De elektronische studiegids voor het academiejaar 2025 - 2026 is onder voorbehoud.





Robotics & sensor technology (2708)

  
Coordinating lecturer :Prof. dr. ir. Eric DEMEESTER 
  
Member of the teaching team :ing. Maarten VERHEYEN 


Language of instruction : English


Credits: 4,0
  
Period: semester 1 (4sp)
  
2nd Chance Exam1: Yes
  
Final grade2: Numerical
 
Exam contract: not possible


 
Sequentiality
 
   No sequentiality

Prerequisites

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.



Content

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)


Organisational and teaching methods
Organisational methods  
Lecture  
Small group session  
Teaching methods  
Exercises  
Report  


Evaluation

Semester 1 (4,00sp)

Evaluation method
Written exam70 %
Transfer of partial marks within the academic year
Conditions transfer of partial marks within the academic yearDe student kan er zelf voor kiezen om het schriftelijk examen niet in 2e examenkans te herdoen en het deelcijfer uit de 1e examenkans te behouden. Hij deelt dit vooraf mee aan de docent.
Report
Oral exam30 %
Transfer of partial marks within the academic year
Conditions transfer of partial marks within the academic yearDe student kan er zelf voor kiezen om de samenvatting van het wetenschappelijk artikel en de bijhorende mondelinge evaluatie niet in 2e examenkans te herdoen en het deelcijfer uit de 1e examenkans te behouden. Hij deelt dit vooraf mee aan de docent.
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 to 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.

Second examination period

Evaluation second examination opportunity different from first examination opprt
No
 

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 has 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.



Learning outcomes
Master of Teaching in Sciences and Technology
  •  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.

 

Master of Electromechanical Engineering Technology
  •  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-M12 - The studentshows 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 ownshortcomings (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).

     
  •  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-M8 - The studentcan 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.

  •  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 studenthas 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 studenthas 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 applybasic probabilistic estimation techniques (e.g. Bayes' rule), and can apply basic vision algorithms.

     
  •  DC 
  • DC-M7 - The studentcan 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 studentcan 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-M5 - The studentcan 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 scientificarticle .

     
  •  DC 
  • DC-M4 - The studentcan 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-M3 - The studentcan 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-M6 - The studentcan 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.

 

  EC = learning outcomes      DC = partial outcomes      BC = evaluation criteria  
Offered inTolerance3
Exchange Programme Engineering Technology J
Master of Electromechanical Engineering Technology J
Master of Teaching in Sciences and Technology - Engineering and Technology choice for subject didactics engineering & technology J



1   Education, Examination and Legal Position Regulations art.12.2, section 2.
2   Education, Examination and Legal Position Regulations art.15.1, section 3.
3   Education, Examination and Legal Position Regulations art.16.9, section 2.