Mr Rodrigo Neves Zenha
Email: email@example.comRoom Number: Peter Landin, CS 319
Advanced Robotics Systems (Robotics III) (Undergraduate)
The module will build on previous knowledge acquired in the previous years on the programme and also introduce new and advanced concept related to geometric, kinematic, and dynamic robots manipulation, vision and machine learning specifically for Robotics, motion control and practical implementation of locomotion solutions, mechanical considerations of medical robots and the necessity of understanding acceptance and ethical values, etc. It will introduce the practicality of applying multidisciplinary techniques in enhancing the current state of the art in Robotics Engineering and allow the students to explore creative and engineered solutions that are outside the box along side conventional industrial and cognitive applications.
Artificial Intelligence (Undergraduate)
The module introduces the student to techniques used in Artificial Intelligence including problem formulation, search, logic, probability and decision theory. The module aims to provide the participants with a basic knowledge of artificial intelligence; an understanding of how to design an intelligent agent; and knowledge of basic AI tools.
Artificial Intelligence (Postgraduate)
This module provides an overview of techniques used in Artificial Intelligence including agent modelling, problem formulation, search, logic, probability and machine learning.
Cognitive Robotics (Robotics IV) (Undergraduate)
This module addresses the emerging field of autonomous systems possessing artificial reasoning skills and also environment and context awareness. The module will introduce students to advance numerical and computational techniques associated with machine learning and artificial intelligence. Successfully-applied algorithms and autonomy models form the basis for study, and provide students an opportunity to design such a system as part of their coursework project. Theory and practical applications will be linked through discussion of real systems such as the medical robotic surgeons and robotic musicians.
C Programming (Undergraduate)
This module introduces the principles of C Programming to students who already know how to program at a basic level in Java. It provides a knowledge of the theory of C Programming and also its practical use in real engineering systems. The focus is on microprocessor based systems.
Data Mining (Undergraduate)
Data that has relevance for decision-making is accumulating at an incredible rate due to a host of technological advances. Electronic data capture has become inexpensive and ubiquitous as a by-product of innovations such as the Internet, e-commerce, electronic banking, point-of-sale devices, bar-code readers, and electronic patient records. Data mining is a rapidly growing field that is concerned with developing techniques to assist decision-makers to make intelligent use of these repositories. The field of data mining has evolved from the disciplines of statistics and artificial intelligence. This module will combine practical exploration of data mining techniques with a exploration of algorithms, including their limitations. Students taking this module should have an elementary understanding of probability concepts and some experience of programming.
Skills for Robotics Engineering (Undergraduate)
This module is designed to support first year students on the MEng Robotics Engineering programme through the transition from school to university. It will provide students with the opportunity to work with others to develop and share basic practical skills that underpin many first year modules and beyond, foster a sense of enquiry and intellectual curiosity, develop basic graduate attributes that underpin effective student learning, and prepare and encourage students to obtain some work / voluntary experience at an early stage in order to enhance their employability.