Topic outline

  • Materials

    • Folder icon
      Lecture 1 March 2, 2021: Course introduction and arrangements. Introduction to mobile robots Folder

      1st Zoom Lecture March 2, 2021. Time  14:15 -16:00

      Course introduction and arrangements
      What do you expect to learn from the course?

      • Understand the main challenges in mobile robotics
      • Understand what are mobile robots made of
      – Sub-systems (perception, mobility, navigation, planning, power, …)
      – Basic approaches and terminology for each sub-system
      – Methodology and algorithms in mobile robotics
      • Learn the characteristics in three applications areas
      1. Indoor mobile service robot
      2. Field Robot: Outdoor semiautonomous vehicle / heavy duty machine UGV
      3. Autonomous vehicle, basics
      • Not processing, manipulation and grasping

      Teaching: Lectures, Team work: Design of a case robot system, Indv.: Testing algorithms under ROS on Pioneer robot platform

      Lectures (estimate)
      Nro topics
      1 Course introduction and arrangements, Introduction to mobile robots
      2 Robot control system architecture , Reactive robotics  
      3 Team work: Design of a case robot system
      Individual project: Testing algorithms under ROS/ Pioneer
      Introduction to ROS
      Locomotion, Kinematics, and Low level Motion Control
      4 Sensing and perception, overview.
      - Kalman-filter based traditional vehicle localization
      5 SLAM = Simultaneous Localization and Mapping, Extended Kalman Filter SLAM (EKF SLAM)
      6 Particle filter and Fast SLAM
      7 Graph SLAM
      8 Satellite Positioning - GNSS technologies
      9 Pose Estimation, Inertial Navigation Systems (INS), Inertial Measurement Unit (IMU)
      10 Visual localization and object recognition
      11 Graph based Path and Motion Planning, Indoor A*. Path and Motion Planning, Outdoor D*
      12 Outdoor Path and Motion Planning Motion Control

      Introduction to mobile robots

      • What is a service robot? Field Robot?
      • Which kinds of service and field robots exist?
      – Examples
      • Mobile robot subsystems
      • Control architectures
      • More on Field robotics
      • Autonomous vehicles

    • Folder icon
      Lecture 2. Control architectures. 03/03/2021 Folder
      Not available unless: You are a(n) Student

      Contents of the lecture

      • Motivation and state-of-the-art issues

      • Short introduction to control paradigms

      • The Hierarchical Paradigm

      • Biological foundations for the reactive paradigm

      • The Reactive Paradigm

      • The Hybrid Paradigm

      +Hopefully some good examples and some inspiration

    • Folder icon
      Lecture 3, March 9, 2021: Course Robot Projects intro, Introduction to ROS, Locomotion, Kinematics, and Low level Motion Control Folder
      Course Robot Projects intro
      • Team Design Robot project
      • Individual Pioneer Lab Robot project
      Introduction to ROS


      Locomotion, Kinematics and Low Level Motion Control
      • Locomotion – Principles and mechanisms to make the robot move.
      • Kinematics – How to model motion of (rigid) bodies?
      1. Differential drive robot, like Pioneer
      2. Wheeled Mobile Robot
      • Motion control – How to make a robot attain a goal or follow a trajectory?

    • Folder icon
      Lecture 4, March 10, 2021: Sensing and Perception, an overview Folder
       Sensing and Perception, an overview

      • Characterizing sensors
      • Classification of sensors
      • Sensor types for mobile robots
      • Perception in mobile robotics

    • Folder icon
      Lecture 5, March 16, 2021: Localization, mapping and SLAM = Simultaneous Localization and Mapping, idea; EKF SLAM Folder
      Not available unless: You are a(n) Student

      Localization, mapping and SLAM = Simultaneous Localization and Mapping, idea

      - Main material as subset of ETH slides
      - Kalman-filter based traditional vehicle localization in the tractor-trailer -case.

