ACIT4820 Applied Robotics and Autonomous Systems Course description

This course provides a hands-on overview of common theories and methods used in the design of robotic and autonomous systems. The course is organized around weekly practical labs and lectures that complement each other. The student will get hands-on experience with the technologies, algorithms, and architecture of robotic and autonomous systems. The course uses examples from aerial, space, ground, underwater, and industrial robotic and autonomous systems.

Knowledge of linear algebra, vector calculus and basic statistics and probability.

No formal requirements over and above the admission requirements.

The student should have the following outcomes upon completing the course:

Knowledge:

Upon successful completion of the course, the student should:

• have advanced knowledge on robotic and autonomous systems components and architecture
• have advanced knowledge in modeling kinematics and dynamics of robotic systems
• have advanced knowledge in common sensor and actuator technologies used in robotics
• have advanced knowledge of algorithms and methods used in state estimation, navigation, motion planning, and computer vision.
• have a good understanding of the Robot Operating System (ROS) and software architectures used in robotic and autonomous systems
• have a good understanding of ML/AI methods used in robotics and autonomous systems

Skills:

Upon successful completion of the course, the student:

• can analyze a robotic and autonomous systems with regard to its components, architecture, and their purpose
• can model and analyze kinematic and dynamics of robotic systems
• can apply a number of algorithms and methods in state estimation, navigation, motion planning, and computer vision
• can analyze and implement solutions based on Robot Operating System (ROS)

General competence:

Upon successful completion of the course, the student:

• can discuss the role of robotic and autonomous systems in a number of practical applications
• can analyze how robotic and autonomous systems operate and design specific components using ROS and other software tools.

This course will feature weekly lectures and lab work to provide both theoretical and hands- on experience. Students will work in groups and complete assignments given to them. The student will supplement the lectures and lab with their own reading. The students will also work on a group project.

The following required coursework must be approved before the student can take the exam:

• Four compulsory group assignments.

Exam autumn 2020 due to Covid-19:

• Individual digital home exam 48 hours duration. 50%
• Group (2-4 students) project work (15-30 pages). 50%

For the group project, both the submitted code/program and the report will be evaluated for the project grade. The comprehensiveness of the code/program is evaluated with the assumption that each student in the group has committed about 60 hours towards developing the solution.

Both exams must be passed in order to pass the course.

The exam grade can be appealed.

[Exam earlier:]

• Individual written exam 3 hours duration. 50%
• Group (2-4 students) project work (15-30 pages). 50%

For the group project, both the submitted code/program and the report will be evaluated for the project grade. The comprehensiveness of the code/program is evaluated with the assumption that each student in the group has committed about 60 hours towards developing the solution.

Both exams must be passed in order to pass the course.

The exam grade can be appealed.

Aids autumn 2020:

All aids are permitted, except communication with others

[Aids earlier:]

None.

For the final assessment a grading scale from A to E is used, where A denotes the highest and E the lowest pass grade, and F denotes a fail.

Two internal examiners. External examiner is used periodically.