基于RaspberryPI的履带式机械臂智能小车外文翻译

外文翻译

An

adaptive

dynamic

controller

for

autonomous

mobile

robot

rajectory

trackingabstract

This

paper

proposes

an

adaptive

controller

to

guide

an

unicycle-like

mobile

robotduring

trajectory

tracking.

Initially,

the

desired

values

of

the

linear

and

angularvelocities

are

generated,

considering

only

the

kinematic

model

of

the

robot.

Next,such

values

are

processed

to

compensate

for

the

robot

dynamics,

thus

generating

thecommands

of

linear

and

angular

velocities

delivered

to

the

robot

actuators.

Theparameters

characterizing

the

robot

dynamics

are

updated

on-line,

thus

providingsmaller

errors

and

better

performance

in

applications

in

which

these

parameters

canvary,

such

as

load

transportation.

The

stability

of

the

whole

system

is

analyzed

usingLyapunov

theory,

and

the

control

errors

are

proved

to

be

ultimately

bounded.Simulation

and

experimental

results

are

also

presented,

which

demonstrate

the

goodperformance

of

the

proposed

controller

for

trajectory

tracking

under

different

loadconditions.

1.

Introduction

Among

different

mobile

robot

structures,

unicycle-like

platforms

are

frequentlyadopted

to

accomplish

different

tasks,

due

to

their

good

mobility

and

simpleconfiguration.

Nonlinear

control

for

this

type

of

robot

has

been

studied

for

severalyears

and

such

robot

structure

has

been

used

in

various

applications,such

as

surveillance

and

floor

cleaning.

Other

applications,

like

industrial

load

transportationusing

automated

guided

vehicles

(AGVs)

automatic

highway

maintenance

andconstruction,

and

autonomous

wheelchairs,

also

make

use

of

the

unicycle-like

structure.

Some

authors

have

addressed

the

problem

of

trajectory

tracking,

a

quiteimportant

functionality

that

allows

a

mobile

robot

to

describe

a

desired

trajectorywhen

accomplishing

a

task.

An

important

issue

in

the

nonlinear

control

of

AGVs

is

that

most

controllersdesigned

so

far

are

based

only

on

the

kinematics

of

the

mobile

robot.

However,

when

high-speed

movements

and/or

heavy

load

transportation

arerequired,

it

becomes

essential

to

consider

the

robot

dynamics,

in

addition

to

itskinematics.

Thus,

some

controllers

that

compensate

for

the

robot

dynamics

have

beenproposed.

As

an

example,

Fierro

and

Lewis

(1995)

proposed

a

combined

kinematic/torquecontrol

law

for

nonholonomic

mobile

robots

taking

into

account

the

modeled

vehicledynamics.

The

control

commands

they

used

were

torques,

which

are

hard

to

deal

with

when

regarding

most

commercial

robots.

Moreover,

only

simulation

results

werereported.

Fierro

and

Lewis

(1997)

also

proposed

a

robust-adaptive

controller

based

onneural

networks

to

deal

with

disturbances

and

non-modeled

dynamics,

althoughnot

reporting

experimental

results.

Das

and

Kar

(2006)

showed

an

adaptive

fuzzylogic-based

controller

in

which

the

uncertainty

is

estimated

by

a

fuzzy

logic

systemand

its

parameters

were

tuned

on-line.

The

dynamic

model

included

the

actuatordynamics,

and

the

commands

generated

by

the

controller

were

voltages

for

the

robotmotors.

The

Neural

Networks

were

used

for

identification

and

control,

and

the

controlsignals

were

linear

and

angular

velocities,

but

the

realtime

implementation

of

their

solution

required

a

high

-performance

computer

architecture

based

on

a

multiprocessorsystem.

