PCS927 Advanced robot control

Contents and structure

Advanced robot control algorithms taking into account the dynamical model of the robot is necessary to be able to interact safely with the environment.

The course covers modelling robot dynamics, dynamic control of robots, robot learning and robot sensor fusion.

The first part of the semester consists of lectures on the three main topics of the course; robot modelling and control, estimation, and robot learning. Relevant experimental labs and student-active hand-ins and presentations are mandatory activities for the three topics.

The second part of the course is a semester research project counting for 50% of the overall grade, and where students will do a dedicated research project on one or a combination of the course topics, and where the results should be documented in the form of a draft version of a scientific paper. The paper should include a scientific introduction section with an overview of the state of the art of the research problem addressed, as well as sections on methodology, results, analysis, discussion and conclusion. The paper can be related to the topic of the PhD-project of the student.

The programming software used in the course will predominantly be Matlab and Python.

Learning Outcome

Knowledge

The student…

• Has an overview of the state of the art for research within robot control, estimation and learning
• Has advanced knowledge of robot dynamics and advanced dynamic control methods for robot manipulators and selected types of mobile robots
• Has advanced knowledge on how to apply robot learning to problems
• Has advanced knowledge on how to fuse sensor information using different types of Kalman filters

Skills

The student…

• Can model robot dynamics for robot manipulators and selected types of mobile robots
• Can control robot manipulator dynamics and the dynamics of selected types of mobile robots
• Can apply robot learning to solve robot problems
• Can fuse different sensor inputs optimally using different types of Kalman filters

General competency

The student…

• Can take charge of advanced robot control development projects
• Can take charge of advanced robot control research projects
• Can communicate with robotic scientists using relevant terminology
• Can propose new and innovative robot control solutions to real-life problems

Entry requirements

None

Recommended previous knowledge

ELE306 Robotics or similar

Teaching methods

Lectures (both physical and digital), student-active learning activities in flipped classroom settings, mandatory assignments and experimental labs, and a semester project report in the form of a draft scientific paper.

Compulsory learning activities

None

Assessment

The course is graded pass/fail based on a project report and an oral exam. Each of the two components must result in a pass grade to obtain a pass grade for the course.

If a students fails one of the parts, that part can be re-taken separately.

Examination support material

All support materials are permitted.

More about examination support material