700.382 (24W) Robotics Fundamentals

Wintersemester 2024/25

Registration possible from
30.08.2024 00:00

First course session
07.10.2024 10:00 - 11:30 HS 6 On Campus
Next session:
14.10.2024 10:00 - 11:30 HS 6 On Campus

Overview

Lecturer
Course title german Robotics Fundamentals
Type Lecture - Course (continuous assessment course )
Course model Attendance-based course
Hours per Week 2.0
ECTS credits 4.0
Registrations 0 (30 max.)
Organisational unit
Language of instruction Englisch
Course begins on 07.10.2024
Seniorstudium Liberale Yes

Time and place

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Course Information

Intended learning outcomes

The course "Robotics Fundamentals" provides students with a comprehensive understanding of the foundational principles and practical applications of robotics. Through a combination of theoretical knowledge and hands-on learning, students will explore the interdisciplinary nature of robotics and its significance in various industries, including manufacturing, healthcare, transportation, and more.

Core Objective:The primary objective of this course is to equip students with a solid foundation in robotics by covering essential topics such as robotics overview, sensor and actuator technologies, human-robot interaction, mechanical design, kinematics, path planning, probabilistic robotics, and robot control. By the end of the course, students will possess a comprehensive understanding of the fundamental concepts, methodologies, and tools used in robotics.

Expected Outcome:Upon completion of the course, students will be able to:

  1. Demonstrate a broad understanding of the history, development, and current applications of robotics.
  2. Identify and classify various sensors and actuators used in robotics and understand their working principles.
  3. Analyze the interaction between humans and robots, considering safety, collaboration, and ethical considerations.
  4. Apply mechanical design principles to create efficient and functional robotic systems.
  5. Solve direct and inverse kinematics problems to determine the position and orientation of robot manipulators.
  6. Design and implement path planning algorithms for autonomous mobile robots.
  7. Understand first simple basics of probabilistic robotics techniques for localization, mapping, and perception in uncertain environments.
  8. Understand the basics of robot control and AI reasoning, including decision-making processes in robotics.
  9. Evaluate the use of AI tools and frameworks for robotics design and simulation.

Teaching methodology

Through a combination of face-to-face lectures, blended learning, weekly group homework assignments, and group mini-projects, students will develop practical skills and hands-on experience in applying robotics concepts. The course aims to foster critical thinking, problem-solving abilities, and teamwork among students, enabling them to tackle real-world challenges in the field of robotics.

Course content

Course Contents:

  1. General Introduction
  • Introduction to robotics as a multidisciplinary field
  • History and development of robotics
  1. Overview and Applications of Robotics
  • Different types of robots and their applications in industries, medicine, space exploration, etc.
  • Ethics and social implications of robotics and artificial intelligence
  1. Sensors and Actuators
  • Classification of sensors and actuators in robotics
  • Applications and working principles of selected sensors and actuators
  1. Human-Robot Interaction
  • Fundamentals of human-robot interaction
  • Safety and collaboration between humans and robots
  1. Mechanical Design
  • Basics of mechanical design for robots
  • Materials and construction methods for robots
  1. Direct Kinematics
  • Modeling direct kinematics
  • Calculation of end effector position and orientation
  1. Inverse Kinematics
  • Modeling inverse kinematics
  • Calculation of joint angles for a desired end effector position and orientation
  1. Self-Driving Vehicles
  • Fundamentals of autonomous vehicles
  • Sensors and algorithms for environment perception and planning
  1. Path Planning
  • Basics of path planning for mobile robots
  • Algorithms for finding collision-free paths
  1. Introduction to Probabilistic Robotics (ABC for Beginners)
  • Bayes filters and probabilistic estimation techniques
  • Application in localization and mapping
  1. Brief Introduction to Robot Control and AI Reasoning (ABC for Beginners)
  • Control techniques for robots
  • Fundamentals of AI reasoning for robotic decision-making
  1. Overview of AI Tools for Robotics Design and Robot Simulation
  • Introduction to tools and frameworks for robotics simulation
  • Application of AI technologies in robotics

       13.  Some future Robotics  concepts:
                # Robotics-as-a-Service
                # Educational Robotics
                #  The future of robotics

Prior knowledge expected

To successfully engage with the course "Robotics Fundamentals," students are expected to have a basic understanding of mathematics, system theory, and information technology (IT). While the course aims to provide a comprehensive introduction to robotics, familiarity with the following concepts will be advantageous:

  1. Mathematics: Students should have a solid grasp of algebra, trigonometry, and calculus. Concepts such as vectors, matrices, differential equations, and basic mathematical operations will be used throughout the course.

  2. System Theory: A foundational understanding of system theory, including concepts like feedback control, state variables, and transfer functions, will be beneficial. Students should be familiar with fundamental principles related to linear systems and system modeling.

  3. Information Technology (IT): Basic knowledge of IT concepts and programming will be helpful for implementing algorithms and working with robotic systems. Familiarity with programming languages, such as Python or C++, and concepts like data structures, loops, and conditional statements will be advantageous.

While the course will cover the fundamental principles of robotics, it is designed to accommodate students with varying levels of prior knowledge in these areas. Students without extensive background in mathematics, system theory, or IT will still be able to grasp the core concepts and build their understanding throughout the course. Supplementary resources and support will be provided to ensure students can bridge any knowledge gaps and succeed in the learning process.

Literature

Selected sources:

Niku, Saeed B. Introduction to robotics: analysis, control, applications. John Wiley & Sons, 2020.

Bartneck, Christoph, et al. Human-robot interaction: An introduction. Cambridge University Press, 2020.