Ontheotherhand,DeLaCruzandCarelli(2006)proposedadynamicmodelusinglinearandvelocitiesasinputs,andshowedthedesignofatrajectorytrackingcontrollerbasedontheirmodel.Oneadvantageoftheircontrolleristhatitsparametersaredirectlyrelatedtotherobotparameters.However,iftheparametersarenotcorrectlyidentifiedoriftheychangewithtime,forexample,duetoloadvariation,theperformanceoftheircontrollerwillbeseverelyaffected.Toreduceperformancedegradation,on-lineparameteradaptationbecomesquiteimportantinapplicationsinwhichtherobotdynamicparametersmayvary,suchasloadtransportation.Itisalsousefulwhentheknowledgeofthedynamicparametersislimitedordoesnotexistatall.Inthispaper,anadaptivetrajectory-trackingcontrollerbasedontherobotdynamicsisproposed,anditsstabilitypropertyisprovedusingtheLyapunovtheory.Thedesignofthecontrollerwasdividedintwoparts,eachpartbeingacontrolleritself.Thefirstoneisakinematiccontroller,whichisbasedontherobotkinematics,andthesecondoneisadynamiccontroller,whichisbasedontherobotdynamics.Thedynamiccontrolleriscapableofupdatingtheestimatedparameters,whicharedirectlyrelatedtophysicalparametersoftherobot.Bothcontrollersworkingtogetherformacompletetrajectory-trackingcontrollerforthemobilerobot.Thecontrollershavebeendesignedbasedonthemodelofaunicycle-likemobilerobotproposedbyDeLaCruzandCarelliAs-modificationtermisappliedtotheparameter-updatinglawtopreventpossibleparameterdrift.Theasymptoticstabilityofboththekinematicandthedynamiccontrollersisproven.Simulationresultsshowthatparameterdriftdoesnotariseevenwhenthesystemworksforalongperiodoftime.Experimentalresultsregardingsuchacontrollerarealsopresentedandshowthattheproposedcontrolleriscapableofupdatingitsparametersinordertoreducethetrackingerror.Anexperimentdealingwiththecaseofloadtransportationisalsopresented,andtheresultsshowthattheproposedcontrolleriscapableofguidingtherobottofollowadesiredtrajectorywithaquitesmallerrorevenwhenitsdynamicparameterschange.Themaincontributionsofthepaperare:(I)theuseofadynamicmodelwhoseinputcommandsarevelocities,whichisusualincommercialmobileobots,whilemostoftheworksintheliteraturedealswithtorquecommands;(2)thedesignofanadaptivecontrollerwithas-modificationterm,whichmakesitrobust,withthecorrespondingstabilitystudyforthewholeadaptivecontrolsystem;and(3)thepresentationofexperimentalresultsshowingthegoodperformanceofthecontrollerinatypicalindustrialapplication,namelyloadtransportation.2.DynamicmodelInthissection,thedynamicmodeloftheunicycle-likemobilerobotproposedbyDeLaCruzandCarelli(2006)isreviewed.Fig.1depictsthemobilerobot,itsparametersandvariablesofinterest.uandoarethelinearandangularvelocitiesdevelopedbytherobot,respectively,Gisthecenterofmassoftherobot,Cisthepositionofthecastorwheel,Eisthelocationofatoolonboardtherobot,histhepointofinterestwithcoordinatesxandyintheXYplane,cistherobotorientation,andaisthedistancebetweenthepointofinterestandthecentralpointofthevirtualaxislinkingthetractionwheels(pointB).Thecompletemathematicalmodeliswrittenas.whеrеиgаndоаrеthеdеѕіrеdvаluеѕоfthеlіnеаrаndаngulаrvеlосіtіеѕ,respectively,andrepresenttheinputsignalsofthesystem.Avectorofidentifiedparametersandavectorofparametricuncertaintiesareassociatedwiththeabovemodelofthemobilerobot,whichare,respectively.wheredxanddyarefunctionsoftheslipvelocitiesandtherobotorientation,duanddoarefunctionsofphysicalparametersasmass,inertia,wheelandtirediameters,parametersofthemotorsanditsservos,forcesonthewheels,etc.,andareconsideredasdisturbances.Theequationsdescribingtheparametershwerefirstlypresentedin,andarereproducedhereforconvenience.TheyareItisimportanttopointoutthatanonholonomicmobilerobotmustbeorientedaccordingtothetangentofthetrajectorypathtotrackatrajectorywithsmallerror.Otherwise,thecontrolerrorswouldincrease.Thisistruebecausethenonholonomicplatformrestrictsthedirectionofthelinearvelocitydevelopedbytherobot.So,iftherobotorientationisnottangenttothetrajectory,thedistancetothedesiredpositionateachinstantwillincrease.Thefactthatthecontrolerrorsconvergetoaboundedvalueshowsthatrobotorientationdoesnotneedtobeexplicitlycontrolled,andwillbetangenttothetrajectorypathwhilethecontrolerrorsremainsmall.3.ExperimentalresultsToshowtheperformanceoftheproposedcontrollerseveralexperimentsandsimulationswereexecuted.Someoftheresultsarepresentedinthissection.The.proposedcontrollerwasimplementedonaPioneer3-DXmobilerobot,whichadmitslinearandangularvelocitiesasinputreferencesignals,andforwhichthedistancebinFig.2isnonzero.Inthefirstexperiment,thecontrollerwasinitializedwiththedynamicparametersofaPioneer2-DXmobilerobot,weighingabout10kg(whichwereobtainedviaidentification).BothrobotsareshowninFig.3,wherethePioneer3-DXhasalasersensorweighingabout6kgmountedonitsplatform,whichmakesitsdynamicssignificantlydifferentfromthatofthePioneer2-DX.Intheexperiment,therobotstartsatx=0.2mandy=0.0m,andshouldfollowaeirculartrajectoryofreference.Thecenterofthereferencecircleisatx=0.0mandy=0.8m.Thereferencetrajectorystartsatx=0.8mandy=0.8mandfollowsacirclehavingaradiusof0.8m.After50s,thereferencetrajectorysuddenlychangestoacircleofradius0.7m.Afterthat,theradiusofthereferencetrajectoryalternatesbetween0.7and0.8meach60s.presentsthereferenceandtheactualrobottrajectoriesforapartoftheexperimentthatincludesachangeinthetrajectoryradius,Inthiscase,theparameterupdatingwasactive.showsthedistanceerrorsforexperimentsusingtheproposedcontroller,withandwithoutparameterupdating,tofollowthedescribedreferencetrajectory.Thedistanceerrorisdefinedastheinstantaneousdistancebetweenthereferenceandtherobotposition.Noticethehighinitialerror,whichisduetothefactthatthereferencetrajectorystartsatapointthatisfarfromtheinitialrobotposition.First,theproposedcontrollerwastestedwithnoparameterupdating.ItcanbeseeninFig.5that,inthis.case,thetrajectorytrackingerrorexhibitsasteady-statevalueofabout0.17m,whichdoesnotvaryevenafterthechangeintheradiusofthereferencetrajectory.Thisfigurealsopresentsthedistanceerrorforthecaseinwhichthedynamicparametersareupdated.Byactivatingtheparameter-updating,andrepeatingthesameexperiment,thetrajectorytrackingerrorachievesamuchsmallervalue,incomparisonwiththecaseinwhichisnoig.3.therobptsuesdintheexperiments.ConcusionAnadaptivetrajectory-trackingcontrollerforaunicycle-likemobilerobotwasdesignedandfullytestedinthiswork.Suchacontrollerisdividedintwoparts,whicharebasedonthekinematicanddynamicmodelsoftherobot.Themodelonsideredtakesthelinearandangularvelocitiesasinputreferencesignals,whichisusualwhenregardingcommercialmobilerobots.Itwasconsideredaparameter-updatinglawforthedynamicpartofthecontroller,improvingthesystemperformance.As-modificationtermwasincludedintheparameterupdatinglawtopreventpossibleparameterdrift.StabilityanalysisbasedonLyapunovtheorywasperformedforbothkinematicanddynamiccontroller.Forthelastone,stabilitywasprovedconsideringaparameter-updatinglawwithandwithoutthes-modificationterm.Experimentalresultswerepresented,andshowedthegoodperformanceoftheproposedcontrollerfortrajectorytrackingwhenappliedtoanexperimentalmobilerobot.Along-termsimulationresultwasalsopresentedtodemonstratethattheupdatedparametersconvergeevenifthesystemworksforalongperiodoftime.Theresultsprovedthattheproposedcontrolleriscapableoftrackingadesiredtrajectorywithasmalldistanceerrorwhenthedynamicparametersareadapted.Theimportanceofon-lineparameterupdatingwasillustratedforthecaseswheretherobotparametersare.notexactlyknownormightchangefromtasktotask.ApossibleapplicationfortheproposedcontrolleristoindustrialAGVsusedforloadtransportation,becauseon-lineparameteradaptationwouldmaintainsmalltrackingerroreveninthecaseofimportantchangesintherobotload.一种用于自主移动机器人目标跟踪的自适应动态控制器摘要本文提出了一种自适应控制器来指导单轮移动机器人进行轨迹跟踪。在初始阶段，只考虑机器人的运动学模型，即可得到所需的线速度和角速度。然后，对这些值进行处理以补偿机器人的动力学，从而生成传递给机器人执行器的线速度和角速度命令。表征机器人动力学的参数是在线更新的，因此在这些参数可以变化的应用中，如负载运输，提供了更小的误差和更好的性能。利用李亚普诺夫理论分析了整个系统的稳定性，证明了控制误差是有界的。仿真和实验结果表明，该控制器在不同负载条件下具有良好的跟踪性能。1.介绍在不同的移动机器人结构中，由于单环类平台具有良好的机动性和简单的配置，因此常被用于完成不同的任务。针对这类机器人的非线性控制研究已有多年，该机器人结构已应用于监视、地板清洗等诸多领域。其他应用，如使用自动导向车辆(AGVs)的工业负荷运输，自动公路维护和建设，以及自动轮椅，也使用了独轮车式的结构。一些作者已经解决了轨迹跟踪的问题，这是一个非常重要的功能，允许移动机器人在完成任务时描述所需的轨迹。agv非线性控制的一个重要问题是，目前设计的控制器大多只基于移动机器人的运动学。