ACIT4820 Applied Robotics and Autonomous Systems Emneplan

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. Knowledge of programming in python and basic introductory course on control or dynamical systems is recommended.

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 
• advanced knowledge in modeling kinematics and dynamics of robotic systems 
• advanced knowledge in common sensor and actuator technologies used in robotics 
• have advanced knowledge of algorithms and methods used in state estimation, navigation, and motion planning
• a good understanding of the Robot Operating System (ROS) and software architectures used in robotic 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 
• model and analyze kinematic and dynamics of robotic systems 
• apply a number of algorithms and methods in state estimation, navigation, and motion planning
• 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 
• analyze how robotic and autonomous systems operate and design specific components using ROS and other software tools. 

Topics covered in this course: 

• Configuration space
• Rigid body motions
• Robot forward kinematics
• Velocity kinematics and statics
• Inverse kinematics 
• Robotics sensors and actuators 
• Navigation, state estimation and filtering algorithms 
• Motion planning 
• ROS Robot Operating System 

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 individual project. 

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

Four assignments in groups of 1-3 students (1000 - 2000 words per assignment)     

The assessment will be based on two part-exams:

1)     Individual project report (4000-6000 words). The project report counts 80% of the final grade.

2)     Individual project presentation (10 minutes). The presentations will be open to public.  The oral examination counts 20% of the final grade

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

The oral examination cannot be appealed.

New/postponed exam

In case of failed exam or legal absence, the student may apply for a new or postponed exam. New or postponed exams are offered within a reasonable time span following the regular exam. The student is responsible for registering for a new/postponed exam within the time limits set by OsloMet. The Regulations for new or postponed examinations are available in Regulations relating to studies and examinations at OsloMet.

All aids are permitted, provided the rules for plagiarism and source referencing are complied with.

Grade scale A-F.

Two internal examiners. External examiner is used periodically. 

Professor Alex Alcocer