| Language of instruction : English |
| Exam contract: not possible |
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Sequentiality
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No sequentiality
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| Degree programme | | Study hours | Credits | P1 SBU | P1 SP | 2nd Chance Exam1 | Tolerance2 | Final grade3 | |
 | Master of Electromechanical Engineering Technology | Compulsory | 108 | 4,0 | 108 | 4,0 | Yes | Yes | Numerical |  |
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| | | Learning outcomes |
- EC
| EC1 - The holder of the degree thinks and acts professionally with an appropriate engineering attitude and continuous focus on personal development, adequately communicates, effectively cooperates, takes into account the sustainable, economical, ethical, social and/or international context and is hereby aware of the impact on the environment. | | | - DC
| DC-M8 - The student can evaluate knowledge and skills critically to adjust own reasoning and course of action accordingly. | | | | - BC
| the student is able to follow up and to understand through private study the evolutions in robotics and vision technology in recent research, to assess the relevance and usefulness of research and to critically reflect on this scientific research. | | | - DC
| DC-M9 - The student can communicate in oral and in written (also graphical) form. | | | | - BC
| the student is able to communicate in a structured way, both orally and in written form, the essence and the results of scientific research (article), to correctly refer to sources and to correctly use robotics and vision terminology. | | | - DC
| DC-M12 - The student shows a suitable engineering attitude. | | | | - BC
| the student is able to truthfully document robotics and vision solutions/applications and to refer to sources, is curious to understand technology (to unravel problems) and displays a researcher's attitude (how do systems work), to remedy own shortcomings (e.g. aspects that are not understood from a paper) through private study, adhere to the quality requirements for the review of a scientific article, and display realism (importance or usefulness of scientific research). | - EC
| EC4 - The holder of the degree has advanced knowledge of and insight in the principles and applications in automation, electrical engineering, mechanical design and materials and production, in which he/she can independently identify and critically analyse complex, practice-oriented design or optimisation problems, and methodologically create solutions with eye for data processing and implementation and with attention to the recent technological developments. | | | - DC
| DC-M1 - The student has knowledge of the basic concepts, structures and coherence. | | | | - BC
| the student possesses knowledge of the key components and terminology of a (mobile) robot (system) and of computer vision. | | | - DC
| DC-M2 - The student has insight in the basic concepts and methods. | | | | - BC
| the student possesses insight in the similarities and differences between mobile robots and robot manipulators, and in the modelling of a robot with (position and velocity) coordinate transforms; the student understands the background of and can apply basic probabilistic estimation techniques (e.g. Bayes' rule), and can apply basic vision algorithms. | | | - DC
| DC-M3 - The student can recognize problems, plan activities and perform accordingly. | | | | - BC
| the student is able to autonomously choose a scientific paper related to robotics and vision, and to make links with the course where possible. | | | - DC
| DC-M4 - The student can gather, measure or obtain information and refer to it correctly. | | | | - BC
| the student can search for and understand a scientific article, by purposefully gathering and processing additional scientific or technical information that may be required. | | | - DC
| DC-M5 - The student can analyze problems, logically structure and interpret them. | | | | - BC
| the student is able to analyse and find errors in a kinematic robot model, to indicate the advantages and disadvantages of a solution or technique for a concrete robotics and vision problem, and to evaluate and process information from a scientific article. | | | - DC
| DC-M6 - The student can select methods and make calculated choices to solve problems or design solutions. | | | | - BC
| the student can make a motivated choice of a robot system for a certain task, and can autonomously compute parts of a (mobile) robot or vision system. | | | - DC
| DC-M7 - The student can use selected methods and tools to implement solutions and designs. | | | | - BC
| the student can correctly apply the discussed robotics and vision algorithms on parts of a (mobile) robot or vision system. | | | - DC
| DC-M8 - The student can evaluate knowledge and skills critically to adjust own reasoning and course of action accordingly. | | | | - BC
| the student is able to follow up and to understand through private study the evolutions in robotics and vision technology in recent research, to assess the relevance and usefulness of research and to critically reflect on this scientific research. |
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| | EC = learning outcomes DC = partial outcomes BC = evaluation criteria |
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Robotics and sensor technology builds on knowledge of mathematics (algebra, matrix calculus, statistics), control theory (feedback, position and velocity control) and measurement systems (position or distance measurement, force measurement). Furthermore, robotics is related to electricity (electric motors), hydraulics and pneumatics (drives), mechanics, and power electronics.
