Advanced Robotics (Autumn 2019)

Abstract

This course introduces students to the broad field of robotics predominately from a software perspective.

Description

This course is the last course in the robot specialization. The course provides an introduction to robotics and starts by answering general questions such as what a robot is, their origins, types, and applications. It then introduces the key approaches to robot control and explores the pros and cons of each.  The course finally covers the advanced topics of robot learning and bio-inspired robots in addition to current robot research topics at ITU. In addition to the theory, the course also has a significant practical, hands-on dimension that comprises introduction to relevant software tools (simulators and operating systems) and hands-on experiments with simulated and physical robots.

Formal prerequisites

Robotics is interdisciplinary by nature and research topics range from fundamental modelling of robot physics over programming and design all the way to ethical and philosophical questions. Hence, students with highly diverse backgrounds are welcome on this course. However, the course as taught at ITU has its root in Computer Science and will be taught predominately from this perspective. Hence, it is required that the student has basic programming skills (e.g. obtained from an introduction to programming course). Although not required, it is also recommended and useful to have taken the sister course:"How to build almost anything" which largely covers how robots are built. Finally, fundamental skills in math (e.g. from "Linear Algebra and Probability") will make some of the technical content more easily accessible. The course also includes some machine learning hence knowledge in this area is also useful, but not mandatory.

Intended learning outcomes

After the course, the student should be able to:

• Describe what a robot is, their origin, types, and applications
• Describe, compare, and apply robot control stategies
• Apply robot software tools (simulation, operating systems)
• Apply bio-inspired solutions and machine learning appropriately in robotics
• Formulate and reflect on robot solutions to real-world problems

Learning activities

The learning activities will be tailored such that there is a suitable balance between obtaining knowledge, applying it, and reflecting on the knowledge. Hence, the learning activities changes between lectures, small exercises, guided introductions to tools and robots, and larger report to allow for deeper reflection of the learned material.

Mandatory activities

The students have to get two mandatory reports approved to attend the exam. The reports will be based on mini-projects made in small groups and will typically cover design, implementation, and experimentation with simulated or physical robots.

The student will receive the grade NA (not approved) at the ordinary exam, if the mandatory activities are not approved and the student will use an exam attempt.

Course literature

The course literature is published in the course page in LearnIT.

Ordinary exam

Exam type:
C: Submission of written work, external (7-trinsskala)
Exam variation:
CG: Submission of written work for groups.
Exam description:
The final project and the resulting exam report will be made in the context of a robot competition. The exam report will describe the group's robotic solution, document the developed robotic solution using experimetal data, and finally reflect on the solution based on the theoretical material of the course. 
Group size: 1-4 persons, preferably 3.

Time and date