Current postgraduate taught students
COMP60492: Robotics (2007-2008)
This course unit introduces students to robotic systems coving multi-link robotic systems, mobile robotic systems, actuators, sensors, biologically inspired robotics and machine learning techniques. The main aim is to give students an introduction to the field, historic background, development and current cutting edge research points, as well as a practical introduction how to move and control robots. The course unit is practical, and students will be given access to robots for exercises.
At the end of the course unit students will be able to:
1. Describe different mechanical configurations for robot manipulators
2. Have an understanding of the functionality and limitations of robot actuators and sensors
3. Undertake kinematic analysis of robot manipulators
4. Understand the importance of robot dynamics
5. Understand and be able to apply a variety of techniques to solve problems in areas such as robot control and navigation
6. To be able to program a robot to perform a specified task
7. Understand how simulations of robots work, where they can be useful and where they can break down.
8. Appreciate the current state and potential for robotics in new application areas.
Assessment of Learning outcomesUnderstanding of the topics covered in the course is assessed in two ways. A 2 hour examination covers the students understanding of the theoretical issues, such as robot control paradigms, machine learning techniques, actuator and sensor theory. The ability to use this knowledge in a practical manner is tested through practical sessions with robots. Practical sessions are marked by the lab demonstrators.
Contribution to Programme Learning OutcomesThe course contributes towards knowledge and understanding of Computer Science through its practical orientation towards programming robots, signal processing in real time, controller architecture and hardware issues. Intellectual skills are trained through the analysis of control problems, identification of ways of solving them and implementation of the solution. Successes or failures are immediately evident through the resulting robot behavior. Practical skills are trained through the practical sessions of the course. Finally transferable skills are trained by having to work tight (lab session) deadlines working in groups during practical sessions, understanding task statements, analyzing them and solving problems.
Skills include: A1, A2, B2, B3, C1, D1, D4
Definitions and history of robotics.
Sensors and actuators
Types of actuator, types of sensor.
Robot design, biologically inspired robotics, kinematics, dynamics, locomotion, control.
Autonomous mobile robotic systems
Benefits, problems, suitable tasks, machine learning, navigation.
Simulation of a robot and its environment. Assessment of simulation accuracy. Model acquisition and validation.
There is no set text for this course, and the lecture notes aim to be self-contained. However, the reading list will provide useful supporting material for certain sections of the course.
Core TextTitle: Introduction to Robotics
Author: H.S. Sandhu
Publisher: Special Interest Model Books
Supplementary TextTitle: Introduction to AI Robotics
Author: Robin R. Murphy
Publisher: MIT Press Ltd