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General description
Robotics and sensor technology is an engineering course in the domain of mechatronics: integrating mechanics, electronics and computer science. This is to a large degree a descriptive course on the current state of the art and the terminology of robot technology (composition, drives, control, programming, applications). Nevertheless, a number of specific techniques are discussed in more detail, such as coordinate transformations, robot modeling and (basic) probabilistic state estimation and localisation. Additionally, components, image formation and image processing of vision systems are discussed. The part on vision systems addresses the recent rise of industrial cameras for a wide range of automation applications, even outside robotics.
Content of lectures and exercise sessions
Mobile robotics:
- wheel types and mobile robot kinematics
- probabilistic localisation and mapping
- obstacle avoidance and path planning
- mobile robot control
Robot manipulators:
- position and orientation of rigid objects, coordinate transformation matrices
- forward and inverse kinematics
- workspace analysis, analysis of singularities;
- robot components
Sensors:
- light and colour
- lenses, cameras, camera model
- image processing (monadic and spatial operations)
- feature extraction (region, line and point features)
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Lecture ✔
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Small group session ✔
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Exercises ✔
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Report ✔
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Period 1 Credits 4,00
| Evaluation method | |
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| Written exam | 70 % |
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| Transfer of partial marks within the academic year | ✔ |
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| Oral exam | 30 % |
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| Transfer of partial marks within the academic year | ✔ |
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| Other | Discussion of scientific paper and summary (Robotics and vision) |
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| Additional information | - Written exam, closed book (70%): test of the knowledge about the properties of a mobile robot and robot manipulator and frequently adopted algorithms, the skill to model and the knowledge and understanding of vision technology. The use of a graphical calculator is permitted provided that the permanent memory and the volatile memory are empty before the start of the exam.
- oral defense of a review of a scientific paper (30%), summarised in 2/3 pages, on a research topic selected by the student but related to the course content and approved by the professor; use of the summarised article is permitted.
C. Overall remarks
(1) If the student does not participate in the 2nd exam period, his score from the 1st exam period remains on either part (oral or written exam). (2) The student may choose to still redo an evaluation on a part, but then (s)he must explicitly notify the professor. |
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Second examination period
| Evaluation second examination opportunity different from first examination opprt | |
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| Compulsory course material |
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For some of the robotics-related exercise sessions, Matlab is needed. Each student can install Matlab on his own laptop or PC. A student license is available via UHasselt. |
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| Recommended reading |
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- Introduction to Autonomous Mobile Robots,Roland Siegwart, Illah Reza Nourbakhsh, Davide Scaramuzza,2,9780262015356,Available as e-book: https://ebookcentral.proquest.com/lib/ubhasselt/detail.action?docID=3339191
- Robotics, vision and control,Peter Corke,2,Springer,9783319544120,pdf beschikbaar via limo-libis, also available as e-book: https://link.springer.com/book/10.1007%2F978-3-319-54413-7
- Introduction to Robotics: Mechanics and Control,John J. Craig,4,Pearson,9780133489798
- Robotics: modelling, planning and control,Bruno Siciliano, Lorenzo Sciavicco, Luigi Villani, Giuseppe Oriolo,1,Springer,9781849966344,pdf beschikbaar via limo-libis
- Springer Handbook of Robotics,Bruno Siciliano, Oussama Khatib,2,Springer,9783319325507,pdf beschikbaar via limo-libis
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| Recommended course material |
| |
- articles from robot conferences, journals or other publications; mostly available through limo-libis;
- extended background information on computer vision is available via the course's electronic learning platform.
|
|
|
| Remarks |
| |
Fit within the curriculum:
This course is part of the domain of automation technology. Robotics and sensor technology is a very broad research and application domain, requiring knowledge and integration of many courses of the curriculum such as mathematics, mechanics, control theory, measurement systems, electricity, etc.
