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#!/usr/bin/env pybricks-micropython
from pybricks.hubs import EV3Brick
from pybricks.ev3devices import (Motor, TouchSensor, ColorSensor,
InfraredSensor, UltrasonicSensor, GyroSensor)
from pybricks.parameters import Port, Stop, Direction, Button, Color
from pybricks.tools import wait, StopWatch, DataLog
from pybricks.robotics import DriveBase
from pybricks.media.ev3dev import SoundFile, ImageFile
import threading
# This program requires LEGO EV3 MicroPython v2.0 or higher.
# Click "Open user guide" on the EV3 extension tab for more information.
# Initialisation de la brique EV3
ev3 = EV3Brick()
# Initialisation des moteurs
left_motor = Motor(Port.D)
right_motor = Motor(Port.A)
# Initialisation des capteurs
gyro_sensor = GyroSensor(Port.S2)
ultrasonic_sensor=UltrasonicSensor(Port.S3)
color_sensor=ColorSensor(Port.S4)
#Fonction
def calibration():
GYRO_CALIBRATION_LOOP_COUNT = 200
global GYRO_OFFSET_FACTOR
gyro_minimum_rate, gyro_maximum_rate = 440, -440
gyro_sum = 0
for _ in range(GYRO_CALIBRATION_LOOP_COUNT):
gyro_sensor_value = gyro_sensor.speed()
gyro_sum += gyro_sensor_value
if gyro_sensor_value > gyro_maximum_rate:
gyro_maximum_rate = gyro_sensor_value
if gyro_sensor_value < gyro_minimum_rate:
gyro_minimum_rate = gyro_sensor_value
wait(5)
gyro_offset = gyro_sum / GYRO_CALIBRATION_LOOP_COUNT
return gyro_offset
def regulation(vitesse_ref,direction):
global psi, K, GYRO_OFFSET_FACTOR, temps_moyen_boucle, gyro_sensor, left_motor, right_motor, gyro_offset
global Kp1, Kp2, Kp3, Kp4, theta_ref, theta_ancien
# Mesure des variables d'états
# Calcul de psi et psi_d
gyro_sensor_value = gyro_sensor.speed()
gyro_offset *= (1 - GYRO_OFFSET_FACTOR)
gyro_offset += GYRO_OFFSET_FACTOR * gyro_sensor_value
psi_d = gyro_sensor_value - gyro_offset
psi=psi/K
psi += psi_d * temps_moyen_boucle
#Calcul de l'angle theta et de la vitesse angulaire des roues
left_motor_angle = left_motor.angle()
right_motor_angle = right_motor.angle()
theta_1=right_motor_angle
theta_2=left_motor_angle
theta = (left_motor_angle+right_motor_angle)/2
#left_motor_rate = left_motor.speed()
#right_motor_rate = right_motor.speed()
#theta_d = (left_motor_rate+right_motor_rate)/2
theta_d = (theta - theta_ancien)/temps_moyen_boucle
theta_ancien=theta
#ev3.screen.print("theta =", theta)
#ev3.screen.print("theta_d =", theta_d)
#ev3.screen.print("psi =",psi)
#ev3.screen.print("psi_d=",psi_d)
# Conversion en radian
theta = K*theta
theta_d = K*theta_d
psi = K*psi
psi_d = K*psi_d
# Erreur
theta_ref= theta_ref + vitesse_ref*temps_moyen_boucle
erreur_theta= theta - theta_ref
erreur_vitesse_theta= theta_d - vitesse_ref
# Retour d'état
retour = Kp1*theta + Kp2*psi + Kp3*theta_d + Kp4*psi_d
retour = Kp1*erreur_theta + Kp2*psi + Kp3*erreur_vitesse_theta + Kp4*psi_d
commande_moteur= -retour
#if commande_moteur > 100:
#commande_moteur = 100
#if commande_moteur < -100:
#commande_moteur = -100
left_motor.dc(commande_moteur/2+direction)
right_motor.dc(commande_moteur/2-direction)
return
def regulation_deviation(theta_diff):
global init, diff_actuel
theta_2 = left_motor.angle()
theta_1= right_motor.angle()
if init==0:
vitesse_ref=2
diff_actuel=theta_2 - theta_1
init=1
direction=0.02*(theta_diff - (theta_2 - theta_1 - diff_actuel))
return direction
#Thread et fonction pour retourner la couleur détéctée
#Initialisation de la couleur et du niveau de gris
coul=0
gris=0
def couleur():
global coul
global gris
while True:
c=color_sensor.rgb()
coul=couleur_rgb(c)
gris=(c[0]+c[1]+c[2])/3
print(coul)
print(c)
wait(200)
def couleur_rgb(c):
if c[0]<10 and c[1]<10 and c[2]<10:
return "noire"
elif c[0]<10 and c[1]<=10 and c[2]>=10:
if c[0]==7:
return 'blanc'
else:
return "bleu"
elif c[0]>10 and c[1]<10 and c[2]<10:
return "rouge"
elif c[0]<15 and c[1]>=27 and c[2]<15:
return "vert"
else:
return "blanc"
threading.Thread(target=couleur).start()
# Kp retour d'état
Kp1=-20
Kp2=-1700.2
Kp3=-20
Kp4=-130.5693
#Initialisation d'un timer et d'un compteur pour déterminer le temps d'une boucle
timer = StopWatch()
nb_iter=0
#Compteur utilisé pour la résolution du labyrinthe
timer_global = StopWatch()
#Période d'échantillonage
Ts=0.030
#Reinitialisation des codeurs des moteurs
left_motor.reset_angle(0)
right_motor.reset_angle(0)
#Gain pour la conversion en radian
pi=3.1415
K = pi/180
#Initialisation des variables pour la dérivation et l'intégration
psi=0
theta_ref=0
theta_ancien=0
# Variables de référence
vitesse_ref=2 #rad/s, on commence par le suivi ligne
direction=0
#Calibration du gyroscope
GYRO_OFFSET_FACTOR = 0.0005
gyro_offset=calibration()
#Emission d'un bruit lorsque la calibration est fini
ev3.speaker.beep()
#ETAT DU ROBOT
suivi_ligne=1
intersection=0
init=0
obstacle=0
#Pour les intersections
etape=0
compteur_bleu=0
#POUR LE SUIVI LIGNE
BLACK = 4
WHITE = 40
seuil = (BLACK + WHITE) / 2
#Boucle de regulation
timer_global.reset()
while True:
#Calcul du temps moyen d'une boucle
if nb_iter == 0:
temps_moyen_boucle = Ts
timer.reset()
else:
temps_moyen_boucle = (timer.time() / 1000 /nb_iter)
nb_iter += 1
#Suivi ligne
if suivi_ligne==1:
vitesse_ref=1.5
#direction=regulation_deviation(0)
gain=0.1
if coul=='noire':
gain=0.2
direction=gain*(gris-seuil)
"""if coul=='blanc':
vitesse_ref=0
init=0"""
if coul=="bleu":
compteur_bleu=compteur_bleu+1
else:
compteur_bleu=0
if compteur_bleu==10:
etape+=1
suivi_ligne=0
intersection=1
ev3.speaker.beep()
init=0
direction=0
theta_actuel=left_motor.angle()
tourner=0
timer_global.reset()
devia=direction
if coul=="vert":
suivi_ligne=0
obstacle=1
ev3.speaker.beep()
vitesse_ref=0
init=0
timer_global.reset()
#Intersection
if intersection==1:
if etape==3 or etape==5:
direction=-devia
else:
direction=11
if (coul=="noire" or coul=="blanc") and timer_global.time()>1000:
suivi_ligne=1
intersection=0
#ev3.speaker.beep()
init=0
timer_global.reset()
#Demi_tour
if obstacle==1:
if timer_global.time()>1500:
direction=regulation_deviation(4*240)
if direction<3 and direction>-3:
obstacle=0
vitesse_ref=2
direction=0
suivi_ligne=1
init=0
regulation(vitesse_ref,direction)
wait(Ts*1000)
#!/usr/bin/env pybricks-micropython
from pybricks.hubs import EV3Brick
from pybricks.ev3devices import (Motor, TouchSensor, ColorSensor,
InfraredSensor, UltrasonicSensor, GyroSensor)
