Autonomous Robotic Systems
| Code | School | Level | Credits | Semesters |
| COMP4082 | Computer Science | 4 | 20 | Autumn Malaysia |
- Code
- COMP4082
- School
- Computer Science
- Level
- 4
- Credits
- 20
- Semesters
- Autumn Malaysia
Summary
This module introduces the main concepts of autonomous mobile robotics, providing an understanding of the hardware and software principles appropriate for control, spatial localisation and navigation. The module consists of theoretical concepts around robotic sensing and control in the lectures, together with a strong practical element for robot programming in the laboratory sessions. Spending two hours each week in lectures, 2 hours in supervised labs - with an additional (optional) two-hour self-guided practical session - the students will work towards building different robotic solutions through a term-long project to demonstrate an understanding of the theory in one or more realistic application scenarios.
Target Students
Available to Level 3 and Level 4 students in the School of Computer Science. This module is not available to students not listed above, without explicit approval from the module convenor(s). Prior knowledge in computer programming is required. This module is part of the Programming theme in the School of Computer Science.This module is part of the AI, Modelling and Optimisation theme in the School of Computer Science. There is a limited number of places on this module. Students are reminded that enrolments which are not agreed by the Offering School in advance may be cancelled without notice.
Classes
- One 2-hour practicum each week for 11 weeks
- One 2-hour lecture each week for 11 weeks
- One 2-hour computing each week for 11 weeks
Activities may take place every teaching week of the Semester or only in specified weeks. It is usually specified above if an activity only takes place in some weeks of a Semester Further Activity Details: Activities may take place every teaching week of the semester or only in specified weeks It is usually specified above if an activity only takes place in some weeks of a semester.
Assessment
- 100% Coursework: Laboratory assignment and associated report and viva demonstration. Reassessment is 100% exam.
Educational Aims
To provide a grounding in the basic principles and application of real-world sensors, actuators, and autonomous mobile robots; and to give experience in implementing robotic behaviour algorithms, with a strong emphasis on reinforcement learning.Learning Outcomes
Knowledge and Understanding:
• Experience in implementing algorithms in a real-world (or simulated) robotic context (e.g., robotic control, sensor data handling).
• Understanding of current technologies and techniques in autonomous mobile robotics and an awareness of their limitations.
• Understanding of how to handle and interpret uncertain sources of information.
Intellectual Skills:
• Apply knowledge of robotic control techniques to particular tasks.
• Apply knowledge of uncertain data sources (such as sensors) within applications.
• Evaluate and compare competing approaches to robotics and real-world sensor-driven applications.
Professional Skills:
• Develop a working knowledge of real-world device programming (sensors and actuators) through implementing robotic behaviour architectures.
• Apply hardware insights to the development of software solutions.
• Develop advanced skills for multi-source data aggregation.
• Develop skills in peer programming.
Transferable Skills:
• Apply knowledge of the methods and approaches presented to other problem domains, in particular knowledge gained about computing with real-world information gathered from sensors, e.g., to mobile device programming.
• Use the available resources (libraries, internet, etc) to supplement the course material.
• Developing effective team-working strategies.
Conveners
- Dr Tomas Henrique Bode Maul