Relation with industry:
Robotics and sensor technology have been adopted in manufacturing industry and many other sectors (medicine, agriculture, care, logistics, food, pharma) for a long time already. They are increasingly needed in combination in order to obtain "smart", sensor-based robotics. Knowledge of these domains is essential for every automation engineer.
Relation with research:
In this course, (own) research results are discussed and demonstrated. Furthermore, students have to consult primary sources (conference and journal articles) and choose, analyse and discuss an article; this review task gives the student more insight into how research is set up and performed, it sharpens his critical mind and analytic capacity, and stimulates self-study and life-long learning. |
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| Master of Teaching in Sciences and Technology - Engineering and Technology choice for subject didactics engineering & technology | Optional | 108 | 4,0 | 108 | 4,0 | Yes | Yes | Numerical | |
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| | | Learning outcomes |
- EC
| 5.2. The master of education is a domain expert ENG & TECH: the EM has a specialised knowledge and understanding of the acquired subject didactics and can creatively conceive, plan and implement them in an educational context and, in particular, as an integrated part of a methodologically and project-based ordered series of actions within a multidisciplinary STEM project with an important research and/or innovation component. | - EC
| 5.3. The master of education is a domain expert ENG & TECH: the EM has advanced or specialised knowledge and understanding of the principles, structure and used technologies of various industrial processes and techniques relevant to the specific subject disciplines and can autonomously recognise, critically analyse and methodically and well-foundedly solve complex, multidisciplinary, non-familiar, practice-oriented design or optimisation problems in these, with an eye for application, selection of materials, automation, safety, environment and sustainability, aware of practical limitations and with attention to current technological developments. |
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| | EC = learning outcomes DC = partial outcomes BC = evaluation criteria |
|
|
Robotics and sensor technology builds on knowledge of mathematics (algebra, matrix calculus, statistics), control theory (feedback, position and velocity control) and measurement systems (position or distance measurement, force measurement). Furthermore, robotics is related to electricity (electric motors), hydraulics and pneumatics (drives), mechanics, and power electronics.
|
|
|
|
General description
Robotics and sensor technology is an engineering course in the domain of mechatronics: integrating mechanics, electronics and computer science. This is to a large degree a descriptive course on the current state of the art and the terminology of robot technology (composition, drives, control, programming, applications). Nevertheless, a number of specific techniques are discussed in more detail, such as coordinate transformations, robot modeling and (basic) probabilistic state estimation and localisation. Additionally, components, image formation and image processing of vision systems are discussed. The part on vision systems addresses the recent rise of industrial cameras for a wide range of automation applications, even outside robotics.
Content of lectures and exercise sessions
Mobile robotics:
- wheel types and mobile robot kinematics
- probabilistic localisation and mapping
- obstacle avoidance and path planning
- mobile robot control
Robot manipulators:
- position and orientation of rigid objects, coordinate transformation matrices
- forward and inverse kinematics
- workspace analysis, analysis of singularities;
- robot components
Sensors:
- light and colour
- lenses, cameras, camera model
- image processing (monadic and spatial operations)
- feature extraction (region, line and point features)
|
|
|
|
|
|
|
|
|
Lecture ✔
|
|
|
|
Small group session ✔
|
|
|
|
|
|
|
|
Exercises ✔
|
|
|
|
Report ✔
|
|
|
|
Period 1 Credits 4,00
| Evaluation method | |
|
| Written exam | 70 % |
|
| Transfer of partial marks within the academic year | ✔ |
|
|
|
|
|
|
|
|
|
|
| Oral exam | 30 % |
|
| Transfer of partial marks within the academic year | ✔ |
|
|
|
| Other | Discussion of scientific paper and summary (Robotics and vision) |
|
|
|
|
|
| Additional information | - Written exam, closed book (70%): test of the knowledge about the properties of a mobile robot and robot manipulator and frequently adopted algorithms, the skill to model and the knowledge and understanding of vision technology. The use of a graphical calculator is permitted provided that the permanent memory and the volatile memory are empty before the start of the exam.
