Business School Computing Division
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Business School Computing Division. Colin Price “Learning Programming with Simulated Robots : IDE for Local and Distance (blended) Learning”. Overview of Programming at UCW. Programming. Digital Technologies. X86 assembler. Level 1. VBasic. Digital Tech. FSM. Neural Nets. Level 2.

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Business School Computing Division

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Business school computing division

Business School Computing Division

Colin Price

“Learning Programming with Simulated Robots :

IDE for Local and Distance (blended) Learning”

HEAcademy


Overview of programming at ucw

Overview of Programming at UCW

Programming

Digital Technologies

X86 assembler

Level 1

VBasic

Digital Tech.

FSM

Neural Nets

Level 2

“C”

OOP

VBasic

Operating Sys.

Multi-tasking

Level 3

VBasic

Comp. Architecture

OOP

X86 assembler

Concepts and Philo.

MSc.

RISC assembler

FSM

OOP

Neural Nets

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Oop level 2 3 java

OOP Level 2 & 3 = Java

Web Page

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Our integrated environment

Our Integrated Environment

Distributed Simulator

Simulator

Robot

mController

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Rationale

Rationale

  • CS Students may need to learn:

  • Various programming paradigms

  • Various programming languages

  • Operating Systems

  • Embedded Systems, Control

  • Artificial Intelligence

Simulator

Integrated Environment provides unifying thread connecting learning modules.

Robot

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Characteristics of this ide

Characteristics of this IDE

  • Same souce code runs on Robots as in the Simulator

  • Robot and Simulator engines ‘isomorphic’

  • Same visual Robot World used for all languages (C, Java, FSM, NNet, LISP)

  • Principal programming paradigm is ‘Concurrent’

  • Hardware is cheap, is ‘Industry Standard’

  • Situates Computing in broader context of Cognitive Science, Ubiquitous Computing, Social Science

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Why program robots

Why program robots?

  • Commercially viable

  • Serious promise of AI

  • Good vehicle for integrated learning of Programming

  • Analogy of living beings

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Business school computing division

Human Qualities

Cognitive

Psychomotoric

Affective

Acting

Thinking

Feelings

Behaving

Knowing

Emotions

Braitenberg Vehicles

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Programming behaviour

Programming Behaviour

Multi-tasking

Collide

bumper

public void collide() {

}

Searchlight

public void searchlight() {

}

CPU

eyes

public void wander() {

for(;;) {

wander_flag = true;

wanderOpL = 10;

wanderOpR = 10;

muMonSleep(500);

}

}

Wander

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Combining behaviours

bumper

Avoid

s

eyes

Seek Light

s

Wander

s

Motors

Combining Behaviours

Subsumption (Brookes)

Schemas (Arkin)

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M robot demo

mRobot Demo

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Approaches to learning programming

Approaches to Learning Programming

Other important paradigms

Deploying this Environment

FSM

  • Year 1 students

    • FSM, Neural Nets

  • Year 2 students

    • Multitasking OS

  • Year 3 students

    • FSM, Neural Nets

NNet

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Finite state machine paradigm

Finite State Machine Paradigm

FSM Table

Robot World

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Neural net tool

Neural Net Tool

L

Training Set

Learned Controller

R

eyes

motors

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Nnet demo

NNet Demo

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Physical m robot

Physical “mRobot”

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Os teaching board

OS Teaching Board

RS 232

http://www.keil.com/

MBC900 Philips 89LPC932

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Pedagogical dimension

Pedagogical Dimension

  • Rapid, efficient, visual, fun learning to program

  • Skills transferable: ‘C’ and ‘Java’; 3 program constructs

  • Programming for action, interaction

  • Unrolling the constraints of the IDE, discover OO paradigm

  • Application of physics and math

  • Links between artificial and natural systems

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Distributed version

ID

ID

Distributed Version

  • one student one robot

  • tutor selects robot world

  • chat area

  • self-organization ?

chat

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Pedagogy of distributed system

Pedagogy of Distributed System

  • Collaborative learning by common goal

  • Peer evaluation of programming success

  • Peer negotiation of tasks to meet learning outcomes

  • ? Formation of ad hoc learning groups

  • ? Management of ad hoc learning groups

  • ? Monitoring of individuals’ learning within groups

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Business school computing division

Structure of Distributed System

Student (client)

Tutor (client)

Server

controller code

Server maintains lists

javac

engine

chat

Info xfer via RMI calls

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Current applications

Current Applications

  • ODEs Solver

  • Digital Simulator

  • Robot Programming

1

2

3

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Future agent technology

Future – Agent Technology

Java Applet

Java Applet

Java Applet

Java RMI Server

Java Servlet

Students (client)

Tutor (client)

Server

Java Agent

Java Agent

Java Agent

Role of Agents :

  • negotiate formation of learning groups

  • monitor dynamics of groups

  • pedagogic – adapt learning materials

(a)synchronous

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Summary

Summary

  • Provides integration of programming effort

  • Multi-language ( “C”, “Java”)

  • Multi-paradigm: Concurrent, Procedural, FSM, NNet, Agent

  • Generalisable: Replace Robot with Atoms

  • Pedagogically interesting: Formation and Management of learning groups

  • Situates Computing in broader context of Cognitive Science, Ubiquitous Computing, Social Science, Philosophy, …

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Acknowledgements

Acknowledgements

Support Received from

http://www.keil.com/

Hitex Ltd.Warwick University, Science Park Coventry CV4 7EZ

http://www.hitex.co.uk

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