      Extended Kalman Filter SLAM (EKF SLAM)

      Save videos for running. A  video  haehnel-RawOdometry-anim.avi demonstrates mapping with raw odometry localization  - Just mapping, not SLAM. The odometry errors accumulate quickly too large.
      A video haehnel-ScanMatching-anim.avi demonstrates  first real SLAM, localization on the basis of laser scan matching, only one estimate for pose, Mapping works.
      EKF SLAM video by Nebot can be run  in the 4_EKF_SLAM 2020.ppt -slide set.



    • Folder icon
      Lecture 6, March 17, 2021: Particle filter and Fast SLAM Folder
      Not available unless: You are a(n) Student

      Particle filter

      Particle filters are introduced in particle-filters 2020.pdf.

      Fast SLAM

      Particle distribution for robot pose, for each robot pose particle,  separate EKFs for positions of  landmarks. Own realization of grid type maps

      Fast SLAM: You can run videos in the fastslam 2020.ppt -slide set. pdf available, too.

      Some Fast SLAM videos added as separate files. In order to run videos, save them.

      bruceton-one-loop.avi ; fastslam-dmb-fastslam.avi ; haehnel-ScanMatchingFastSLAM-Seattle-anim-2.avi


    • Folder icon
      Lecture 7, March 23, 2021: Graph SLAM Folder
      Not available unless: You are a(n) Student

      Graph SLAM

      – Graph construction and optimization
      – Case forest SLAM
      – Advanced topics

      Zoom-video from remote lecture

      Supplementary paper, not required in Exam, Grisetti & al: A Tutorial on Graph-Based SLAM

    • Folder icon
      Lecture 8, March 24, 2021: Satellite positioning – GNSS technologies Folder
      Not available unless: You are a(n) Student

      Satellite positioning – GNSS technologies

      ● GNSS (Global Navigation Satellite System
      – Applications
      – Constellations: GPS, Galileo, GLONASS, Beidou
      ● GPS architecture and system
      ● Multi-sensor data input
      ● Position determination
      ● Error sources
      ● GNSS performance
      ● GNSS shortcomings
      ● Practicals for coding (formats, libs, links)

      Zoom-recording of the remote lecture


    • Folder icon
      Lecture 9, March 30, 2021: Pose Estimation, Inertial Navigation Systems (INS), Inertial Measurement Unit (IMU) Folder

      Pose Estimation, Inertial Navigation Systems (INS), Inertial Measurement Unit (IMU)

      • Introduction
      • Mathematics of Inertial Navigation
      • Errors and Aiding in Inertial Navigation
      • Example: Simple Odometry Aided AHRS
      • Use of cheap MEMS IMUs in robotics
      • Summary

      A DCM Based Attitude Estimation Algorithm for Low-Cost MEMS IMUs - paper as additional material, not required in exam

      Zoom-recording  of the remote lecture


    • Folder icon
      Lecture 10, March 31, 2021: Visual localization and object recognition Folder

      Visual localization and object recognition
      • Perception for Mobile Robots
      • Machine Vision
      • Stereo Vision
      • Filtering, Edges, and Point-features
      • Corner Detection
      • Blob features
      • Place Recognition, Line Extraction

    • Folder icon
      Lecture 11 April 6, 2021: Path and Motion Planning Folder
      Not available unless: You are a(n) Student
      Path and Motion Planning

      Graph based Path and Motion
      Planning, Indoor A*.

      Path and Motion
      Planning, Outdoor D*

      As supplementary material a journal paper, not required in the exam.

    • Folder icon
      Lecture 12, April 7, 2021: Outdoor Motion Planning and Control Folder

      Outdoor Motion Planning and Control

      Predictive Modeling

      – Braking
      – Turning
      – Vehicle Rollover
      – Wheel Slip and Yaw Stability

      Control of mobile robot
      1. Robot Trajectory Following
      2. Perception Based Control
      3. Steering Trajectory Generation
      4. Optimal and Model Predictive Control

      Nonlinear Model Predictive Control (NMPC)  in Semiautonomous Systems at Aalto
      Example: Autonomous driving of Tractor and Implement

      5. Intelligent Control

      Recording from the lecture

      A journal paper as a supplementary material, not required in the exam,

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