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 CG2 Interact in a multicultural environment through knowledge of the national and European cultures, human rights and European realities. CG2- Interact in a multicultural environment through knowledge of the national and European cultures, human rights and European realities CG3 Communicate in an effective way both orally and in writing, preparing documents and presenting projects and results with English language. CG3- Communicate in an effective way both orally and in writing, preparing documents and presenting projects and results with English language CG4 Designing creative proposals. CG4- Designing creative proposals CG5 Collect and select information to be able to evaluate the state of the art of a specific topic or subject. CG5- Collect and select information to be able to evaluate the state of the art of a specific topic or subject CG6 Work in multidisciplinary teams, establishing those relationships that can help to bring out the most effective cooperation and maintain them continuously. CG6- Work in multidisciplinary teams, establishing those relationships that can help to bring out the most effective cooperation and maintain them continuously CB9 That students know how to communicate their conclusions and the knowledge and ultimate reasons that sustain them to specialized and non-specialized audiences in a clear and unambiguous way. CB9- That students know how to communicate their conclusions and the knowledge and ultimate reasons that sustain them to specialized and non-specialized audiences in a clear and unambiguous way 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 CE2 Analyse a problem related to intelligent autonomous systems and identify the appropriate techniques and tools to solve it. CE2- Analyse a problem related to intelligent autonomous systems and identify the appropriate techniques and tools to solve it CE5 Know, understand and be able to apply the algorithms that allow autonomous vehicles to localize themselves and navigate effectively. CE5- Know, understand and be able to apply the algorithms that allow autonomous vehicles to localize themselves and navigate effectively CE6 Know and understand when and how to use the main sensors and actuators available for intelligent field robots. CE6- Know and understand when and how to use the main sensors and actuators available for intelligent field robots CE8 Understand the mathematical foundations of intelligent robotic system algorithms. CE8- Understand the mathematical foundations of intelligent robotic system algorithms CE9 Design and manage projects in the field of intelligent field robotic systems. CE9- Design and manage projects in the field of intelligent field robotic systems CE10 Learn and use the main techniques of control and trajectory planning used in manipulators and autonomous vehicles. CE10- Learn and use the main techniques of control and trajectory planning used in manipulators and autonomous vehicles
1. Common extensions for motion planning algorithms 2. Motion planning with differential constraints 3. View planning, inspection, coverage, and automatic exploration 4. Formal and Automatic task planning methods 5. Hands-on project
Activity type Hours with a teacher Hours without a teacher Virtual hours with a teacher Total Analysis / case study 4,00 21,00 0 25,00 Student presentations 2,00 6,00 0 8,00 Seminars 10,00 5,00 0 15,00 Theory class 12,00 10,00 0 22,00 Hands-on class 10,00 20,00 0 30,00 Teamwork 22,00 28,00 0 50,00 Total 60,00 90,00 0 150
Peter Corke (2011). Robot Vision and Control. Springer. Howie Choset, Kevin M. Lynch, Seth Hutchinson, George A. Kantor, Wolfram Burgard, Lydia E. Kavraki and Sebastian Thrun (2005). Principles of Robot Motion Theory, Algorithms, and Implementations. The MIT Press. Thrun, Sebastian; Burgard, Wolfram; Fox, Dieter (2005). Probabilistic robotics. Cambridge, Massachusetts ; London : The MIT Press.
Assessment activities: Description of the activity Assessment Activity % Remediable subject Test An individual test to evaluate the theoretical contents of the course, as well as the seminars. The minimum grade for the test in order to pass the course is 5/10. 20 Yes Seminars Exercises will be proposed by the invited scholar to be solved by the students. 5 No Labs A few guided labs will be proposed to familiarize students with the libraries and algorithms needed to conduct the practical project. Students' presence in the lab is mandatory. A report must be submitted for each lab. The correctness of the solution, the quality and the clarity of the report document will be evaluated. An oral examination can be asked in addition to the presented report. 15 No Hands-on project Students, in small groups, will develop a hands-on project related to exploration and motion planning techniques. The code must run on a simulated or real Turtlebot robot. Students will be required to meet periodically with the professor to evaluate the progress of the work. The correctness of the solution, the innovation and originality of the proposal and the quality and clarity of the code submitted will be evaluated. In addition, an oral questionnaire may be done to certify the involvement of all members of the group. The final grade may be different for each member of the group considering the laboratory work, the personal involvement in the code presented, and the answers to the oral questionnaire if any. 35 No Hands-on project presentation The clarity of the presentations and their ability to defend the work presented answering the questions requested by the audience will be evaluated. 10 No Hands-on project report, video, and demonstration A scientific paper and a video should be made to communicate the hands-on project performed. A demonstration of the final code running on the real Turtlebot robot or on a simulator should also be made. During the demonstration, additional questions may be asked to each member of the group to evaluate their involvement in the project. The paper, video and demonstration must be done as a group, but the grade may be different for each member depending on their degree of participation. 15 No
- Test = 20% - Seminar exercise = 5% - Labs = 15% - Hands-on project: --- continuous work and code = 35% --- presentation = 10% --- paper + video + demonstration = 15% Only the test can be recovered, the other activities no. Specific criteria for the "No show" grade: If the student does not present the hands-on project or the evaluable labs, or do not perform the test, he/she will be considered as not been presented and will be evaluated with this grade. If the student is not present in the presentation or in the demonstration due to a major force, these activities must be rescheduled. 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: A minimum grade of 5/10 for the test is required to average all the marks with their weight to obtain the final grade. Otherwise, the test grade will be the final grade. A minimum final grade of 5.0 must be obtained to pass the course.
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.
Students must know how to program in C++ or Python, as well as be familiar with the Robot Operating System (ROS) to follow the course.