然而，当需要高速运动和/或重载运输时，除了考虑机器人的运动学外，还必须考虑机器人的动力学。因此，提出了一些补偿机器人动力学的控制器。Fierro和Lewis(1995)以非完整移动机器人为例，提出了一种考虑建模车辆动力学的运动学/转矩联合控制律，其控制指令为力矩，对于大多数商用机器人来说，力矩是难以处理的。此外,只报道。仿真结果Fierro和刘易斯(1997)也提出了一个基于神经网络的鲁棒自适应控制器来处理干扰和non-modeled动态,虽然不是报告实验结果。Das和冰斗(2006)显示一个自适应模糊控制器基于逻辑的模糊逻辑系统估计的不确定性和参数调优在线。动态模型包括执行器动力学，控制器生成的命令为机器人电机的电压。神经网络用于辨识和控制，控制信号为线速度和角速度，但其实时实现要求基于多处理器系统的高性能计算机体系结构。另一方面，DeLaCruz和Carelli(2006)提出了一个以线性和速度为输入的动态模型，并展示了基于该模型的轨迹跟踪控制器的设计。其控制器的一个优点是其参数与机器人参数直接相关。但是，如果参数识别不正确，或者随着时间的推移而变化，例如由于负载的变化，会严重影响控制器的性能。为了减少性能下降，在线参数自适应在机器人动态参数变化的应用中变得非常重要，例如负载运输。当动态参数的知识有限或根本不存在时，它也很有用。本文提出了一种基于机器人动力学的自适应轨迹跟踪控制器，并用李亚普诺夫理论证明了其稳定性。控制器的设计分为两部分，每一部分都是控制器本身。第一个是基于机器人运动学的运动控制器，第二个是基于机器人动力学的动态控制器。动态控制器能够更新与机器人物理参数直接相关的估计参数。这两个控制器共同工作，形成了一个完整的移动机器人轨迹跟踪控制器。基于DeLaCruz和Carelli提出的单环类移动机器人模型设计了控制器，并将s修正项应用于参数更新律中，以防止可能出现的参数漂移。证明了运动控制器和动态控制器的渐近稳定性。仿真结果表明，即使系统工作时间较长，也不会产生参数漂移。实验结果表明，该控制器具有较强的参数更新能力，能够有效地降低跟踪误差。实验结果表明，该控制器能够在动态参数变化的情况下，以较小的误差引导机器人沿预定轨迹运动。本文的主要贡献是:(I)使用了一个动态模型，该模型的put命令中包含速度，这在商用移动机器人中很常见，而文献中的大部分工作都是关于扭矩命令的;(2)设计了具有修改项的自适应控制器，使其具有鲁棒性，并对整个自适应控制系统进行了相应的稳定性研究;(3)实验结果表明，该控制器在典型的工业应用，即负荷输送中具有良好的性能。2.动态模型本节对DeLaCruz和Carelli(2006)提出的单环类移动机器人的动力学模型进行了综述。图1描述了移动机器人及其感兴趣的参数和变量。u和o线速度和角速度都是由机器人,分别G是机器人的质心,C是castor轮的位置,E是一个工具的位置上机器人,h是感兴趣的点与XY平面的x和y坐标,C是机器人取向和兴趣点之间的距离和中心点的虚拟轴连接牵引轮(B点),写成完整的数学模型。分别代表系统的输入信号。上述移动机器人模型分别与确定的参数向量和参数不确定性向量相关联，分别为其中dx和dy是滑移速度和机器人方向的函数，是质量、惯量、车轮和轮胎直径、电机及其伺服参数、车轮上的力等物理参数的函数，被认为是扰动。文中首先给出了参数h的描述方程，为了方便起见，在此重新给出。他们是需要指出的是，非完整移动机器人必须根据轨迹轨迹的切线进行定向，才能跟踪误差较小的轨迹。否则，控制误差将会增加。这是真的，因为非完整平台限制了机器人所发展的线速度方向。所以，如果机器人的方向与轨迹不相切，那么每一瞬间到目标位置的距离就会增加。控制误差收敛到有界值的事实表明，机器人的姿态不需要显式控制，在控制误差较小的情况下与轨迹轨迹相切。3.实验结果为了验证该控制器的性能，进行了实验和仿真。本节将介绍一些结果。该控制器是在一个先进的3-DX移动机器人上实现的，该机器人以线速度和角速度作为输入参考信号，距离b在图中。2是零。在第一个实验中，控制器初始化为一个先锋2-DX移动机器人的动态参数，重约10公斤(通过辨识得到)。两个机器人如图3所示，其中先锋3-DX的平台上安装了一个重约6公斤的激光传感器，这使得它的动力学特性与先锋2-dx明显不同。在实验中，机器人从x=0.2m开始，y=0.0m开始，应遵循参考的圆周轨迹。参考圆的中心在x=0.0m和y=0.8m处。参考轨迹从x=0.8m,y=0.8m开始，沿半径为0.8m的圆运动。50秒后，参考轨迹突然变为半径为0.7m的圆。之后，参考轨迹半径每60秒在0.7~0.8m之间变化。给出了部分实验机器人轨迹的参考和实际轨迹，其中包括轨迹半径的变化，在这种情况下，参数更新是主动的。给出了该控制器在不进行参数更新的情况下，跟踪所述参考轨迹的距离误差。距离误差定义为参考点到机器人位置的瞬时距离。注意初始误差很大，这是由于参考轨迹从远离初始机器人位置的点开始。首先，在不更新参数的情况下对该控制器进行了测试。从图5中可以看出，在这种情况下，轨迹跟踪误差的稳态值约为0.17m，即使在参考轨迹半径改变后也没有变化。该图还显示了动态参数更新时的距离误差。通过激活参数更新，并重复相同的实验，与ig.3不存在的情况相比，轨迹跟踪误差的值要小得多。这些机器人在实验中使用。4.结论设计了一种适用于单环类移动机器人的自适应轨迹跟踪控制器，并对其进行了全面测试。基于机器人的运动学和动力学模型，将该控制器分为两部分。侧边红色的模型以线速度和角速度作为输入参考信号，这在商用移动机器人中很常见。该方法被认为是控制器动态部分的参数更新律，提高了系统性能。为了防止参数漂移，在参数更新律中加入了s修正项。对运动控制器和动态控制器进行了基于李雅普诺夫理论的稳定性分析。最后，证明了考虑参数更新律的稳定性，其中包含和不包含s修正项。给出了实验结果，并将该控制器应用于实验移动机器人的轨迹跟踪中，取得了较好的效果。仿真结果表明，即使系统工作时间较长，更新后的参数也会收敛。实验结果表明，该控制器在动态参数调整的情况下，能够以较小的距离误差跟踪目标轨迹。阐述了机器人参数在线更新的重要性。不完全知道或可能在不同的任务之间更改。该控制器的一个可能的应用是用于工业agv的负荷运输，因为即使在机器人负荷发生重要变化的情况下，在线参数自适应也能保持较小的跟踪误差。Raspberry

