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Syllabus for

Academic year
TME290 - Autonomous robots
Autonoma robotar
 
Syllabus adopted 2018-02-20 by Head of Programme (or corresponding)
Owner: MPCAS
7,5 Credits
Grading: TH - Pass with distinction (5), Pass with credit (4), Pass (3), Fail
Education cycle: Second-cycle
Major subject: Engineering Physics
Department: 30 - MECHANICS AND MARITIME SCIENCES


Teaching language: English
Application code: 11118
Open for exchange students: No
Block schedule: B
Maximum participants: 48

Module   Credit distribution   Examination dates
Sp1 Sp2 Sp3 Sp4 Summer course No Sp
0116 Examination 7,5c Grading: TH   7,5c   Contact examiner

In programs

MPALG COMPUTER SCIENCE - ALGORITHMS, LANGUAGES AND LOGIC, MSC PROGR, Year 1 (elective)
MPAUT AUTOMOTIVE ENGINEERING, MSC PROGR, Year 1 (elective)
MPCAS COMPLEX ADAPTIVE SYSTEMS, MSC PROGR, Year 1 (compulsory elective)
MPCAS COMPLEX ADAPTIVE SYSTEMS, MSC PROGR, Year 2 (elective)
MPSYS SYSTEMS, CONTROL AND MECHATRONICS, MSC PROGR, Year 1 (elective)
MPHPC HIGH-PERFORMANCE COMPUTER SYSTEMS, MSC PROGR, Year 1 (elective)

Examiner:

Ola Benderius


Eligibility

General entry requirements for Master's level (second cycle)
Applicants enrolled in a programme at Chalmers where the course is included in the study programme are exempted from fulfilling the requirements above.

Specific entry requirements

English 6 (or by other approved means with the equivalent proficiency level)
Applicants enrolled in a programme at Chalmers where the course is included in the study programme are exempted from fulfilling the requirements above.

Course specific prerequisites

Basic mathematical and programming skills are required. It is an advantage, but not absolutely necessary, to be familiar with modern C++ (version 11 or later) and Linux systems.

Aim

The course aims at giving the students an understanding of design principles for autonomous systems, both robots and software agens, and also gives students the opportunity to apply their knowledge in practice through the construction of a simple autonomous robot.

Learning outcomes (after completion of the course the student should be able to)

  • Describe properties of common types of robotic hardware, including sensors, actuators, and computational nodes
  • Apply modern software development and deployment strategies connected with autonomous robots
  • Set up and use equations of motion of wheeled autonomous robots
  • Apply basic sensor fusion
  • Set up and use computer simulations of autonomous robots
  • Apply global and local navigation of autonomous robots
  • Apply the basics of behavior-based robotics and evolutionary robotics
  • Apply methods for decision making in autonomous robots
  • Discuss the potential role of autonomous robots in society, including social, ethical, and legal aspects
  • Discuss technical challenges with autonomous robots in society

Content

  • Survey of robot related hardware
  • Modern software development for autonomous robots
  • Kinematics and dynamics for autonomous robots
  • Simulation of autonomous robots
  • Perception and sensor fusion for autonomous robots
  • Behaviour modeling for autonomous robots
  • Practical work related to autonomous robots

Organisation

  • Lectures
  • Home assignments, individual (mandatory)
  • Project including report and demonstration, groups of 2-4 students (mandatory)

Literature

Lecture notes, scientific papers, and handouts. The material will be made available via the course web page.

Examination including compulsory elements

  • Home assignments (individual)
  • Project work (individual and in group)
  • Project demonstration (group)
  • Project report (group)
The results from each activity are combined to give each student an individual grade. To pass the course, the student needs to actively participate in all mandatory activities.


Published: Mon 28 Nov 2016.