2025
Introduction to Aerospace Robotic Systems
Name: Introduction to Aerospace Robotic Systems
Code: EME14865L
6 ECTS
Duration: 15 weeks/156 hours
Scientific Area:
Engenharia Aeroespacial
Teaching languages: Portuguese
Languages of tutoring support: Portuguese
Sustainable Development Goals
Learning Goals
The student will acquire knowledge in manipulator-robotic systems. Will develop kinematic models - Direct and Inverse Kinematics. Will formulate dynamic models and trajectory planning. Will be able to evaluate and select Robotic Sensors and Actuators.
Regarding robotic sensors, special attention is given to artificial vision, where the student must have the ability to implement image processing, within the scope of pattern recognition and trajectory detection. The information from the image sensor will be processed and the decision will be used in navigation, controlling the corresponding actuators.
The student must acquire knowledge about Mobile Robotics, namely the structure, main sensors and actuators of AGVs (Automated Guided Vehicles). Particular study emphasis is placed on land and air AGVs and their geolocation.
Regarding robotic sensors, special attention is given to artificial vision, where the student must have the ability to implement image processing, within the scope of pattern recognition and trajectory detection. The information from the image sensor will be processed and the decision will be used in navigation, controlling the corresponding actuators.
The student must acquire knowledge about Mobile Robotics, namely the structure, main sensors and actuators of AGVs (Automated Guided Vehicles). Particular study emphasis is placed on land and air AGVs and their geolocation.
Contents
1) Manipulator robots. Robots classification. 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.
4) Robot Control: independent joint-control and work space-control.
5) Robotic sensors: position/speed, proximity, force/torque, artificial vision sensors.
6) Introduction to automatic vision. Equipment for artificial vision. Digital signal processing. Filtering. Textures and form classification. Introduction to pattern recognition.
7) Mobile Robots, AGVs (Automated Guided vehicle) in terrestrial and aerospace exploration: locomotion, control and navigation and geolocation.
8) Integration of artificial vision in mobile robotics. Use of artificial vision in robot navigation.
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.
4) Robot Control: independent joint-control and work space-control.
5) Robotic sensors: position/speed, proximity, force/torque, artificial vision sensors.
6) Introduction to automatic vision. Equipment for artificial vision. Digital signal processing. Filtering. Textures and form classification. Introduction to pattern recognition.
7) Mobile Robots, AGVs (Automated Guided vehicle) in terrestrial and aerospace exploration: locomotion, control and navigation and geolocation.
8) Integration of artificial vision in mobile robotics. Use of artificial vision in robot navigation.
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.
Assessment
The evaluation presupposes the completion of 2 projects (P1 + P2).
The Project P1 has an alternative between 2 possible choices: P1 = Direct and Inverse kinematics Model of Robotic Manipulator with 6 DOF or P1 = Experimental Implementation on Artificial Vision for Manipulator Robot Pattern Recognition;
The Project P2 = Experimental Implementation on mobile robots navigation .
The final grade is: NF = 0.5*P1 + 0.5*P2.
Being a mostly experimental curricular unit The final assessment has the same format as the continuous assessment, requiring the completion of the same 2 projects (P1 + P2).
The P1 Project has an alternative between 2 possible choices: P1= Direct and Inverse Kinematic Model of a Robotic Manipulator w/ 6 GDL or P1= Experimental project of artificial vision for Robot Manipulator Pattern Recognition;
Project P2= Experimental implementation of mobile robotics navigation (AGV).
The final grade is: NF = 0.5*P1+0.5*P2.
Approved if NF>= 9.5
Failed if NF < 9.5
The Project P1 has an alternative between 2 possible choices: P1 = Direct and Inverse kinematics Model of Robotic Manipulator with 6 DOF or P1 = Experimental Implementation on Artificial Vision for Manipulator Robot Pattern Recognition;
The Project P2 = Experimental Implementation on mobile robots navigation .
The final grade is: NF = 0.5*P1 + 0.5*P2.
Being a mostly experimental curricular unit The final assessment has the same format as the continuous assessment, requiring the completion of the same 2 projects (P1 + P2).
The P1 Project has an alternative between 2 possible choices: P1= Direct and Inverse Kinematic Model of a Robotic Manipulator w/ 6 GDL or P1= Experimental project of artificial vision for Robot Manipulator Pattern Recognition;
Project P2= Experimental implementation of mobile robotics navigation (AGV).
The final grade is: NF = 0.5*P1+0.5*P2.
Approved if NF>= 9.5
Failed if NF < 9.5
Accreditations and Certifications