- oral defense of a review of a scientific paper (30%), summarised in 2/3 pages, on a research topic selected by the student but related to the course content and approved by the professor; use of the summarised article is permitted.
C. Overall remarks
(1) If the student does not participate in the 2nd exam period, his score from the 1st exam period remains on either part (oral or written exam). (2) The student may choose to still redo an evaluation on a part, but then (s)he must explicitly notify the professor. |
|
Second examination period
| Evaluation second examination opportunity different from first examination opprt | |
|
|
|
| Compulsory course material |
| |
For some of the robotics-related exercise sessions, Matlab is needed. Each student can install Matlab on his own laptop or PC. A student license is available via UHasselt. |
|
|
| Recommended reading |
| |
- Introduction to Autonomous Mobile Robots,Roland Siegwart, Illah Reza Nourbakhsh, Davide Scaramuzza,2,9780262015356,Available as e-book: https://ebookcentral.proquest.com/lib/ubhasselt/detail.action?docID=3339191
- Robotics, vision and control,Peter Corke,2,Springer,9783319544120,pdf beschikbaar via limo-libis, also available as e-book: https://link.springer.com/book/10.1007%2F978-3-319-54413-7
- Introduction to Robotics: Mechanics and Control,John J. Craig,4,Pearson,9780133489798
- Robotics: modelling, planning and control,Bruno Siciliano, Lorenzo Sciavicco, Luigi Villani, Giuseppe Oriolo,1,Springer,9781849966344,pdf beschikbaar via limo-libis
- Springer Handbook of Robotics,Bruno Siciliano, Oussama Khatib,2,Springer,9783319325507,pdf beschikbaar via limo-libis
|
|
|
| Recommended course material |
| |
- articles from robot conferences, journals or other publications; mostly available through limo-libis;
- extended background information on computer vision is available via the course's electronic learning platform.
|
|
|
| Remarks |
| |
Fit within the curriculum:
This course is part of the domain of automation technology. Robotics and sensor technology is a very broad research and application domain, requiring knowledge and integration of many courses of the curriculum such as mathematics, mechanics, control theory, measurement systems, electricity, etc.
Relation with industry:
Robotics and sensor technology have been adopted in manufacturing industry and many other sectors (medicine, agriculture, care, logistics, food, pharma) for a long time already. They are increasingly needed in combination in order to obtain "smart", sensor-based robotics. Knowledge of these domains is essential for every automation engineer.
Relation with research:
In this course, (own) research results are discussed and demonstrated. Furthermore, students have to consult primary sources (conference and journal articles) and choose, analyse and discuss an article; this review task gives the student more insight into how research is set up and performed, it sharpens his critical mind and analytic capacity, and stimulates self-study and life-long learning. |
|
|
|
|
|
| Exchange Programme Engineering Technology | Optional | 108 | 4,0 | 108 | 4,0 | Yes | Yes | Numerical | |
|
| |
|
|
Robotics and sensor technology builds on knowledge of mathematics (algebra, matrix calculus, statistics), control theory (feedback, position and velocity control) and measurement systems (position or distance measurement, force measurement). Furthermore, robotics is related to electricity (electric motors), hydraulics and pneumatics (drives), mechanics, and power electronics.
|
|
|
|
General description
Robotics and sensor technology is an engineering course in the domain of mechatronics: integrating mechanics, electronics and computer science. This is to a large degree a descriptive course on the current state of the art and the terminology of robot technology (composition, drives, control, programming, applications). Nevertheless, a number of specific techniques are discussed in more detail, such as coordinate transformations, robot modeling and (basic) probabilistic state estimation and localisation. Additionally, components, image formation and image processing of vision systems are discussed. The part on vision systems addresses the recent rise of industrial cameras for a wide range of automation applications, even outside robotics.
