presentacion de robótica

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Robotics in today’s world: Some applications Dra. Am´ erica Berenice Morales D´ ıaz CINVESTAV Unidad Saltillo Abril 2014 Dra. Am´ erica Morales (CINVESTAV) Robotics in today’s world Abril 2014 1 / 41

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Page 1: presentacion de robótica

Robotics in today’s world: Some applications

Dra. America Berenice Morales Dıaz

CINVESTAVUnidad Saltillo

Abril 2014

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video

videoDra. America Morales (CINVESTAV) Robotics in today’s world Abril 2014 2 / 41

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Outline

1 Robotics history

2 Applications

3 Actual Work

4 Conclusions and future trends

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Robotics history

Ancient vision

Greeks: Aristotle writes:

“If every tool, when ordered, or even of its ownaccord, could do the work that befits it... thenthere would be no need either of apprentices forthe master workers or of slaves for the lords.”

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The word “Robot” (1921)

Karel Capek’s play “Rossuum’s UniversalRobots”

“Robot” is coined from Czech word “robota”

“Robota” means labor

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Trademarks of science fiction

Robot Maria in classic SF movie“Metropolis” of Fritz Lang (1926)

Famous R2-D2 (left) and C3PO(right) in SF saga “Star Wars” ofGeorge Lucas (1977)

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Three laws of robotics

According to writer Isaac Asimov:

1 A robot may not harm a human being, or,through inaction, allow a human being to cometo harm.

2 A robot must obey the orders given to it byhuman beings except where such orders wouldconflict with the First Law.

3 A robot must protect its own existence, as longas such protection does not conflict with theFirst or Second Law.

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A definition of “Robot”

Robot Institute of America:

Robot is a reprogrammable, multifunctional manipulator designed tomove material, parts, tools, or specialized devices through variableprogrammed motions for the performance of a variety of tasks.

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Applications: Industrial Robots

Manufacturing

(a) Cartesian (b) Delta

(c) Manipulator

Fig. 1 : Manufacturing Robots.Dra. America Morales (CINVESTAV) Robotics in today’s world Abril 2014 9 / 41

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Industrial robots

Beer industry

(a) Mexico (PiedrasNegras, Coah.)

(b) Holland

(c) Germany (d) Argentina

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Medicine

(a) Exosqueleton

(b) Scanner (c) DaVinci

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Medicine

Rehabilitation

(a) Prosthesis (b) Rehabilitation

(c) Bionic hand

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Space

(a) satellite (b) Kirobo

(c) Curiosity (d) Spiderfab

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Household robots

(a) Roomba (b) Luna

(c) Scooba

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Entertainment robots

(a) Aibo

(b) Bioloid (c) Lego mindstorms

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Autonomous Guided Vehicles

(a) Google car

(b) Line follower (c) Kiva

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Humanoids

(a) HRP-2 (b) Nao

(c) Darwin (d) HRP-4

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Surveillance

(a) PIAP (b) ASV (c) Riotbot

(d) Drone (e) UAV

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Formations

(a) Pioneer (b) UAV

(c) UAV (d) Epucks

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What we need to know?

Robotics

Algebra

Differential equations

Control

Electronics

Programming

Mechanics

Phisics

Signal processing

Artificial vision

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Actual work

Fig. 2 : The actual and desired coordinates of the unicycle eq. (1).

xi = vi cos(θi)

yi = vi sin(θi) (1)

θi = ωi

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Actual work (cont.)

xei = cosθi(xri − xi) + sinθi(yri − yi)yei = −sinθi(xri − xi) + cosθi(yri − yi) (2)

θei = θri − θi

xei = ωiyei − vi + vricosθei

yei = −ωixei + vrisinθei (3)

θei = ωri − ωi

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Actual work (cont.)

Fig. 3 : A formation composed of 4 vehicles with a known virtual center.

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all-to-all syncronization control

vi = vri cos θei +Kxi

xei + n∑j=1

Cxij(xei − xej)

(4)

ωi = ωri +Kθiθei + vrisin θeiKCyi

θeiαi+yei + n∑

j=1

Cyij(yei − yej )

; for i 6= j (5)

with αi =√K2 + (xei)2 + (yei)2 +

∑nj=1 [(xei − xej)2 + (yei − yej)2]

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Tracking

−0.6 −0.4 −0.2 0 0.2 0.4 0.6 0.8

−0.4

−0.2

0

0.2

0.4

0.6

xri,x

i

yr i,y

i

x

1(0),y

1(0)

Robot1

x2(0),y

2(0)

Robot2

x3(0),y

3(0)

Robot3

Trajectory

Fig. 4 : Tracking evolution with control (4) and (5) for three robots swarm.

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Incorporation 1 robot

−0.8 −0.6 −0.4 −0.2 0 0.2 0.4 0.6 0.8 1−0.8

−0.6

−0.4

−0.2

0

0.2

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xri,x

i

yri,

yi

Cartesian trajectories

x1(0),y

1(0)

Robot1

x2(0),y

2(0)

Robot2

x3(0),y

3(0)

Robot3

Trajectory

Fig. 5 : Entrance of a new element in the formation.

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Incorporation multiple robots

−0.8 −0.6 −0.4 −0.2 0 0.2 0.4 0.6 0.8−0.8

−0.6

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0

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xri, x

i

yri, y

i

Cartesian trajectories: multiple merging

x

1(0),y

1(0)

Robot1

x2(0),y

2(0)

Robot2

x3(0),y

3(0)

Robot3

x4(0),y

4(0)

Robot4

x5(0),y

5(0)

Robot5

x6(0),y

6(0)

Robot6

merging ofnew robots

Fig. 6 : Incorporation of several robots with controller in experiments: XYcoordinates.

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Experimental Setup

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Experimental Setup (cont.)

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Experimental Setup (cont.)

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Experimental Setup (cont.)

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Experimental Setup (cont.)

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Implementation

Fig. 7 : Data acquisition for our collision avoidance strategy.

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Inertial data adquisition

Fig. 8 : Microcontroller Arduino board with embedded IMU.

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Collision avoidance

Two formations in the same path, opposite directions.

−1 −0.5 0 0.5 1−1

−0.8

−0.6

−0.4

−0.2

0

0.2

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1

1 23

4

5

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Cartesian coordinates

xri, xi

yri,yi

Robot1

Robot2

Robot3

Robot4

Robot5

Robot6

Fig. 9 : Cooperative collision avoidance betweeen two formations

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Delay effect

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Delay effect (cont.)

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Delay effect (cont.)

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Delay effect (cont.)

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Conclusions and future trends

Group coordination in a robot group is an interesting topic that has beenreceive a lot of attention the las decade.

Many applications have been done: drones, surveillance, map recognition,exploration, in the fuel company, among others.

Future trends can be encountered in:

Automated highways (AHDA see:https://www.youtube.com/watch?v=4pMO475heog)Manufacturing systems (see Kiva Systems,https://www.youtube.com/watch?v=lWsMdN7HMuA).

In the future trends we have coordination in unstructured environments forservice robot at home and also in the industry in general for un identicalrobots.

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Thanks!, questions???

{america.morales,hugo.gutierrez,hector.perez,flabio.mirelez}@cinvestav.edu.mx

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