CG1 Organize and evaluate the learning and the research activity themselves and develop strategies to improve them. CG1- Organize and evaluate the learning and the research activity themselves and develop strategies to improve them CB6 Possess and understand the knowledge that provides a basis or opportunity to be original in the development and/or application of ideas, often in a research context. CB6- Possess and understand the knowledge that provides a basis or opportunity to be original in the development and/or application of ideas, often in a research context CB7 That students know how to apply the knowledge acquired and their ability to solve problems in new or unfamiliar environments within broader contexts related to their area of ??study. CB7- That students know how to apply the knowledge acquired and their ability to solve problems in new or unfamiliar environments within broader contexts related to their area of ??study CB10 That students have the learning skills to allow them to continue studying in a way that will mostly be self-directed or autonomous. CB10- That students have the learning skills to allow them to continue studying in a way that will mostly be self-directed or autonomous CE1 Programming, at an advanced level, in the languages and libraries most used in intelligent field robotics. CE1- Programming, at an advanced level, in the languages and libraries most used in intelligent field robotics CE8 Understand the mathematical foundations of intelligent robotic system algorithms. CE8- Understand the mathematical foundations of intelligent robotic system algorithms CE10 Learn and use the main techniques of control and trajectory planning used in manipulators and autonomous vehicles.
1. Introduction to industrial manipulators 2. Coordinate systems 3. Forward Kinematics 4. Inverse Kinematics 5. Differential Kinematics 6. Dynamics 7. Trajectory Control and generation 8. Industrial Manipulators Programming
Activity type Hours with a teacher Hours without a teacher Virtual hours with a teacher Total Analysis / case study 27,00 38,00 0 65,00 Assessment test 3,00 6,00 0 9,00 Solution of exercises 8,00 8,00 0 16,00 Theory class 28,00 24,00 0 52,00 Hands-on class 4,00 4,00 0 8,00 Total 70,00 80,00 0 150
Corke, Peter I (2011). Robotics, vision and control : fundamental algorithms in Matlab . New York: Springer. Siciliano, Bruno & Sciavicco, Lorenzo & Luigi, Villani & Oriolo, Giuseppe. (2011). Robotics: Modelling, Planning and Control.. Springer.
Assessment activities: Description of the activity Assessment Activity % Remediable subject Lab 2: Pick & Place TS60 The evaluation criteria will follow different points: Level reached. Completition quality. Report. Progress. Level reached Level 1: 4/10. Level 2: 6/10. Level 3: 8/10. Completition quality Up to 1/10. Robot modelling parts and composition. The use of colours, parameters, etc. Code good structuration. Report Up to 1/10. In the report, the students have to develop a formal document where they have to present the application, what they are asked to develop, and how they had developed. The code developed also has to be explained, making emphasis on the functions used. The student can add a final section where suggestions to improve the laboratory sessions can be done. Progress Will add extra points if total is less than 10. Here, improvements applied will be considered. Including an end-effector to the robot manipulator. 12,5 No Lab 3: Pick & Place TX60 The evaluation criteria will follow different points: Level reached. Completition quality. Report. Progress. Level reached Level 1: 4/10. Level 2: 6/10. Level 3: 8/10. Completition quality Up to 1/10. Robot modelling parts and composition. The use of colours, parameters, etc. Code good structuration. Report Up to 1/10. In the report, the students have to develop a formal document where they have to present the application, what they are asked to develop, and how they had developed. The code developed also has to be explained, making emphasis on the functions used. The student can add a final section where suggestions to improve the laboratory sessions can be done. Progress Will add extra points if total is less than 10. Here, improvements applied will be considered. Including an end-effector to the robot manipulator. 12,5 No Lab 4: Machine Vision Implementation The evaluation criteria will follow different points: Level reached. Completition quality. Report. Progress. Level reached Level 1: 4/10. Level 2: 6/10. Level 3: 8/10. Completition quality Up to 1/10. Robot modelling parts and composition. The use of colours, parameters, etc. Code good structuration. Report Up to 1/10. In the report, the students have to develop a formal document where they have to present the application, what they are asked to develop, and how they had developed. The code developed also has to be explained, making emphasis on the functions used. The student can add a final section where suggestions to improve the laboratory sessions can be done. Progress Will add extra points if total is less than 10. Here, improvements applied will be considered. Including an end-effector to the robot manipulator. 12,5 No Lab 5: Robotics Toolbox. The evaluation criteria will follow different points: Level reached. Completition quality. Report. Progress. Level reached Level 1: 4/10. Level 2: 6/10. Level 3: 8/10. Completition quality Up to 1/10. Robot modelling parts and composition. The use of colours, parameters, etc. Code good structuration. Report Up to 1/10. In the report, the students have to develop a formal document where they have to present the application, what they are asked to develop, and how they had developed. The code developed also has to be explained, making emphasis on the functions used. The student can add a final section where suggestions to improve the laboratory sessions can be done. Progress Will add extra points if total is less than 10. Here, improvements applied will be considered. Including an end-effector to the robot manipulator. 12,5 No 1st Partial Examination If passed this part is eliminative, otherwise i must be recovered in the final examination. Must be passed with at least 4 points in order to averaged with the contents of the 2nd partial evaluated in the final exmaination 25 Yes Final Examination. The final has 2 parts: 1) partial 1 and 2 ) partial 2. Students who already passed the partial 1 with a mark P1>= 4, only has to be examined of partial 2. Otherwise they must complete the both parts of the final: part 1 and part 2. The Final mark F is the average of both (both must be over >=4). 25 No
50% Laboratory Exercices. 50% Written Examination. All qualifiable parts need at least a qualification >= 4/10 Specific criteria for the "No show" grade: If the student does not take the exam or does not complete the evaluable labs, he/she will be considered as not been presented and will be evaluated with this grade. Single Assessment: The same evaluation activities will be carried out but it will be facilitated that those activities that require a compulsory presence in the laboratory can be done either in person at agreed times, or remotely using robot simulators. Deadlines will also be adjusted so that a single delivery of all activities can be made. Minimum requirements to pass: To be considered to have passed the course, a minimum grade of 5.0 must be obtained
To arrange a tutorial, the student or group of students should send an email to the teacher of the course. If possible, the tutorial will be resolved by email, otherwise Google Meet will be used.
All the information and activities of the subject will be done through Moodle. Google Meet will be used for non-contact sessions. All teacher notifications to students will be made by internal Moodle messaging system or email. Students will also need to use Moodle or email to contact the teacher.
The VAL3 programming language for Stäubli industrial robots and its environment will be used. Exercises will also be done with Python and ROS among others. The students will use an industrial robot for the practices. It will be necessary to work with the proposed programming environment inside the laboratory, in the agreed schedule, and also from outside.