|Teaching method||Contact hours|
|Course coordinator(s)||ing. SK Blaauw|
|Lecturer(s)||ing. SK Blaauw|
|dr. ir. LG van Willigenburg|
|Examiner(s)||dr. ir. LG van Willigenburg|
|prof. dr. ir. EJ van Henten|
Language of instruction:
Assumed knowledge on:
FTE-27306 Sensor Technology; INF-22306 Programming in Python.
Agriculture is challenged to overcome increasing labour costs, decreasing availability of labour and increasing demands concerning precision, product quality and reduction of environmental and animal load. As can be seen in Western Europe an important solution is to replace human labour by automation in areas such as arable farming, livestock farming, and horticulture. Examples of automation are milking robots, GPS steering of tractors, autonomous vehicles and automated harvesting in greenhouse production. The design and implementation of such automated systems is expected to be at the heart of agricultural innovation the next decades.
The guideline for this course is taken from the robotics domain and is stated as: 'Robotics is the intelligent transformation of perception into mechanical action'. To realize these transformations sensors, actuators, manipulators, vehicles, computers and decision systems, are important components. These components and how they may be applied to design automated agricultural systems constitute the contents of this course.
The theoretical part of this course will be presented during lectures. Practical assignments concern the design, programming and control of a robot manipulator and an autonomous vehicle.
After successful completion of the course students are expected to be able to:
- describe the main driving forces for automation in agriculture;
- appoint and explain the function of the components of a robotic system;
- employ commonly used robot coordinate transformations in a 2D and 3D space;
- explain the effect of vehicle structure, wheel configuration and steering principles on the kinematic behavior of a mobile platform;
- describe the kinematics of simple mobile platform configurations with a mathematical model;
- explain the effect of links and joints on the kinematic behavior of a manipulator;
- describe the forward and inverse kinematics of simple manipulator structures with a mathematical model,
- list sensors commonly used for robots and automation, specify their characteristics, and select a proper sensor for a given application;
- employ simple control and motion planning techniques for vehicles and manipulators, simulate and program a small autonomous vehicle as well as a 5DOF manipulator.
Many autonomous/robotic systems in agriculture consist of two main functions: 1) mobility, i.e. making the system move over or through the working environment of a field, greenhouse or barn, 2) manipulation, i.e. performing an action on an object using a mechanical device like a robotic arm. The course is built on this functional decomposition and consists of two parts: 1) the first half of the course is devoted to understanding, modelling, simulation and control of mobile platforms, 2) the second half of the course addresses the behaviour, modelling, simulation and control of a robotic arm.
Theoretical concepts will be introduced in lectures. Examples will be provided to exercise with these concepts. Besides the lectures, the course contains two lab projects: one on mobile robots and one on robot manipulators. These lab projects will provide hands-on experience with modelling and programming a mobile platform and a robotic arm to perform a pre-defined task. In these lab projects students will work on various tasks in small groups of 2 or at most 3 people. Your presence is not only required for reasons of learning to master the material and performing your fair share of the task, but is mandatory (see examination). In the lab work Python and Matlab will be used. Having basic skills in these languages will be an advantage.
The two lab work tracks on mobile robots and manipulators are mandatory. Absence without notice or consent of the coordinator during one or more of the sessions in a lab track will be noted as a fail to pass that element of the course.
The assessment of the course will be based on:
- a written closed book exam on the lecture and study material;
- a report of code and supplementary material of the mobile robots lab work;
- a report of code and supplementary material of the robot manipulator lab work.
For each of the above three course elements, a lower threshold mark of 5.50 is implemented. So, to pass this course and to obtain a final mark, students should complete each of the three course elements with a mark that is equal to or higher than 5.50.
In case marks on all three course elements exceed 5.50, the final mark will be calculated as follows: 70% written exam, 15% mobile robot lab work, 15% manipulator practical lab work.
|Restricted Optional for:||MBE||Biosystems Engineering||MSc||6AF|