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COMP52815: Robotics - Planning and Motion

It is possible that changes to modules or programmes might need to be made during the academic year, in response to the impact of Covid-19 and/or any further changes in public health advice.

Type Tied
Level 5
Credits 15
Availability Available in 2024/2025
Module Cap None.
Location Durham
Department Computer Science

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 Combinations 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

ActivityNumberFrequencyDurationTotalMonitored
Lectures81 per week2 hours16 
Seminars81 per week2 hours16 
Preparation and Reading118 
Total150 

Summative Assessment

Component: CourseworkComponent Weighting: 100%
ElementLength / DurationElement WeightingResit Opportunity
Coursework 100 

Formative Assessment

Feedback on coursework.

More information

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