Postgraduate Programme and Module Handbook 2023-2024 (archived)
Module COMP52815: Robotics - Planning and Motion
Department: Computer Science
COMP52815: Robotics - Planning and Motion
Type | Tied | Level | 5 | Credits | 15 | Availability | Available in 2023/24 | Module Cap | None. |
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Tied to | G5T509 |
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Prerequisites
- None
Corequisites
- COMP52615 Computer Vision; COMP52715 Deep Learning for Computer Vision and Robotics; PHYS51915 Introduction to Machine Learning and Statistics; PHYS52015 Introduction to Scientific and High Performance Computing
Excluded Combination of Modules
- None
Aims
- Develop knowledge of key concepts, approaches and algorithms in Robotics related to the planning and motion of one or multiple robotic platforms.
- Develop critical understanding and appreciation of current theoretical and empirical research in robotics and its application within industry.
Content
- Themes will be chosen from contemporary areas of robotics including the following:
- general overview of the field of robotics;
- robot classification;
- position and orientation;
- typical actuators/sensors and basic/classical feedback control;
- kinematics and dynamics of mobile robots;
- simultaneous localisation and mapping (SLAM);
- path planning and obstacle avoidance.
Learning Outcomes
Subject-specific Knowledge:
- By the end of the module students should have:
- developed a critical understanding of the contemporary robotics topics presented, how these are applicable to relevant real-world problems and have future potential for emerging needs in both a research and industrial setting;
- developed an advanced knowledge of the principles and practice of analysing relevant robotic planning and motion algorithms for problem suitability;
- developed a good understanding of managing the trade-off between task performance and processing requirements within the context of robotics;
- explored the most recent advancements in the relevant academic literature and developed a critical understanding of their implications for current industry practice.
Subject-specific Skills:
- By the end of the module, students should have developed highly specialised and advanced technical, professional and academic skills that enable them to:
- formulate and solve problems that involve the use of robotics for a range of control, motion and planning tasks using a range of algorithmic approaches;
- develop robotics control, motion and planning software solutions and use appropriate algorithms and approaches to address both industrial and research application tasks.
Key Skills:
- Written communication;
- Planning, organising and time management;
- Problem solving and analysis;
- Using initiative;
- Adaptability;
- Numeracy;
- Computer literacy.
Modes of Teaching, Learning and Assessment and how these contribute to the learning outcomes of the module
- A combination of lectures, seminars, and guided reading will contribute to achieving the aims and learning outcomes of this module.
- The summative written assignment will test students' knowledge and critical understanding of the material covered in the module, their analytical and problem-solving skills.
Teaching Methods and Learning Hours
Activity | Number | Frequency | Duration | Total/Hours | |
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Lectures | 10 | 2 per week | 2 hours | 20 | |
Seminars | 6 | 2 per week | 2 hours | 12 | |
Preparation and Reading | 118 | ||||
Total | 150 |
Summative Assessment
Component: Coursework | Component Weighting: 100% | ||
---|---|---|---|
Element | Length / duration | Element Weighting | Resit Opportunity |
Coursework or Take-Home Exam | 48 hours | 100% |
Formative Assessment:
Feedback on coursework/take-home exam.
■ Attendance at all activities marked with this symbol will be monitored. Students who fail to attend these activities, or to complete the summative or formative assessment specified above, will be subject to the procedures defined in the University's General Regulation V, and may be required to leave the University