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