Pi

32016

Raspberry

Pi

3

User

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Effective

use

of

Terminal

commands

Оnе

оf

thе

kеу

аѕресtѕ

оf

uѕіng

а

tеrmіnаl

іѕ

bеіng

аblе

tо

nаvіgаtе

уоur

fіlеsystem.

Firstly,

run

the

following

command:

ls

-la.

You

should

see

something

similar

to:

The

Is

command

lists

the

contents

of

the

directory

that

you

are

currently

in

or

yourpresent

working

directory.

The

-la

component

of

the

command

is

what's

known

as

a

flag'.Flags

modify

the

command

that's

being

run.

In

order

to

navigate

to

other

directories

thechange

directory

command,

cd

can

be

used.

You

can

specify

the

directory

that

you

want

to

by

either

the

'absolute

or

the

'relative

path.

So

if

you

wanted

to

navigate

to

the

/pidirectory,

you

could

either

do

cd

/home/pi/

or

just

pi

if

you

are

currently

in

/home.

There

aresome

special

cases

that

may

be

useful:

~

acts

as

an

alias

for

your

home

directory,

so~/Desktop

is

the

same

as

/home/pi/Desktop;

.

and

..

are

aliases

for

the

current

directory

and

theparent

directory

respectively,

e.g.

if

you

were

in

/home/pi.Auto-detectcommandRatherthantypeeverycommand,theterminalallowsyoutoscrollthroughpreviouscommandsthatyourunbypressingtheupordownkeysonyourkeyboard.Ifyouarewritingthenameofafileordirectoryaspartofacommandthenthepressingtab:willattempttoAutocompletethenameofwhatyouaretyping.Forexample,ifyouhaveafileinadirectorycalledTestFileNamethenpressingtabaftertyping'T'willallowyoutochoosefromallfileanddirectorynamesbeginningwithaninthecurrentdirectory,allowingyoutochooseTestFileName.SudoprivilegeSomecommandthatmakepermanentchangestothestateofyoursystemrequireyoutohaverootprivilegestorun.Thecommandtemporarilygivesyouraccount(ifyourenotalreadyloggedinasroot)theabilitytorunthesecommands,providedyourusernameisinalistofusers.Whenyouappendsudotothestartofacommandandpressenteryouwillbeaskedforyourpassword,ifthatisenteredcorrectlythenthecommandyouwanttorunwillberunusingrootprivileges.Becareful,thoughsomecommandsthatrequiresudotoruncanirreparablydamageyoursystemsobecareful!InstallSoftwareorotherutilitiesusingapt-getRatherthanusingthePiStoretodownloadnewsoftwareyoucanusethecommandapt-get,thisisthe'packagemanagerthatisincludedwithanyDebianbasedLinuxdistributions(includingRaspbian).ItallowsyoutoinstallandmanagenewsoftwarepackagesonyourPi.Inordertoinstallanewpackageyouwouldtypesudoapt-getinstal<package-name>(where<packagename>isthepackagethatyouwanttoinstall).Runningsudoapt-getupdateupdatesalistofsoftwarepackagesthatareavailableonyoursystem.Ifanewversionofapackageisavailablethensudoapt-getupgradewillupdateanyoldpackagestothenewversion