Optimisation des trajectoires d'un robot Delta

W e s t e f n S w i t z e r l à n d

D o r n a i n e S c i e n c e s d e l i n g é n i e u r Rte du Rawyl 47

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Filière Systèmes industriels

Orientation Power & Control

Diplôrne 2010

Michaël B,riguet

)ptimisation des trajectoires d'un robot Delta

Professeur Expert

Jean-Daniel Marcuard Christian Vouillamoz

Sion, le 12 juillet2010

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Le pé tra co re lo pl po tra 3D U co ce dé co

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HES-SO Valais Route du Rawyl 47 1950 Sion

Travail de diplôme

| é d i t i o n 2 0 1 0 |

Filière

Systèmes industriels

Domaine d’application Power & Control

Professeur responsable Marcuard Jean-Daniel jdaniel.marcuard@hevs.ch

Partenaire

Bosch Packaging Technology SA

1

B N R

Objectif du projet

Ce projet a pour but d’analyser et de développer une métho d’optimiser les consignes d’accélération et de vitesse en fon du robot tout en limitant les échauffements moteurs.

Méthodes | Ex périences | Rés ultats

Le travail s’est déroulé en plusieurs étapes. Dans un premi période a été nécessaire à l’apprentissage du robot et de travail. Une analyse théorique a ensuite été effectuée a comportements à étudier. A l’aide d’un programme d’acqu relatives aux mouvements du robot ont été récupérées logiciel Matlab. Le choix du paramètre à améliorer s’est por plan de transition du robot. Pour se faire, le script du logicie pour effectuer différentes analyses et définir les accélérati trajectoires. Finalement, ces valeurs ont permis de réalise 3D du plan de transition.

Un travail conséquent doit encore être fourni pour ob concrète du robot. Néanmoins, une progression significati cette direction. De plus, le rapport contient des ana développements théoriques offrant des perspectives concrétisation de l’objectif premier du projet.

Optimisation des trajectoires d’un Ro

Diplômant Michaël Briguet

Bleu : Vue de face du volume de travail

Noir : Convoyeurs

Rouge : Trajectoires du robot

Cartograp critiques avec des

ode permettant onction de la trajectoire

ier temps, une certaine son environnement de afin de déterminer les uisition, les informations s puis traitées avec le orté sur l’accélération du iel Matlab a été optimisé tions critiques selon les ser une cartographie en

btenir une optimisation tive a été réalisée dans nalyses ainsi que des intéressantes vers la

Robot Delta

phie 3D des accélérations sur le plan de transition s trajectoires radiales et

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{Boucle de cycle}A 41!A!963C2@_AA1A363C2!C7A1A BE#IN

{Mouvement lent pour le point de départ}

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{Assignation des paramètres d'accélération et de vitesse}

NewAccel:=AccelMin+AccelStep*(RunStepReal);

D3n_Accel(left,newAccel);

D3n_Speed(left,4000);

{Calcul de temps du premier mouvement}

IF RunStep = 0 THEN BEGIN

D3n_PrepareAbsMove(left,End_X,End_Y,End_Z,nil,d3mp);

PrepareTargetTime := D3n_Q_PrepareTargetTime(left);

END;

{Pause de stabilisation}

TimeWait(0.2);

{Lancement de la procédure d'enregistrement}

StartMoving:=true;

{Mouvement}

TestingMovement(point2,locName2);

{Pause de stabilisation}

TimeWait(0.4);

Arret de la procédure d'enregistrement}

StartMoving:=false;

{Incrementation du mouvement}

RunStepReal := RunStepReal+1;

END

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A

if ( (t == 1) || (((abs(Diff1(t-3)))+(abs(Diff1(t-2)))+ (abs(Diff1(t-1)))<=5) &&

Diff1(t)~=0 && ((abs(Diff1(t+1)) + abs(Diff1(t+2)) + abs(Diff1(t+3)) + abs(Diff1(t+4)) + abs(Diff1(t+5)) + abs(Diff1(t+6))+ abs(Diff1(t+7)))>150) )),

… end :

Boucle d'échantillonnage for Step=0 : NbStep-1, next=0;

%Boucle de début de mouvement while next==0;

...

end;

end;

%Début de l'échantillonnage startendstep(1,(Step+1)) = t;

%Fin de l'échantillonnage

startendstep(2,(Step+1)) = t+350;

%si l’index dépasse le max du tableau if startendstep(2,(Step+1)) >l, endstep = l ;

end;

Définition de la variance Variance1 =

var(Diff1(startendstep(1,(Step+1)):startends tep(2,(Step+1))));

%Recherche de mouvement suivant next=1;

%Assignation dans un tableau de la variance correspondante

TabVar1(Step+1)=Variance1;

%Assignation dans un tableau de

l'accélération liée à la variance TabAccel1(Step+1)=(AccelMin+AccelStep*Step);

%Recherche du mouvement suivant t=t+350;

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%Plot de la courbe d'échantillonnage plot(TabAccel1,TabVar1,'-g');

%Dérivée première et seconde deriv11 = gradient(TabVar1);

deriv12 = gradient(deriv11);

%maximum de la deuxième dérivée [yd1,vd1]=max(deriv12);

%Assignation des valeurs correspondantes AccelCritAxe1=TabAccel1(vd1-1);

VarCritAxe1=TabVar1(vd1-1);

%lignes des valeurs critiques

plot([AccelCritAxe1 AccelCritAxe1],[0 VarCritAxe1],'-.g')

plot([AccelMin AccelCritAxe1],[VarCritAxe1 VarCritAxe1],'-.g')

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