4.3-4.5 Feature Extraction
    • Chapter 4.6-4.7 Place Recognition
  • Week 9:
    • Partial Exam, Marz 2th, 16:00-18:00, SP G2.02
  • Week 10:
    • Chapter 5.1-5.5 Sensors for Mobile Robots
    • Chapter 5.6 Probabilistic Map Based Localization
  • Week 11:
    • Chapter 5.6.8 Kalman Filter Localization
    • Chapter 5.8 Simultaneous Localization and Mapping
  • Week 12:
    • Chapter 6 - Planning and Navigation part I
    • Chapter 6 - Planning and Navigation part II
  • Week 13:
    • Partial Exam, Marz 27th, 13:00-15:00, SP C0.05

Literature

This course is based on the book:

Prof. Dr. Roland Yves Siegwart, Prof. Dr. Illah R. Nourbakhsh and Prof. Dr. Davide Scaramuzza, 'Introduction to Autonomous Mobile Robots', 2nd edition, The MIT Press, 2011.

Embedding in AI curriculum

This course is supported by the following chapters of 'Artificial Intelligence - A Modern Approach' 3rd edition, by Stuart Russell and Peter Norvig:

  • Chapter 13: Quantifying Uncertainty
  • Chapter 14: Probabilistic Reasoning
  • Chapter 15: Probabilistic Reasoning over Time
  • Chapter 24: Perception
  • Chapter 25: Robotics

Links

Video Index

Software toolkits

Chapter 4, section 2.6 (page 186) - Structure from Motion:

Chapter 4, section 5 (page 234) - Interest Point Detectors:

Chapter 5, section 8 (page 365) - Simultaneous Localization and Mapping algorithms:

Bibliography (page 444) - Referenced webpages: