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Robots for the Kid in All of Us Nikhil J. Nanivadekar Robots for the Kid in All of Us

GS.com/Engineering Nikhil J. Nanivadekar

Introduction Agenda AGENDA

Demos Dijkstra’sAlgorithm on EV3 JREvs Compact Profiles Dijkstra’s A*and Algorithm at a glance Java vs EV3 Programmer App LiveProgramming Demo Robot video Robot

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• Agenda Robot Video ROBOT VIDEO

https://youtu.be/EXdtbkYDRgI Robot Video AGENDA

Demos Dijkstra’sAlgorithm on EV3 JREvs Compact Profiles Dijkstra’s A*and Algorithm at a glance Java vs EV3 vs Java Programmer App LiveProgramming Demo Robotvideo

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• Agenda Java vs EV3 Programmer App EV3 PROGRAMMER APP 10

Availableat Mindstorms website interface Legos Visual graphical and programming EV3 ProgrammerAppdistributed by

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• EV3 Programmer App LEJOS 11

open source Bettermotor control,faster processing, project Doesnot run Lego software Write codesimilar toa standardJava Runsstandard Java Virtual machine

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• Lejos THIRD PARTY LIBRARIES

12 is a JavaVirtual Machine

Run similarRun to a standardJavaproject classpath Easyintegration with third partylibraries Upload jarsto EV3on and reference Lejos

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• Third Party Libraries AGENDA 13

Demos Dijkstra’sAlgorithm on EV3 JREvs Compact Profiles Dijkstra’s A*and Algorithm at a glance Java vs EV3 Programmer App Demo Programming Live Robotvideo

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• Agenda Live Programming Demo AGENDA 15

Demos JREvs Compact Profiles glance Dijkstra’sAlgorithm on EV3 Dijkstra’s and A* Algorithm at a a at A* and Algorithm Dijkstra’s Java vs EV3 Programmer App LiveProgramming Demo Robotvideo

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• Agenda Dijkstra’s and A* Algorithm at a glance DIJKSTRA’S ALGORITHM 17

W. Dijkstra

Edsger

Conceived by Leastcost path can be a longer path nodes Each node hascost for traversal Findleast the costpathsource fromto all

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• Dijkstra’s Algorithm DIJKSTRA’S ALGORITHM 18

Wikipedia(Dijkstra’s Algorithm) Wikipedia(Dijkstra’s Source:

Dijkstra’s Algorithm A* ALGORITHM 19

towards the goal Heuristic can be anything Add a heuristicto guide the program (distance, time, etc.) Extension to Dijkstra’s Algorithm

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• A* Algorithm ALGORITHM FUNCTIONS

20 on

h: heuristic functi

f(n) = c(n) + h(n) + c(n) = f(n) f(n) = c(n) = f(n)

c: cost function A* Dijkstra – –

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Algorithm Functions AGENDA 21

Demos Dijkstra’s Algorithm on EV3 on Algorithm Dijkstra’s JREvs Compact Profiles Dijkstra’s A*and Algorithm at a glance Java vs EV3 Programmer App LiveProgramming Demo Robotvideo

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• Agenda Dijkstra’s Algorithm on EV3 PROBLEM STATEMENT 23

absolutedistance absolutedistance Motion in ydirection costs2xthe Motion in xdirection costs1xthe Solve themaze

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• Problem Statement

PROBLEM STATEMENT 24 Problem Statement GRAPH 25

-ordinates

nodes Useadjacency matrix, color datato get Forms an adjacency matrix of Red:Traversable Blue: Obstacle y co x, UseRGB data of maze

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• Graph GRAPH

= = 26 );

), ),

GRAPH 0

> > <>(); Map Point < HashMap 0, Point( Map

Int Int Object (newput new

. GRAPH // Red = 256, Blue = 1 = Blue = 256, Red // MutableObject MutableObjectInt Storenode, color data in a

• Graph SUCCESSORS

27 4);

{

) > {

> successors = ) > 1) .withInitialCapacity( negativeX (point .get( .get successors.add(negativeX ); GRAPH

Sets.mutable

GRAPH ... return successors; } MutableSet

}

if(

Successors COST FUNCTION 28

()); .getY .getX()); (

abs point2 point2 .abs( getCost( yCost;

* Math. () – () – + , ) { Math 2 = = .getY .getX xCost point1 point2 yCost xCost

point1 point1

return int Point Point int

public static int

Cost FunctionCost } PRIORITIZATION 29

minBy( )); .get(each . getNodeToVisit(

Point> verticesToSearch ) { > vertexCostMap verticesToSearch point,

each -

return Point SetIterable<

}

public static Point

Prioritization PRIORITIZATION 30

MAX_VALUE . Each timenode isvisited; update withleast cost visit to Map ofnode tocost tovisit Initialized with allnode costs tobe Integer

– – –

vertexCostMap: Prioritization PATH

{

; (path.peek()));

.get

; = true > path = .empty();

(

isPathComplete) { isPathComplete = false nodeBackpointerMap start (!

isPathComplete path.push else

} } if ( Stacks

Path

while

return path; }

boolean

MutableStack

PATH: DIJKSTRA’S

Path: Dijkstra’s PATH: A* | 2 point y

–

33 endpoint |y

+ | 2 point x

–

endpoint |x

Heuristic

Path: A* PATH: A* | 2 point x

–

34 endpoint |y

+ | 2 point x

–

endpoint |x

Heuristic

Path: A* MOTION UNINTERRUPTED 35

times Howto makerobot move smoothly? Robotmoves to node node, pausing225 Path comprisedof226 nodes

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• Motion Uninterrupted MOTION UNINTERRUPTED 36 node hasthe

Different heading: Compute the angle the robot needs to turn Same heading: Mark it to be flattenedSamebe heading: to Markit

– – Hence,achieving motion uninterrupted peekingin thefuture Checkif the next Flattenthe pathmotion during by sameheading

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• Motion Uninterrupted AGENDA 37

Demos Dijkstra’sAlgorithm on EV3 Profiles Compact JRE vs Dijkstra’s A*and Algorithm at a glance Java vs EV3 Programmer App LiveProgramming Demo Robotvideo

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• Agenda Performance of JRE vs Compact Profiles JRE VS COMPACT PROFILES 39

Compact Profiles Overview Source:

Stripped downversion of JRE into subsets

• JRE vs Compact Profiles PERFORMANCE COMPARISON

54 80 15 22

115 40 Full JRE (Times) in

49 80 13 22 110

Compact2 (Times) in Compact Profiles Overview up - Source:

Task

up -

A* algorithm EV3 start start execution Program initialization Graph algorithm Dijkstra’s Performance Comparison Performance EMPIRICAL OBSERVATIONS 41

What aboutthe memoryfootprint? Is the performance consistent? Whatthe jar about sizes? Doesit stopmid -execution?

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• Empirical Observations AGENDA 42

Demos Dijkstra’sAlgorithm on EV3 JREvs Compact Profiles Dijkstra’s A*and Algorithm at a glance Java vs EV3 Programmer App LiveProgramming Demo Robotvideo

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• Agenda Demos Learn more at GS.com/Engineering

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