2017/18 Undergraduate Module Catalogue

MECH3460 Robotics and Machine Intelligence

20 creditsClass Size: 100

Module manager: Dr Abbas Dehghani
Email: a.dehghani@leeds.ac.uk

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

Year running 2017/18

Pre-requisite qualifications

Students may select this module if either MECH 2650 Mechatronics and Measurement Systems OR MECH 2660 Mechatronics and Robotics Systems have been studied.

Pre-requisites

MECH2620	Vibration and Control
MECH2650	Mechatronics and Measurement Systems
MECH2660	Mechatronics and Robotics Systems

Module replaces

MECH 3160, MECH 3115

This module is not approved as a discovery module

Objectives

- to provide an overview and understanding of robotic systems, including the study of robot manipulators currently used in manufacturing industry, and aspects of mobile robots for providing services in hazardous, space, medical, etc applications
- to provide an overview and understanding of machine intelligence (Soft Computing) and its applications in mechatronic and robotic systems as well as in intelligent controls.

At the end of the module students should be able to:
- describe the different mechanical configurations for robot manipulators
- choose appropriate robot components for a given application (sensors, actuators, powering method, configurations, controllers, etc)
- undertake kinematic analysis of robot manipulators
- analyse the dynamics of planar manipulators
- understand the different methods of providing robot mobility (wheels, legs, tracks, climbing, etc)
- understand the methods for localisation
- appreciate the methods for navigation
- perform basic conceptual designs of mobile robot systems
- understand basic concepts in machine vision and decision making
- describe the social and economic impact of industrial and service robotics
- appreciate the current state and potential for robotics in new application areas (eg medical).

Students will also have an overall view and understanding of the following areas:
- The Human brain and how it functions
- Machine Intelligence
- Artificial Neural Networks and intelligent control
- Fuzzy Logic and intelligent control
- Evolutionary Computation, Genetic Computing
- Hybrid Systems
- Biologically Inspired robotic systems
> Humanoid robots
> Robots inspired from animals

At the end of this part of the module students should be able to:
- design an intelligent control for a mechatronic/robotic system using artificial neural networks;
- design an intelligent control for a mechatronic/robotic system using Fuzzy Logic Control;
- design an intelligent control for a mechatronic/robotic system using a hybrid system.

Skills outcomes
Select robot components and perform kinematic analysis of robot movement, selection of robot sensors, dynamical control of robots, robot navigation.

Design of control systems using soft computing: artificial neural networks, fuzzy logic and hybrid systems.

Syllabus

PART I: INDUSTRIAL ROBOT MANIPULATORS
- Introduction: Robotics: a definition, History, The parts of a robot manipulator system, Robot component modularity, Robot manipulator classification, industrial, economic and social impact of robots
- Kinematics: Definitions, Transformations, Properties of transformation matrices, Forward kinematics, Matlab and the robotics toolbox, Inverse kinematics
- Design: Actuators, Internal state sensors, External state sensors, End effectors, Mechanical arrangement and specification: PUMA 500 series
- Dynamics and control: Inverse Dynamics, Forward Dynamics, Control
- Vision systems: Introduction, vision hardware, image processing, object recognition
- User Interfaces: Input and output devices; force feedback; virtual reality; natural interfaces.

PART II: MOBILE ROBOTICS
- Mobile robots: types of mobility; wheeled, tracked, legged etc, climbing robots
- Localisation; sensors for localisation, odometry, triangulation, trilateration
- Navigation; biological strategies, behaviours, motion planning, path planning
- Autonomous robots; Classical AI, behaviour based, learning
- Service robots; Introduction, application sectors, examples.

Part III: MACHINE INTELLIGENCE
- The Human Brain and How It Functions
- Machine Intelligence
- Comparison between human and machine intelligence
- Artificial neural network and intelligent control
> Linear Separable Patterns and Linear Classification
> Single Layer Perceptron
> Multi-layer Perceptron
> Back Propagation Algorithm
> Radial Basis Function Network
> Kohonen Self-Organisation Network
> Hopfield Network
> Neural Networks in Robotics and Control Applications.

- Fuzzy Logic and intelligent control
> Fuzzy Sets: Definitions and Relations
> Fuzzy Logic and Fuzzy Inference
> Fuzzy Logic Control
> Fuzzy Logic Control Design
> Fuzzy Logic Control Case Examples
> Mamdani and Sugeno Type Fuzzy Logic Systems
> Fuzzy Logic in Robotics and Control Applications.

- Hybrid Systems
> Neuro-Fuzzy control systems

- Biologically inspired robots
> Case studies of humanoid robots
> Case studies of robots inspired from animals.

Teaching methods

Delivery type	Number	Length hours	Student hours
Class tests, exams and assessment	1	1.00	1.00
Class tests, exams and assessment	1	2.00	2.00
Lecture	44	1.00	44.00
Practical	2	2.00	4.00
Private study hours			149.00
Total Contact hours			51.00
Total hours (100hr per 10 credits)			200.00

Private study

Problem sheets. preparation for assignments, reading and revision.

Opportunities for Formative Feedback

Formally through assignments, presentations and less formally through problem sheets.

Methods of assessment

Coursework

Assessment type	Notes	% of formal assessment
Assignment	Assignment 1	30.00
Assignment	Assignment 2	10.00
Report	Lab report	20.00
Total percentage (Assessment Coursework)		60.00

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

Exams

Exam type	Exam duration	% of formal assessment
Standard exam (closed essays, MCQs etc)	1 hr 30 mins	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: 25/04/2018

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