2023/24 Undergraduate Module Catalogue

MECH3465 Robotics and Machine Intelligence

20 creditsClass Size: 60

Module manager: Prof Peter Culmer
Email: P.R.Culmer@leeds.ac.uk

Taught: Semesters 1 & 2 (Sep to Jun) View Timetable

Year running 2023/24

Pre-requisites

MECH1010	Computers in Engineering Analysis
MECH2620	Vibration and Control
MECH2650	Mechatronics and Measurement Systems

This module is not approved as a discovery module

Module summary

This module will provide students with technical skills in the design and construction of robotic devices, programming of robotic controllers, as well as an understanding of their limitations. The module will also provide an introduction to Machine (or Artificial) intelligence (where systems emulate the human mind to learn, solve problems and make decisions on the fly, without needing the instructions specifically programmed), with applications in robotics such as route planning and obstacle avoidance. The module will also explore the ethical and societal implications of robotics and AI, as well as the challenges faced in designing and building intelligent machines.

Objectives

On completion of this module students should acquire a good understanding of the scientific principles of robotic system design i.e. sensors, actuators, powering methods, controllers, navigation. Students will be able to; select robot components, perform kinematic analysis of robot movement, and dynamically control robots using soft computing: artificial neural networks, fuzzy logic and hybrid systems.

Having completed the module students should be able to formulate a design of a robotic system that satisfies a given requirement (select, compare, contrast, understand limitations and apply appropriate methods).

Learning outcomes
1. describe the different mechanical configurations for robot manipulators
2. choose appropriate robot components for a given application (sensors, actuators, powering method, configurations, controllers, etc)
3. undertake kinematic analysis of robot manipulators
4. analyse the dynamics of planar manipulators
5. understand the different methods of providing robot mobility (wheels, legs, tracks, climbing, etc)
6. understand the methods for localisation
7. appreciate the methods for navigation
8. perform basic conceptual designs of mobile robot systems
9. understand basic concepts in machine vision and decision making
10. describe the social and economic impact of industrial and service robotics
11. appreciate the current state and potential for robotics in new application areas (e.g. medical).

Upon successful completion of this module the following UK-SPEC learning outcome descriptors are satisfied:
- A comprehensive knowledge and understanding of the scientific principles and methodology necessary to underpin their education in their engineering discipline, and an understanding and know-how of the scientific principles of related disciplines. to enable appreciation of the scientific and engineering context, and to support their understanding of relevant historical, current and future developments and technologies. (SM1m)

- Knowledge and understanding of mathematical and statistical methods necessary to underpin their education in their engineering discipline and to enable them to apply a range of mathematical and statistical methods, tools and notations proficiently and critically in the analysis and solution of engineering problems (SM2m)

- Ability to apply and integrate knowledge and understanding of other engineering disciplines to support study of study of their own engineering discipline and the ability to evaluate them critically and to apply them effectively (SM3m)

- Awareness of developing technologies related to mechanical engineering (SM4m)

- A comprehensive knowledge and understanding of mathematical and computational models relevant to the engineering discipline and an appreciation of their limitations (SM5m)

- Understanding of concepts from a range of areas, including some outside engineering, and the ability to evaluate them critically and to apply them effectively in engineering projects (SM6m)

- Understanding of engineering principles and the ability to apply them to undertake critical analysis of key engineering processes (EA1m)

- Ability to identify, classify and describe the performance of systems and components through the use of analytical methods and modelling techniques (EA2)

- Ability to apply quantitative and computational methods, using alternative approaches and understanding their limitations, in order to solve engineering problems and implement appropriate action (EA3m)

- Understanding of, and the ability to apply, an integrated or systems approach to solving complex engineering problems (EA4m)

- Demonstrate the ability to generate an innovative design for products, systems, components or processes to fulfil new needs (D8m)

- Knowledge and understanding of the commercial, economic and social context of engineering processes (EL2)

- Knowledge of characteristics of particular equipment, processes or products, with extensive knowledge and understanding of a wide range of engineering materials and components (P2m)

- Ability to apply relevant practical and laboratory skills (P3)

- Ability to work with technical uncertainty (P8)

- Ability to apply engineering techniques taking account of a range of commercial and industrial constraints (P10m)

- Apply their skills in problem solving, communication, information retrieval, working with others, and the effective use of general IT facilities (G1)

Syllabus

PART I: INDUSTRIAL ROBOT MANIPULATORS
- Introduction to robotic components
- Economic and social impacts
- Kinematics: transformations and the robotics (Matlab) toolbox
- Design: actuators, effectors and sensors and their mechanical arrangements
- Dynamics and control
- Vision systems
- User Interfaces

PART II: MOBILE ROBOTICS
- Mobile robots: wheeled, tracked, legged, climbing
- Localisation and navigation
- Autonomous robots

Part III: MACHINE INTELLIGENCE
- Comparison between human and machine intelligence
- Artificial neural network and intelligent control
- Fuzzy Logic and intelligent control
- Hybrid Systems
- Biologically inspired robots

Teaching methods

Delivery type	Number	Length hours	Student hours
Lecture	44	1.00	44.00
Practical	2	2.00	4.00
Private study hours			152.00
Total Contact hours			48.00
Total hours (100hr per 10 credits)			200.00

Opportunities for Formative Feedback

Skills in robotics are best established through a combination of taught material supported by problem sheets and worked assignments provide a route to develop the required skills and provide formative feedback.

Methods of assessment

Coursework

Assessment type	Notes	% of formal assessment
Assignment	Lab assignment	30.00
Assignment	Design assignment	30.00
Total percentage (Assessment Coursework)		60.00

A formative in-course MCQ assessment will be included in semester 2. A coursework resit will be available for students that fail the module having passed the exam, otherwise students will take a resit exam.

Exams

Exam type	Exam duration	% of formal assessment
Unseen exam	2 hr	40.00
Total percentage (Assessment Exams)		40.00

Normally resits will be assessed by the same methodology as the first attempt, unless otherwise stated

Reading list

The reading list is available from the Library website

Last updated: 28/11/2023

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