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vehicle.py
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vehicle.py
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import pygame as pg
from utils import Aircraft, random_color, limit, constrain, bivariateFunction, derivativeBivariate, normalFunction
from constants import *
from math import cos, sin, atan2, pi
import random
import copy
vec2 = pg.math.Vector2
class Vehicle(object):
def __init__(self, x,y, behavior, window):
"""
idealized vehicle representing a drone
:param x and y: represents inicial target
:param behavior: State Machine
:param window: pygame screen were it will be draw
"""
self.debug = False # debug lines is Off
# Variables used to move drone
self.location = vec2(x,y) # Random position in screen
self.velocity = vec2(0.1,0) # Inicial speed
self.target = vec2(x,y)
self.acceleration = vec2(0,0)
self.radius = SIZE_DRONE # Drone Size
self.desired = vec2()
self.memory_location = [] # To draw track
self.rotation = atan2(self.location.y, self.location.x) # inicital rotation
# Arbitrary values
self.max_speed = FORWARD_SPEED
self.max_force = SEEK_FORCE
self.angular_speed = ANGULAR_SPEED
# Picks a random color for target, is used to differentiate visually during simulation
self.color_target = random_color()
# Variables related to State Machine
self.behavior = behavior
self.window = window # tela em que esta acontecendo a simulaçao
self.theta = 0 # variavel para o eight somada no seek_around
self.count = 0
# Variables to draw drone using Sprites
self.drone = Aircraft()
self.all_sprites = pg.sprite.Group()
self.all_sprites.add(self.drone)
def reached_goal(self, target):
return target and (target - self.location).length() <= RADIUS_TARGET
def update(self):
"""
Standart Euler integration
Updates bahavior tree
"""
# updates behavior in machine state
self.behavior.update(self)
# Updates velocity at every step and limits it to max_speed
self.velocity += self.acceleration * 1
self.velocity = limit(self.velocity, self.max_speed)
# updates position
self.location += self.velocity
# Prevents it from crazy spinning due to very low noise speeds
if self.velocity.length() > 0.8:
self.rotation = atan2(self.velocity.y,self.velocity.x)
# Constrains position to limits of screen
self.location = constrain(self.location,SCREEN_WIDTH,SCREEN_HEIGHT)
self.acceleration *= 0
# Memory of positions to draw Track
self.memory_location.append((self.location.x,self.location.y))
# size of track
if len(self.memory_location) > SIZE_TRACK:
self.memory_location.pop(0)
def applyForce(self, force):
"""
Applies vetor force to vehicle
Newton's second law -> F=m.a
You can divide by mass
"""
self.acceleration += force/MASS
def seek(self, target):
"""
Seek Steering force Algorithm
"""
try:
self.desired = (target - self.location).normalize()*self.max_speed
except: # if you try to normalize a null vector it will catch
self.desired = (target - self.location)*self.max_speed
# Calculates steering force
steer = self.desired - self.velocity
# Limit the magnitude of the steering force.
steer = limit(steer,self.max_force)
# Applies steering force to drone
self.applyForce(steer)
# Draws current target being seeked
pg.draw.circle(self.window, self.color_target ,target ,5, 0)
def arrive_new(self, target):
"""
Arrive using potential fields
"""
# Calculates vector desired
velocity_attract = vec2(0,0)
velocity_repulsion= vec2(0,0)
velocity_attract = derivativeBivariate(.05,.05,target,self.location)
desired_velocity = (velocity_attract - velocity_repulsion)
error = (desired_velocity - self.velocity) / SAMPLE_TIME
accelerate = limit(error, self.max_force)
self.applyForce(accelerate)
# Draws current target as a point
pg.draw.circle(self.window, self.color_target ,target ,5, 0)
def arrive(self, target):
"""
Arrive Steering Behavior
"""
# Calculates vector desired
self.desired = (target - self.location)
# get the distance to the target
d = self.desired.magnitude()
try:
dist = copy.deepcopy(self.desired.normalize()) # obtem direção
except: # If the magnitude of desired is zero it cant be normalized
dist = copy.deepcopy(self.desired)
r = RADIUS_TARGET
# Modulates the force
if d < r : # close to target it will reduce velocty till stops
# interpolation
dist *= self.max_speed*(1 + 1/r*(d-r))
else:
dist *= self.max_speed
# Steering force
steer = dist - self.velocity
#Limit the magnitude of the steering force.