from pybricks.parameters import Port, Stop, Direction, Button, Color
from pybricks.tools import wait, StopWatch, DataLog
from pybricks.robotics import DriveBase
from pybricks.media.ev3dev import SoundFile, ImageFile
import threading
# This program requires LEGO EV3 MicroPython v2.0 or higher.
# Click "Open user guide" on the EV3 extension tab for more information.
# Initialisation de la brique EV3
ev3 = EV3Brick()
# Initialisation des moteurs
left_motor = Motor(Port.D)
right_motor = Motor(Port.A)
# Initialisation des capteurs
gyro_sensor = GyroSensor(Port.S2)
color_sensor = ColorSensor(Port.S4)
#Fonction
def calibration():
GYRO_CALIBRATION_LOOP_COUNT = 200
global GYRO_OFFSET_FACTOR
gyro_minimum_rate, gyro_maximum_rate = 440, -440
gyro_sum = 0
for _ in range(GYRO_CALIBRATION_LOOP_COUNT):
gyro_sensor_value = gyro_sensor.speed()
gyro_sum += gyro_sensor_value
if gyro_sensor_value > gyro_maximum_rate:
gyro_maximum_rate = gyro_sensor_value
if gyro_sensor_value < gyro_minimum_rate:
gyro_minimum_rate = gyro_sensor_value
wait(5)
gyro_offset = gyro_sum / GYRO_CALIBRATION_LOOP_COUNT
return gyro_offset
def regulation(vitesse_ref,deviation):
global psi, K, GYRO_OFFSET_FACTOR, temps_moyen_boucle, gyro_sensor, left_motor, right_motor, gyro_offset
global Kp1, Kp2, Kp3, Kp4, theta_ref, theta_ancien
# Mesure des variables d'états
# Calcul de psi et psi_d
gyro_sensor_value = gyro_sensor.speed()
gyro_offset *= (1 - GYRO_OFFSET_FACTOR)
gyro_offset += GYRO_OFFSET_FACTOR * gyro_sensor_value
psi_d = gyro_sensor_value - gyro_offset
psi=psi/K
psi += psi_d * temps_moyen_boucle
#Calcul de l'angle theta et de la vitesse angulaire des roues
left_motor_angle = left_motor.angle()
right_motor_angle = right_motor.angle()
theta = (left_motor_angle+right_motor_angle)/2
#left_motor_rate = left_motor.speed()
#right_motor_rate = right_motor.speed()
#theta_d = (left_motor_rate+right_motor_rate)/2
theta_d = (theta - theta_ancien)/temps_moyen_boucle
theta_ancien=theta
#ev3.screen.print("theta =", theta)
#ev3.screen.print("theta_d =", theta_d)
#ev3.screen.print("psi =",psi)
#ev3.screen.print("psi_d=",psi_d)
# Conversion en radian
theta = K*theta
theta_d = K*theta_d
psi = K*psi
psi_d = K*psi_d
# Erreur
theta_ref= theta_ref + vitesse_ref*temps_moyen_boucle
erreur_theta= theta - theta_ref
erreur_vitesse_theta= theta_d - vitesse_ref
# Retour d'état
retour = Kp1*theta + Kp2*psi + Kp3*theta_d + Kp4*psi_d
retour = Kp1*erreur_theta + Kp2*psi + Kp3*erreur_vitesse_theta + Kp4*psi_d
commande_moteur= -retour
#if commande_moteur > 100:
#commande_moteur = 100
#if commande_moteur < -100:
#commande_moteur = -100
left_motor.dc(commande_moteur/2+deviation)
right_motor.dc(commande_moteur/2-deviation)
return
# Kp retour d'état
Kp1=-20
Kp2=-1700.2
Kp3=-20
Kp4=-130.5693
#Initialisation d'un timer et d'un compteur pour déterminer le temps d'une boucle
timer = StopWatch()
nb_iter=0
#Période d'échantillonage
Ts=0.030
#Reinitialisation des codeurs des moteurs
left_motor.reset_angle(0)
right_motor.reset_angle(0)
#Gain pour la conversion en radian
pi=3.1415
K = pi/180
#Initialisation des variables pour la dérivation et l'intégration
psi=0
theta_ref=0
theta_ancien=0
# Variables de référence
vitesse_ref=0 #rad/s
deviation=0
#Calibration du gyroscope
GYRO_OFFSET_FACTOR = 0.0005
gyro_offset=calibration()
#Emission d'un bruit lorsque la calibration est fini
ev3.speaker.beep()
#Boucle de regulation
while True:
#Calcul du temps moyen d'une boucle
if nb_iter == 0:
temps_moyen_boucle = Ts
timer.reset()
else:
temps_moyen_boucle = (timer.time() / 1000 /nb_iter)
nb_iter += 1
regulation(vitesse_ref,deviation)
wait(Ts*1000)
# PFE Segway Intelligent
Ce projet de fin d'études consiste à développer un programme permettant à un robot lego Segway
de parcourir de manière autonome un labyrinthe muni d’indications colorées.
Ce github comprend un programme permettant au robot de se stabiliser debout et un programme permettant
au robot de naviguer le long du labyrinthe.
## Getting started
Chaque programme, une fois exécuté sur le robot, comprend une phase d'initialisation durant laquelle il faut
tenir le robot debout verticalement. Un bip sonore marque la fin de cette phase.
To make it easy for you to get started with GitLab, here's a list of recommended next steps.
Already a pro? Just edit this README.md and make it your own. Want to make it easy? [Use the template at the bottom](#editing-this-readme)!
