IPLUSO 22088

Applied and Mobile Robotics

• ApresentaçãoPresentation

  The Applied and Mobile Robotics curricular unit aims to introduce essential concepts and tools in context of knowing the constituent elements of a robotic system (mobile robot), focusing essentially on terrestrial robots. Know mobile robots, as well as the elements that make them up: sensors, controller/microcontroller, pre-actuators and actuators. Robot programming and parameterization. Add wireless communication networks for robot control
• ProgramaProgramme

  Part 1 1. Introduction to Mobile Robotics The. Introduction to Mobile Robotics B. Historical context w. Types of mobile robots d. State of the art in Mobile Robotics and applications It is. Components of a Mobile Robot Part 2 2. Movement and Control of mobile robots The. Introduction to locomotion B. Types of locomotion w. Actuators: definition and types d. Kinematics It is. Sensors f. PID control Part 3 4. Robot programming paradigms The. Reactive B. Hierarchical w. Hybrid Part 4 6. Navigation and planning The. Path planning B. Obstacle avoidance 8. Other types of transportation 9. Mobile robot project
• ObjectivosObjectives

  Recognize the different aspects and applications of Mobile Robotics. Recognize the main components of a mobile robot. Gain programming knowledge with mobile robots. Have knowledge of programming and parameterization of mobile robots. Have programming knowledge to control mobile robots using networks wireless. Have knowledge in the use of modeling and programming software.
• BibliografiaBibliography

  1. SIEGWART, R.; NOURBAKHSH, I. Introduction to Autonomous Mobile Robots. Cambridge, Massachusetts: MIT Press, 2004. 2. MURPHY, Robin. R. Introduction to AI robotics. Cambridge, Massachusetts: MIT Press, 2000. 3. THRUN, S., BURGARD, W., FOX, D. Probabilistic Robotics. Cambridge, Massachusetts: MIT Press, 2005. 4. DUDEK, G.; JENKIN, M. Computational Principles of Mobile Robotics. Cambridge, Massachusetts: MIT Press, 2010. 5. RUSSEL, S. .; NORVIG, P. Artificial Intelligence: a modern approach. Prentice Hall. 3rd edition, 2009. 6. MITCHELL, T. Machine Learning. McGrawHill, 1997.  
• MetodologiaMethodology

  The exposition of concepts is carried out by appealing to the active participation of students. Introduce Yourself illustrative examples of concepts and results. In practical classes, students analyze and solve assignments practical in the laboratory, as well as the development of projects. Continuous assessment: one frequency to be carried out during the semester, with a weight of 50%, 1 assignment project with report delivery, with a weight of 50%. Students who obtain an average equal to or greater than 9.5 and who have attendance greater than 75% of the total number of classes, as long as they are not covered by special statutes/situations. Final assessment: an exam period for students who did not pass continuous assessment. Students with a classification equal to or greater than 9.5 are approved.
• LínguaLanguage

  Português
• TipoType

  Semestral
• ECTS

  6
• NaturezaNature

  Mandatory
• EstágioInternship

  Não