ELEC-E8111 - Autonomous Mobile Robots D, Lecture, 27.2.2024-29.5.2024

Topic outline

• Materials
  • Select activity Lecture 1

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    Course Introduction and arrangements:
    

    1. Learning Goals
    2. Teaching Format
    3. Lecture topics
    4. Assessment and grading
    5. Project topic introduction

    Introduction to mobile Robotics

    1. What is robot
    2. Types of mobile robots
    3. Challenges of mobility
    4. Embodied intelligence
    5. Levels of Autonomy
    6. Standard Architectural Model
    7. Robotic Paradigms

    
    

    
    
  • Select activity Lecture 2

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    Lecture topics:

    • Locomotion - Overview
    • Wheeled Robots
    • Kinematics of Wheeled Robots
    • Motion Control of Wheeled robots
    • Legged robots
    • Other types of Locomotion

    Please read both the slides and additional reading for the quiz.
    
  • Select activity Lecture 3

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    Lecture topics:

    • Perception
    • Measurement principles
    • Sensing and Perception
    • Sensors
    • Internal sensors
    • Range Sensors
    • Estimation

    The quiz will cover only the topics discussed during the lecture!

    The quiz will include information covering the extension of said topics from the "Introduction to Autonomous Robots" book!

    The material from Hands book of robotics are provided only to further clarify the discussed topic, and they will not be included in the quiz.
    
  • Select activity Lecture 4

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    The lecture covered the following topics:

    • Bayes Rule
    • Robot environment interaction
    • Bayes filters
    • Motion models
    • Sensor models
    • Histogram filters
    • Particle filters
    • Particle filters for localisation

    The quiz will not cover slides 52-55 or 75-77.
    

    The material in the books provides the theoretical foundation for the lecture's content, but it will not be included in the quiz.
    
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    • GIM ROBOTICS, COMPANY PRESENTATION, WHAT DO WE DO?
    •  MIDDLEWARES (GIM’s HISTORY): GIMNET->ROS->ROS2
    • WHY ROS2?
    • BF-PEAMS PROJECT AS AN EXAMPLE
    • MEVEA-GIM CASE
    • INDUSTRIAL USE CASES
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    • Mapping
    • Gridded representations
    • Map Building
    • Registration
    • SLAM
    • EKF-SLAM with landmarks
    • RBPF-SLAM
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    • Limitations of HMM-based SLAM
    • Graph-SLAM Framework
    • Front end
    • Back end
    • Graph-SLAM Efficiency
    • Robust back ends
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    • INS
    • GPS/GNSS

    
    

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  • Select activity Lecture 10

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