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Embedded Perception Systems, 6 credits
Inbyggda perceptionssystem, 6 hp
TSBB18
Main field of study
Computer Science and EngineeringCourse level
First cycleCourse type
Programme courseExaminer
Mårten Wadenbäck, Yonghao XuDirector of studies or equivalent
Lasse AlfredssonEducation components
Preliminary scheduled hours: 10 hRecommended self-study hours: 150 h
ECV = Elective / Compulsory / Voluntary
Main field of study
Computer Science and EngineeringCourse level
First cycleAdvancement level
G2FCourse offered for
- Master of Science in Industrial Engineering and Management - International
- Master of Science in Industrial Engineering and Management
- Master's Programme in Data Science and Information Engineering
Prerequisites
Programming, Signals and Systems, Digital Circuits, Computer Systems.
Intended learning outcomes
After the course, the student is able to:
Goal 1: Implement a lego sorting robot based on resource constrained hard- and software.
Goal 2: Be able to explain and solve central problems in robotics, such as camera calibration, hand-eye-calibration, and forward and inverse kinematics.
Goal 3: Apply basic operations on images and video, such as reading, thresholding, and morphological operations.
Goal 4: Apply and explain important themes in prototype development, such as virtual environments and digital twins.
Course content
The course introduces automatic image processing, sensor calibration and inverse kinematics for robot control.
In a design and development project, consisting of 3 sub-projects, each group of 2-3 students will implement an automatic sorting robot. This will be done with the help of a Raspberry Pi, a camera, an Arduino and a robotic arm with grip claw. The camera is used to provide digital images of a number of lego pieces. These should be detected and their respective positions shall be related to the coordinate system of the robot, which picks up and sorts them by color. In the three sub-projects, the overall system is gradually built up. How these sub-assignments are solved is up to the students and the training in independent problem solving is a central sub-objective of the course.
Teaching and working methods
The working method of the course is very much related to prototype development where the students, from a concrete problem formulation, build a system that solves the problem with the help of available components and their documentation. The course has a somewhat PBL (problem-based learning) style, where students are expected to encounter sub-problems where they need to acquire new knowledge in order to solve the problem.
The students have support in the form of expert supervisors, who are available to discuss problems and recommend study material. The course starts with a lecture that introduces course objectives and working methods and gives an introduction to the area of computer vision with a focus on digital images, the imaging forming process for real cameras, image processing, homographies, hand-eye calibration and the open source libraries that are popular for image processing. The second lecture introduces inverse kinematics and how this problem can be solved. Furthermore, subject relevant seminars on e.g. system building, Linux and numerical optimisation can be held on demand.
Examination
| PRA2 | Projects | 6 credits | U, G |
Each subproject is examined in the form of a common demonstration that shows that the subproject is solved. This tests the "implement" part of goal 1, the "solve" part of goal 2, and the "apply" parts in goals 3-4. Each student must be able to explain each part of each subproject, which is tested through questions during the demonstrations. These questions, together with a brief (maximum one A4-page) summary of subprojects two and three, test the "explain" part of goals 2 and 4.
Grades
Two-grade scale, U, GOther information
Supplementary courses:
TSEA56 Electronics Engineering – Bachelor Project
TSBB09 Image Sensors,
TSBB08 Digital Image Processing,
TSBB15 Computer Vision,
TSRT08 Optimal Control,
TSBK07 Computer Graphics
About teaching and examination language
The teaching language is presented in the Overview tab for each course. The examination language relates to the teaching language as follows:
- If teaching language is “Swedish”, the course as a whole could be given in Swedish, or partly in English. Examination language is Swedish, but parts of the examination can be in English.
- If teaching language is “English”, the course as a whole is taught in English. Examination language is English.
- If teaching language is “Swedish/English”, the course as a whole will be taught in English if students without prior knowledge of the Swedish language participate. Examination language is Swedish or English depending on teaching language.
Other
The course is conducted in such a way that there are equal opportunities with regard to sex, transgender identity or expression, ethnicity, religion or other belief, disability, sexual orientation and age.
The planning and implementation of a course should correspond to the course syllabus. The course evaluation should therefore be conducted with the course syllabus as a starting point.
The course is campus-based at the location specified for the course, unless otherwise stated under “Teaching and working methods”. Please note, in a campus-based course occasional remote sessions could be included.
Department
Institutionen för systemteknikCourse literature
Other
| Code | Name | Scope | Grading scale |
|---|---|---|---|
| PRA2 | Projects | 6 credits | U, G |
Each subproject is examined in the form of a common demonstration that shows that the subproject is solved. This tests the "implement" part of goal 1, the "solve" part of goal 2, and the "apply" parts in goals 3-4. Each student must be able to explain each part of each subproject, which is tested through questions during the demonstrations. These questions, together with a brief (maximum one A4-page) summary of subprojects two and three, test the "explain" part of goals 2 and 4.
Other
Note: The course matrix might contain more information in Swedish.
I = Introduce, U = Teach, A = Utilize
| I | U | A | Modules | Comment | ||
|---|---|---|---|---|---|---|
| 1. DISCIPLINARY KNOWLEDGE AND REASONING | ||||||
| 1.1 Knowledge of underlying mathematics and science (G1X level) |
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| 1.2 Fundamental engineering knowledge (G1X level) |
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| 1.3 Further knowledge, methods, and tools in one or several subjects in engineering or natural science (G2X level) |
X
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PRA2
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| 1.4 Advanced knowledge, methods, and tools in one or several subjects in engineering or natural sciences (A1X level) |
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| 1.5 Insight into current research and development work |
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| 2. PERSONAL AND PROFESSIONAL SKILLS AND ATTRIBUTES | ||||||
| 2.1 Analytical reasoning and problem solving |
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| 2.2 Experimentation, investigation, and knowledge discovery |
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X
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PRA2
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| 2.3 System thinking |
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X
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X
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PRA2
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| 2.4 Attitudes, thought, and learning |
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X
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PRA2
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| 2.5 Ethics, equity, and other responsibilities |
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X
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PRA2
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| 3. INTERPERSONAL SKILLS: TEAMWORK AND COMMUNICATION | ||||||
| 3.1 Teamwork |
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X
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PRA2
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| 3.2 Communications |
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PRA2
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| 3.3 Communication in foreign languages |
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| 4. CONCEIVING, DESIGNING, IMPLEMENTING AND OPERATING SYSTEMS IN THE ENTERPRISE, SOCIETAL AND ENVIRONMENTAL CONTEXT | ||||||
| 4.1 External, societal, and environmental context |
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| 4.2 Enterprise and business context |
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| 4.3 Conceiving, system engineering and management |
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PRA2
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| 4.4 Designing |
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PRA2
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| 4.5 Implementing |
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PRA2
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| 4.6 Operating |
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| 5. PLANNING, EXECUTION AND PRESENTATION OF RESEARCH DEVELOPMENT PROJECTS WITH RESPECT TO SCIENTIFIC AND SOCIETAL NEEDS AND REQUIREMENTS | ||||||
| 5.1 Societal conditions, including economic, social, and ecological aspects of sustainable development for knowledge development |
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| 5.2 Economic conditions for knowledge development |
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| 5.3 Identification of needs, structuring and planning of research or development projects |
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| 5.4 Execution of research or development projects |
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| 5.5 Presentation and evaluation of research or development projects |
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X
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PRA2
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