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Robot Programming and IoT (5cr)

Code: R504TL130-3003

General information


Enrollment
06.10.2025 - 18.01.2026
Registration for the implementation has begun.
Timing
19.01.2026 - 17.04.2026
The implementation has not yet started.
Number of ECTS credits allocated
5 cr
Mode of delivery
Contact learning
Teaching languages
english
Seats
0 - 50
Teachers
Tommi Kokko
Teacher in charge
Tommi Kokko
Course
R504TL130

Evaluation scale

H-5

Content scheduling

Utilising Robot Operating Systems (ROS2) in robot programming
Internet of Robotic Things (IoRT)
Security aspect of a robot
Reading the robot sensor data and implementing data processing
Building the functional logic for a robot
Robot data transfer and use of external services, robots as part of IoT-system
Mobile robotics specification, design and implementation

Objective

The student is able to use the technologies and operating systems in programming a robot with connectivity capabilities. The student knows how to read and process robot sensor data and implement required functionalities with a robot. The student is able to select and implement the appropriate sensing systems and mechanics for further utilisation in robot programming and control. The student is able to use various hardware and software interfaces. Students know how to use robot programming tools and know how to use tools for robot do assigned tasks.

Content

Utilising Robot Operating Systems (ROS) in robot programming
Internet of Robotic Things (IoRT)
Reading the robot sensor data and implementing data processing
Building the functional logic for a robot
Kinematics in robotics
Robot data transfer and use of external services, robots as part of IoT-system
Mobile robotics specification, design and implementation

Location and time

The course includes scheduled lectures and laboratory work according to the schedule in the B220 IoT laboratory.

Materials

Material distributed by the teacher in the Moodle workspace (instructions, examples, videos). The software used in the study is installed during the lectures.



The course utilizes the ARENA traffic light model. In the course, the use of artificial intelligence is allowed, may be used, must be reported (yellow).


Teaching methods

The study includes inquiry-based learning, problem-based learning, lectures, and demonstrations in the laboratory (exercises with equipment and software), combining IoT, robotics, and embedded systems.

Exam schedules

No exam.

Grade increase and re-grading of failed grades:

It is possible to increase the grade of a course by the end of the following semester. The method of increase will be discussed on a case-by-case basis with the responsible teacher.

Completion alternatives

Students can complete course assignments alone, in pairs or in groups. Each student returns their own report to the Moodle workspace return box, even if the report was done in pairs/groups.

Student workload

The scope of the course is 5 credits, which means a total workload of approximately 135 hours.
The workload is divided on average as follows:
Working in accordance with the lesson plan 40h
Independent work 95h

Assessment criteria, satisfactory (1)

The student masters the basic concepts of robotics and IoT-systems. The student understands the operating system and programming principles required for robot programming and is able execute commands. The student is able to read data from robot interface and implement simple operations. The student can search for the necessary information about robotics and understand the operation of sensors. The student knows how to use actuators.

Assessment criteria, good (3)

The student is versatile in utilization of robot technologies and is able to program various functionalities for robots. The student can technically define the device and program functions of the robot. The student is able to choose appropriate algorithms for the tasks, plan own programming tasks and solve programming problems. The student knows how to design a device platform and implement a robot system and related programmatic intelligence.

Assessment criteria, excellent (5)

The student is versatile in utilization of robot technologies and is able to program advanced functionalities for robots. The student is able to use advanced technologies and algorithms in solving demanding problems. The student knows how to define, plan, implement and test a IoRT-system. The student can use sensors and actuators in a robot in an advanced way. Able to independently develop the robot and its functions.

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