2024
Robotics
Name: Robotics
Code: EME13220L
6 ECTS
Duration: 15 weeks/156 hours
Scientific Area:
Mechatronic Engineering
Teaching languages: Portuguese
Languages of tutoring support: Portuguese, English
Regime de Frequência: Presencial
Sustainable Development Goals
Learning Goals
The student will acquire knowledge in manipulator-robotic systems. Will develop kinematics models - Direct and Inverse Kinematics. Will formulate dynamic models and will be able to avaliate and select Robotic Sensors and Actuators.
In the field of robotic sensors, the student will gain special know-how in vision-sensors. The student will have the capability to implement an automatic image processing system, in the domain of pattern recognition. The vision-sensor information is processed and the decision is send to a PLC that will control the corresponding actions.
In the field of robotic sensors, the student will gain special know-how in vision-sensors. The student will have the capability to implement an automatic image processing system, in the domain of pattern recognition. The vision-sensor information is processed and the decision is send to a PLC that will control the corresponding actions.
Contents
1)Manipulator robots. Robot classes. Components of a robotic system.
2)Mathematical models of typical joints. Kinematic chains. Kinematics and linear transformations: direct kinematics and inverse kinematics. Denavit-Hartenberg formulation.
3)Robot Dynamics: Lagrange and Newton-Euler formulations. Trajectory planning.
4)Robot Control: independent joint-control, work space-control. Practical implementation with Laboratory Robots Online and Offline Programming.
5)Robotic sensors: position/speed, proximity, force/torque, artificial vision sensors.
6)Introduction to automatic vision. Equipment for industrial vision. Digital signal processing. Filtering. Textures and form classification. Introduction to pattern recognition.
7)The integration of artificial vision in industrial automation controlled by PLC (Programmable Logic Controller). Practical implementations with vision sensors Siemens VS-710 (Siemens-ProVision).
2)Mathematical models of typical joints. Kinematic chains. Kinematics and linear transformations: direct kinematics and inverse kinematics. Denavit-Hartenberg formulation.
3)Robot Dynamics: Lagrange and Newton-Euler formulations. Trajectory planning.
4)Robot Control: independent joint-control, work space-control. Practical implementation with Laboratory Robots Online and Offline Programming.
5)Robotic sensors: position/speed, proximity, force/torque, artificial vision sensors.
6)Introduction to automatic vision. Equipment for industrial vision. Digital signal processing. Filtering. Textures and form classification. Introduction to pattern recognition.
7)The integration of artificial vision in industrial automation controlled by PLC (Programmable Logic Controller). Practical implementations with vision sensors Siemens VS-710 (Siemens-ProVision).
Teaching Methods
The teaching method is based on theoretic/ practice lessons together with tutorial orientation. It is stimulated an active learning process where the student is motivated to search deeper the several subjects studied in this curricular unit. In the practical classes the student makes contact with laboratory implementations to better realize the topics in study.
The evaluation has 2 components:
P1 = Direct and Inverse kinematics Model of Robotic Manipulator with 6 DOF;
P2 = Experimental Implementation with Industrial Manipulador Robot 6 DOF;
or
P2 = Experimental Implementation on Artificial Vision Pattern Recognition - integrated with Industrial Automation (PLC)
The final grade is obtained by: 0.5xP1 + 0.5xP2
The evaluation has 2 components:
P1 = Direct and Inverse kinematics Model of Robotic Manipulator with 6 DOF;
P2 = Experimental Implementation with Industrial Manipulador Robot 6 DOF;
or
P2 = Experimental Implementation on Artificial Vision Pattern Recognition - integrated with Industrial Automation (PLC)
The final grade is obtained by: 0.5xP1 + 0.5xP2
Teaching Staff
Certificações