Content of lectures and exercise sessions
Mobile robotics:
- wheel types and mobile robot kinematics
- probabilistic localisation and mapping
- obstacle avoidance and path planning
- mobile robot control
Robot manipulators:
- position and orientation of rigid objects, coordinate transformation matrices
- forward and inverse kinematics
- workspace analysis, analysis of singularities;
- robot components
Sensors:
- light and colour
- lenses, cameras, camera model
- image processing (monadic and spatial operations)
- feature extraction (region, line and point features)
|
|
|
|
|
|
|
|
|
Lecture ✔
|
|
|
|
Small group session ✔
|
|
|
|
|
|
|
|
Exercises ✔
|
|
|
|
Report ✔
|
|
|
|
Period 1 Credits 4,00
| Evaluation method | |
|
| Written exam | 70 % |
|
| Transfer of partial marks within the academic year | ✔ |
|
|
|
|
|
|
|
|
|
|
| Oral exam | 30 % |
|
| Transfer of partial marks within the academic year | ✔ |
|
|
|
| Other | Discussion of scientific paper and summary (Robotics and vision) |
|
|
|
|
|
| Additional information | - Written exam, closed book (70%): test of the knowledge about the properties of a mobile robot and robot manipulator and frequently adopted algorithms, the skill to model and the knowledge and understanding of vision technology. The use of a graphical calculator is permitted provided that the permanent memory and the volatile memory are empty before the start of the exam.
- oral defense of a review of a scientific paper (30%), summarised in 2/3 pages, on a research topic selected by the student but related to the course content and approved by the professor; use of the summarised article is permitted.
C. Overall remarks
(1) If the student does not participate in the 2nd exam period, his score from the 1st exam period remains on either part (oral or written exam). (2) The student may choose to still redo an evaluation on a part, but then (s)he must explicitly notify the professor. |
|
Second examination period
| Evaluation second examination opportunity different from first examination opprt | |
|
|
|
| Compulsory course material |
| |
For some of the robotics-related exercise sessions, Matlab is needed. Each student can install Matlab on his own laptop or PC. A student license is available via UHasselt. |
|
|
| Recommended reading |
| |
- Introduction to Autonomous Mobile Robots,Roland Siegwart, Illah Reza Nourbakhsh, Davide Scaramuzza,2,9780262015356,Available as e-book: https://ebookcentral.proquest.com/lib/ubhasselt/detail.action?docID=3339191
- Robotics, vision and control,Peter Corke,2,Springer,9783319544120,pdf beschikbaar via limo-libis, also available as e-book: https://link.springer.com/book/10.1007%2F978-3-319-54413-7
- Introduction to Robotics: Mechanics and Control,John J. Craig,4,Pearson,9780133489798
- Robotics: modelling, planning and control,Bruno Siciliano, Lorenzo Sciavicco, Luigi Villani, Giuseppe Oriolo,1,Springer,9781849966344,pdf beschikbaar via limo-libis
- Springer Handbook of Robotics,Bruno Siciliano, Oussama Khatib,2,Springer,9783319325507,pdf beschikbaar via limo-libis
|
|
|
| Recommended course material |
| |
- articles from robot conferences, journals or other publications; mostly available through limo-libis;
- extended background information on computer vision is available via the course's electronic learning platform.
|
|
|
| Remarks |
| |
Fit within the curriculum:
This course is part of the domain of automation technology. Robotics and sensor technology is a very broad research and application domain, requiring knowledge and integration of many courses of the curriculum such as mathematics, mechanics, control theory, measurement systems, electricity, etc.
Relation with industry:
Robotics and sensor technology have been adopted in manufacturing industry and many other sectors (medicine, agriculture, care, logistics, food, pharma) for a long time already. They are increasingly needed in combination in order to obtain "smart", sensor-based robotics. Knowledge of these domains is essential for every automation engineer.
Relation with research:
In this course, (own) research results are discussed and demonstrated. Furthermore, students have to consult primary sources (conference and journal articles) and choose, analyse and discuss an article; this review task gives the student more insight into how research is set up and performed, it sharpens his critical mind and analytic capacity, and stimulates self-study and life-long learning. |
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1 Education, Examination and Legal Position Regulations art.12.2, section 2. |
| 2 Education, Examination and Legal Position Regulations art.16.9, section 2. |
3 Education, Examination and Legal Position Regulations art.15.1, section 3.
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| Legend |
| SBU : course load | SP : ECTS | N : Dutch | E : English |
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