Intelligent Autonomous Systems

2018/2019

Content, progress and pedagogy of the module

The module adds to the knowledge obtained in 1st Semester.

Learning objectives

Knowledge

  • Have gained knowledge and experience of how to develop autonomous solution with advanced sensing, big data, machine learning, vision and perception technologies.
  • Have gained knowledge and experience of how to design intelligent autonomous systems and networks with related concepts, theories, methods and tools, based on demand characteristics in different industry/business contexts.
  • Have gained knowledge and experience of how to evaluate the performance of intelligent autonomous systems and networks in a dynamic application/commercial environment.

Skills

  • Be able to analyse the system demand in a real case and specify its characteristics.
  • Be able to develop an intelligent autonomous solution with related technologies, aiming to meet the identified demands.
  • Be able to conduct a cost and benefit analysis for the proposed solution to justify economic feasibility.
  • Be able to comprehensively evaluate the performance of intelligent autonomous systems and networks in a dynamic application/commercial environment.

Competences

  • Have the ability to interpret the differences of intelligent autonomous solutions compared with conventional ones in a specific context, e.g. autonomous robots, production or transportation logistics.
  • Have the ability to formulate a project to target and solve an intelligent autonomous solution in a real case, as well as planning and conducting such a project with team work.
  • Have the ability to estimate and assess the achievement of logistic and economic objectives in intelligent autonomous solutions in a specific context.
  • Have the ability to analyse the limitations, opportunities, and the survivability of an intelligent autonomous system/network against more complex and contested environments.

Type of instruction

The module is carried out as group-based, problem-oriented project work. The group work is carried out as an independent work process in which the students themselves organise and coordinate their workload in collaboration with a supervisor. The project is carried out in groups with normally no more than 6 members.



Extent and expected workload

Since it is a 15 ECTS course module the expected workload is 450 hours for the student.

Exam

Exams

Name of examIntelligent Autonomous Systems
Type of exam
Oral exam based on a project
ECTS15
Assessment7-point grading scale
Type of gradingExternal examination

Facts about the module

Danish titleIntelligente autonome systemer
Module codeM-AS-K2-1
Module typeProject
Duration1 semester
SemesterSpring
ECTS15
Empty-place SchemeYes
Location of the lectureCampus Copenhagen
Responsible for the module

Organisation

Study BoardStudy Board of Industry and Global Business Development
FacultyFaculty of Engineering and Science
SchoolSchool of Engineering and Science