.Finally,sudoapt-getremove<package-name>removesoruninstallsapackagefromyoursystem.FindingthemanualofcommandTofindoutmoreinformationaboutaparticularcommandthenyoucanrunthemanfollowedbythecommandyouwanttoknowmoreabout(e.g.man1s).Theman(ormanualpage)forthatcommandwillbedisplayed,includinginformationabouttheflagsforthatprogramandwhateffecttheyhave.Somemanswillgiveexampleusage.RaspberryPi:GPIOGPIOisoneofthepowerfultoolsofRaspberryPi.YoucaninterfacevarioushardwarewiththeseRaspberryPi.youcanthinkofthemasswitchesthatyoucanturnonorofforthatthePicanturnonoroff.26pinsareGPIOpins,theothersarepowerorgroundpins.Youcanprogramthepinstointeractinamazingwayswiththerealworld.Inputsdon'thavetocomefromaphysicalswitch;itcouldbeinputfromasensororasignalfromanothercomputerordevice,forexample.Theoutputcanalsodoanything,fromturningonaLEDtosendingasignalordatatoanotherdevice.IftheRaspberryPiisonanetwork,youcancontroldevicesthatareattachedtoitfromanywhereandthosedevicescansenddataback.Connectivityandcontrolofphysicaldevicesovertheinternetisapowerfulandexcitingthing,andtheRaspberryPiisidealforthis.WorkingofGPIOIfyouareawareofthefunctionalityofGPIOandhowitisworkingthenmessingaboutwiththeGPIOissafeandfun.GPIOpinscanbeconfiguredaseithergeneral-purposeinput,general-purposeoutputorasoneofupto6specialalternatesettings,thefunctionsofwhicharepin-dependant..Thereare3GPIObanksonRaspberryPi3.Eachofthe3bankshasitsownVDDinputpin.OnRaspberryPi3,allGPIObanksaresuppliedfrom3.3V.TheconnectionofaGPIOtoavoltagehigherthan3.3VwilllikelydestroyordamagetheGPIOblockwithinboardorSoC.GPIOPowerStatesAllGPIOsaresettoinputpinonthepower-onreset.MostoftheGPIOshavethepullupappliedbydefault.InterruptsInterruptsarethemainfeaturesofanyGPIOPinwhichwillenablethepinforfunctioninginamultipleway.Basically,itwillstoptheexecutionofaprogramanddotheotherhighprioritytask.Therearemainly3typesofinterruptsavailablewhichareasfollows:(high/low)Level-sensitive,Risingedgeandfallingedge,AsynchronousrisingedgeandAsynchronousfallingedge.Theinterruptwillworkitstaskuntilthelevelisclearedbythesystemorthetaskofthatinterruptiscompleted.Therisingandfallingedgedetectionwillworkasthedetectionortransitionfromhightoloworlowtohighvoltage.Afterthistransition,theinterruptwilloccurandthecompilerwilljumpintothatparticularinterruptserviceroutine.WhatisInterruptServiceRoutine(ISR)?Itistheroutineorprogramthatwillbeexecutedwhentheinterruptwilloccur.EachinterruptmusthaveitsISRtomakeitstaskcomplete.OtherFunctionsofGPIOAlltheGPIOhasthealternatefunctionaswell.Raspberrypi'sGPIOhasalsosuchfunctionavailable.PinscanactasGeneralPurposeInput/Output,I2CprotocolwhichisusedfortheserialcommunicationwithexternalperipheralslikeEEPROM,otherdevicesetc.SPI(SerialPeripheralInterface)isanotherserialcommunicationprotocolwhichisavailableinRaspberryPI.RandomlypluggingwiresandpowersourcesintoyourPi,however,maydamagetheRaspberryPi.DamagecanalsohappenifyoutrytoconnectthingstoyourPithatusealotofpower.YoucanconnectLEDorsimpleswitcheswithRaspberryPi,ButMotorshavinghighcurrentandotherhighvoltagedevicesmayharmyourboard.Differencefromanotherraspberries1.Cost.AllthreemodelsofRaspberryPicostaround$35.ModelB+waslaunchedinJuly2014wherePi2and3waslaunchedinFebruary2015and2016(ayearapart).AlthoughthePiischeapertherearesomehiddencostswithinvolvedwhenyoubuyone.YouneedaMicroSDCardforloadingtheRaspbianImage,Keyboard,Mouse(Canbewiredorwireless)forcontrollingthepi,HDMIcablefordisplayandawifidongleorEthernetCableforinternetconnectivity.ForRaspberryPi3,thereinanonboardwifimoduleandBluetoothmodule.ThisisanadvantageofbuyingthePi3comparedtopreviousversionsofRaspberryPi.2.PerformanceWhileoperatingat700MHzbydefault,thefirstgenerationRaspberryPiprovidedareal-worldperformanceroughlyequivalentto0.041GFLOPS.OntheCPUleveltheperformanceissimilartoa300MHzPentiumIIof1997--99.TheGPUprovides1Gpixel/sor1.5Gtexel/sofgraphicsprocessingor24GFLOPSofgeneralpurposecomputingperformance.ThegraphicsabilitiesoftheRaspberryPiareroughlyequivalenttotheperformanceoftheXboxof2001.TheLINPACKsinglenodecomputebenchmarkresultsinameansingleprecisionperformanceof0.065GFLOPSandameandoubleprecisionperformanceof0.041GFLOPSforoneRaspberryPiModel-Bboard.Aclusterof64RaspberryPiModel-Bcomputers,labeledIridis-pi",achievedaLINPACKHPLsuiteresultof1.14GFLOPS(n=10240)at216wattsforc.4000US$.RaspberryPi2includesaquad-coreCortex-A7CPUrunningat900MHzand1GBRAM.Itisdescribedas4-6timesmorepowerfulthanitspredecessor.TheGPUisidenticaltotheoriginal.Inparallelizedbenchmarks,theRaspberryPi2couldbeupto14timesfasterthanaRaspberryPi1B+.TheRaspberryPi3,withaQuadcoreCortex-A53processor,isdescribedas10timestheperformanceofaRaspberryPi1.Thiswassuggestedtobehighlydependentupontaskthreadingandinstructionsetuse.BenchmarksshowedtheRaspberryPi3tobeapproximately80%fasterthantheRaspberryPi2inparallelizedtasks.3.CPUModelB+havea700MHzsingle-coreARM1176JZF-Sprocessor.Inthelatermodel,RaspberryPi2havea900MHzquad-coreARMCortex-A7processor.ComparedtotheModelB+,Pi2havemorespeedandmuchmoresuitableformultitaskingbecauseofitsquad-coreprocessor.Intherecentversion,RaspberryPi3,theCPUisa1.2Ghz64-bitquad-coreARMCortex-A53processor.Pi3hasmoreprocessingpowercomparedtoPi2andModelB+andalsoitiscapabletorun64-bitsystems.However,thecurrentversionoftheoperatingsystemsarestill32bit.Inthecomingdaystheremightbeavailabilityof64bitoperatingsystemsforRaspberryPi3.ComparedtotheRaspberryPi2,RaspberryPi3delivers50-60percenthigherperformance.4.RAMOntheolderbetamodelBboards,128MBwasallocatedbydefaulttotheGPU,leaving128MBfortheCPU.Onthefirst256MBreleasemodelB(andmodelA),