## Add your files
- [ ] [Create](https://docs.gitlab.com/ee/user/project/repository/web_editor.html#create-a-file) or [upload](https://docs.gitlab.com/ee/user/project/repository/web_editor.html#upload-a-file) files
- [ ] [Add files using the command line](https://docs.gitlab.com/ee/gitlab-basics/add-file.html#add-a-file-using-the-command-line) or push an existing Git repository with the following command:
```
cd existing_repo
git remote add origin https://gitlab.univ-lorraine.fr/mecirdi1u/pfe-segway-intelligent.git
git branch -M main
git push -uf origin main
```
## Integrate with your tools
- [ ] [Set up project integrations](https://gitlab.univ-lorraine.fr/mecirdi1u/pfe-segway-intelligent/-/settings/integrations)
## Collaborate with your team
- [ ] [Invite team members and collaborators](https://docs.gitlab.com/ee/user/project/members/)
- [ ] [Create a new merge request](https://docs.gitlab.com/ee/user/project/merge_requests/creating_merge_requests.html)
- [ ] [Automatically close issues from merge requests](https://docs.gitlab.com/ee/user/project/issues/managing_issues.html#closing-issues-automatically)
- [ ] [Enable merge request approvals](https://docs.gitlab.com/ee/user/project/merge_requests/approvals/)
- [ ] [Automatically merge when pipeline succeeds](https://docs.gitlab.com/ee/user/project/merge_requests/merge_when_pipeline_succeeds.html)
## Test and Deploy
Use the built-in continuous integration in GitLab.
- [ ] [Get started with GitLab CI/CD](https://docs.gitlab.com/ee/ci/quick_start/index.html)
- [ ] [Analyze your code for known vulnerabilities with Static Application Security Testing(SAST)](https://docs.gitlab.com/ee/user/application_security/sast/)
- [ ] [Deploy to Kubernetes, Amazon EC2, or Amazon ECS using Auto Deploy](https://docs.gitlab.com/ee/topics/autodevops/requirements.html)
- [ ] [Use pull-based deployments for improved Kubernetes management](https://docs.gitlab.com/ee/user/clusters/agent/)
- [ ] [Set up protected environments](https://docs.gitlab.com/ee/ci/environments/protected_environments.html)
***
# Editing this README
When you're ready to make this README your own, just edit this file and use the handy template below (or feel free to structure it however you want - this is just a starting point!). Thank you to [makeareadme.com](https://www.makeareadme.com/) for this template.
## Suggestions for a good README
Every project is different, so consider which of these sections apply to yours. The sections used in the template are suggestions for most open source projects. Also keep in mind that while a README can be too long and detailed, too long is better than too short. If you think your README is too long, consider utilizing another form of documentation rather than cutting out information.
## Name
Choose a self-explaining name for your project.
## Description
Let people know what your project can do specifically. Provide context and add a link to any reference visitors might be unfamiliar with. A list of Features or a Background subsection can also be added here. If there are alternatives to your project, this is a good place to list differentiating factors.
## Badges
On some READMEs, you may see small images that convey metadata, such as whether or not all the tests are passing for the project. You can use Shields to add some to your README. Many services also have instructions for adding a badge.
## Visuals
Depending on what you are making, it can be a good idea to include screenshots or even a video (you'll frequently see GIFs rather than actual videos). Tools like ttygif can help, but check out Asciinema for a more sophisticated method.
## Installation
Within a particular ecosystem, there may be a common way of installing things, such as using Yarn, NuGet, or Homebrew. However, consider the possibility that whoever is reading your README is a novice and would like more guidance. Listing specific steps helps remove ambiguity and gets people to using your project as quickly as possible. If it only runs in a specific context like a particular programming language version or operating system or has dependencies that have to be installed manually, also add a Requirements subsection.
## Usage
Use examples liberally, and show the expected output if you can. It's helpful to have inline the smallest example of usage that you can demonstrate, while providing links to more sophisticated examples if they are too long to reasonably include in the README.
## Support
Tell people where they can go to for help. It can be any combination of an issue tracker, a chat room, an email address, etc.
## Roadmap
If you have ideas for releases in the future, it is a good idea to list them in the README.
## Contributing
State if you are open to contributions and what your requirements are for accepting them.
For people who want to make changes to your project, it's helpful to have some documentation on how to get started. Perhaps there is a script that they should run or some environment variables that they need to set. Make these steps explicit. These instructions could also be useful to your future self.
You can also document commands to lint the code or run tests. These steps help to ensure high code quality and reduce the likelihood that the changes inadvertently break something. Having instructions for running tests is especially helpful if it requires external setup, such as starting a Selenium server for testing in a browser.
## Authors and acknowledgment
Show your appreciation to those who have contributed to the project.
## License
For open source projects, say how it is licensed.
## Project status
If you have run out of energy or time for your project, put a note at the top of the README saying that development has slowed down or stopped completely. Someone may choose to fork your project or volunteer to step in as a maintainer or owner, allowing your project to keep going. You can also make an explicit request for maintainers.
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