Demir, Kadir Alpaslan, Gözde Döven, and Bülent Sezen. "Industry 5.0 and human-robot co-working." Procedia computer science 158 (2019): 688-695.

Tzagkaraki, Effransia, Stamatios Papadakis, and Michail Kalogiannakis. "Exploring the Use of Educational Robotics in primary school and its possible place in the curricula." Educational Robotics International Conference. Cham: Springer International Publishing, 2021.

Mizrahi, Joseph, ed. Kinematics: Analysis and Applications. BoD–Books on Demand, 2019.

Ceccarelli, Marco. Fundamentals of mechanics of robotic manipulation. Vol. 112. Springer Nature, 2022.

Taulli, Tom. "The robotic process automation handbook." The Robotic Process Automation Handbook. https://doi. org/10.1007/978-1-4842-5729-6 (2020).

Kinematics of Robot Manipulators (The MIT Press)
Author:  J. M. McCarthy (Editor)

Springer Handbook of Robotics (Springer Handbooks)
by Bruno Siciliano and Oussama Khatib
Publcation Date:  27 Jul 2016

Examination information

Im Fall von online durchgeführten Prüfungen sind die Standards zu beachten, die die technischen Geräte der Studierenden erfüllen müssen, um an diesen Prüfungen teilnehmen zu können.

Examination methodology

Written or oral exam

Examination topic(s)

see Chapter 0 in Moodle

Assessment criteria / Standards of assessment for examinations

The final Assessment (Grade) will be determined as follows:

  • Attendance and participation: 5%
  • Weekly homework assignments: 20%
  • Group mini-projects: 15%
  • Final exam: 60%

Grading scheme

Grade / Grade grading scheme

Position in the curriculum

  • Master's degree programme Information and Communications Engineering (ICE) (SKZ: 488, Version: 15W.1)
    • Subject: Information and Communications Engineering: Supplements (NC, ASR) (Compulsory elective)
      • Wahl aus dem LV-Katalog (Anhang 4) ( 0.0h VK, VO, KU / 14.0 ECTS)
        • 700.382 Robotics Fundamentals (2.0h VC / 4.0 ECTS)
  • Master's degree programme Information and Communications Engineering (ICE) (SKZ: 488, Version: 15W.1)
    • Subject: Technical Complements (NC, ASR) (Compulsory elective)
      • Wahl aus dem LV-Katalog (Anhang 5) ( 0.0h VK, VO, KU / 12.0 ECTS)
        • 700.382 Robotics Fundamentals (2.0h VC / 4.0 ECTS)
  • Master's degree programme Information and Communications Engineering (ICE) (SKZ: 488, Version: 15W.1)
    • Subject: Autonomous Systems and Robotics: Fundamentals (ASR) (Compulsory subject)
      • Robotics ( 0.0h VK / 4.0 ECTS)
        • 700.382 Robotics Fundamentals (2.0h VC / 4.0 ECTS)
  • Master's degree programme Information and Communications Engineering (ICE) (SKZ: 488, Version: 15W.1)
    • Subject: Information and Communications Engineering: Supplements (NC, ASR) (Compulsory elective)
      • Wahl aus dem LV-Katalog (Anhang 4) ( 0.0h VK, VO, KU / 14.0 ECTS)
        • 700.382 Robotics Fundamentals (2.0h VC / 4.0 ECTS)
  • Master's degree programme Information and Communications Engineering (ICE) (SKZ: 488, Version: 15W.1)
    • Subject: Technical Complements (NC, ASR) (Compulsory elective)
      • Wahl aus dem LV-Katalog (Anhang 5) ( 0.0h VK, VO, KU / 12.0 ECTS)
        • 700.382 Robotics Fundamentals (2.0h VC / 4.0 ECTS)
  • Master's degree programme Information and Communications Engineering (ICE) (SKZ: 488, Version: 15W.1)
    • Subject: Autonomous Systems and Robotics (WI) (Compulsory elective)
      • Robotics ( 0.0h VK / 4.0 ECTS)
        • 700.382 Robotics Fundamentals (2.0h VC / 4.0 ECTS)
  • Master's degree programme Information and Communications Engineering (ICE) (SKZ: 488, Version: 22W.1)
    • Subject: Autonomous Systems and Robotics: Fundamentals (Compulsory subject)
      • 2.1 Robotics Fundamentals ( 0.0h VC / 4.0 ECTS)
        • 700.382 Robotics Fundamentals (2.0h VC / 4.0 ECTS)

Equivalent courses for counting the examination attempts

Wintersemester 2023/24
  • 700.382 VC Robotics Fundamentals (2.0h / 4.0ECTS)
Wintersemester 2022/23
  • 700.382 VC Robotics Fundamentals (2.0h / 4.0ECTS)
Wintersemester 2021/22
  • 700.382 VC Robotics Fundamentals (2.0h / 4.0ECTS)
Wintersemester 2020/21
  • 700.382 VC Robotics Fundamentals (2.0h / 4.0ECTS)
Wintersemester 2019/20
  • 700.382 VC Robotics Fundamentals (2.0h / 4.0ECTS)
Wintersemester 2018/19
  • 700.382 VC Robotics Fundamentals (2.0h / 4.0ECTS)
Wintersemester 2017/18
  • 700.382 VC Robotics Fundamentals (2.0h / 4.0ECTS)
Wintersemester 2016/17
  • 700.382 VC Robotics Fundamentals (2.0h / 4.0ECTS)
Wintersemester 2015/16
  • 700.382 VC Robotics Fundamentals (2.0h / 4.0ECTS)