steer = limit(steer, self.max_force)
# apply force to the vehicle
self.applyForce(steer)
# Simulates Wind - random Noise
wind = vec2(random.uniform(-0.15,0.15) , random.uniform(-0.15,0.15) )
self.applyForce(wind)
# Draws current target as a point
pg.draw.circle(self.window, self.color_target ,target ,5, 0)
def stay_at(self, center, r = RADIUS_TARGET):
"""
Drone Behavior - it will orbit a given target (center)
"""
posToCenter = center - self.location
#ok
if self.debug == True:
pg.draw.line(self.window,BLACK, self.location ,center,1)
# se o veiculo se encontra mais longue q o raio de rotaçao
if posToCenter.length() > r :
self.seek(center)
#self.target =copy.deepcopy(center)
else: # se ele esta dentro do raio de rotaçao
# reinicia forças
centerToPerimeter = posToCenter.normalize()*(-1*r )
#ok
pg.draw.line(self.window,(0,0,255),center,center+centerToPerimeter,5 )
posToPerimeter = centerToPerimeter + posToCenter
#pg.draw.line(window,(255,0,0),center,center+posToPerimeter,5 )
print(f'distancia até perimetro {posToPerimeter.length()}')
# new target is on the radius
# theta is the angle of the vector center to perimeter
theta = atan2(centerToPerimeter.y, centerToPerimeter.x)
theta += self.angular_speed
new_target = vec2(0,0)
# new target
new_target.x += r * cos(theta)
new_target.y += r * sin(theta)
new_target += center
if self.debug == True:
pg.draw.line(self.window,(0,255,0), center, new_target ,5)# verde é o target
pg.draw.line(self.window,BLACK, self.location, new_target, 2 )
self.seek(new_target)
def seek_around(self, center, radius_target = RADIUS_TARGET):
"""
Drone Behavior - it will orbit a given target (center) with prevision
:param center: position of target to orbite
:param radius_target: distance till center, default = RADIUS_TARGET from constants
"""
# Calculating the max speed
self.angular_speed = FORWARD_SPEED / radius_target
# future positiom
hop_ahead = HOP_AHEAD #o quanto se ve a frente
fut_pos = self.velocity.normalize()*(hop_ahead)
fut_pos += self.location
if self.debug == True:
pg.draw.line(self.window,(0,255,50),self.location,fut_pos,5)
#print(f'center: {center}')
posToCenter = center - fut_pos
# line from drone to center
if self.debug == True:
pg.draw.line(self.window,BLACK, self.location ,center,1)
# se o veiculo se encontra mais longue q o raio de rotaçao
if posToCenter.length() > radius_target:
self.seek(center)
#self.target =copy.deepcopy(center)
else: # se ele esta dentro do raio de rotaçao
# reinicia forças
centerToPerimeter = posToCenter.normalize()*(-1*radius_target)
#ok
if self.debug == True:
pg.draw.line(self.window,(0,0,255),center,center+centerToPerimeter,5 )
posToPerimeter = centerToPerimeter + posToCenter
#pg.draw.line(window,(255,0,0),center,center+posToPerimeter,5 )
#print(f'distancia até perimetro {posToPerimeter.length()}')
# new target is on the radius
# theta is the angle of the vector center to perimeter
self.theta = atan2(centerToPerimeter.y, centerToPerimeter.x)
self.theta += self.angular_speed
new_target = vec2(0,0)
# new target
new_target.x += radius_target * cos(self.theta)
new_target.y += radius_target * sin(self.theta)
new_target += center
if self.debug == True:
pg.draw.line(self.window,(0,255,0), center, new_target ,5)# verde é o target
pg.draw.line(self.window,BLACK, self.location, new_target, 2 )
self.seek(new_target)
def mission_accomplished(self):
if self.target :
return self.location.x == self.target.x and self.location.y == self.target.y
else:
return False
def get_position(self):
return self.location
def set_target(self, target):
self.target = target
def get_target(self):
try:
return self.target
except:
return None
def set_debug(self):
"""
Method to view debug lines . Assists the developer.
"""
self.debug = not self.debug
def get_debug(self):
return str(self.debug)
def collision_avoidance(self, all_positions, index):
"""
This method avoids collisions with other drones
During simulation it receives all the positions from all drones
index: is the current id of drone being checked
"""
# gets all positions of simultaneos drones
aux = 0
soma = vec2(0,0) # sums up all directions of close drones
count = 0 # counts the number of drones that are close
for p in all_positions:
# compares current position to all the drones
# aux != index -> avoids the auto-collision check
d = (self.location - p.location).magnitude()
separation_factor = 2.2
if ( (d > 0) and (d < AVOID_DISTANCE*separation_factor) and (aux != index) ) :
diff = (self.location - p.location).normalize()
diff = diff/d # proporcional to the distance. The closer the stronger needs to be
soma += diff
count += 1 # p drone is close
aux+=1
if count > 0:
media = soma / count
media = media.normalize()
media *= self.max_speed
steer = (media - self.velocity)
steer = limit(steer,self.max_force)
#----
#----
self.applyForce(steer)
def draw(self, window):
"""
Defines shape of vehicle and draw it to screen
"""
# draws track
if len(self.memory_location) >= 2:
pg.draw.lines(self.window, self.color_target, False, self.memory_location, 1)
# Drawing drone's outer circle as a hitbox?
if self.debug == True:
pg.draw.circle(self.window, (100, 100, 100), self.location, AVOID_DISTANCE, 1)
#pg.draw.line(self.window, (100, 100, 100), self.location, self.location+self.desired , 1)
# Draw Direction
v = self.velocity.length()
pg.draw.line(self.window, self.color_target, self.location, self.location + self.velocity.normalize()*v*20 , 1)
# usar sprite para desenhar drone
self.all_sprites.draw(self.window)
self.all_sprites.update(self.location,self.rotation)
def check_collision(self, positions_drones , pos_obstacles , index):
"""
Not working yet, it should detect obstacles and collision with other drones
"""
# check drones
f = 1
aux = 0
for p in positions_drones:
d = (self.location - p.location).length()
factor_distance = 2
dist_avoid = AVOID_DISTANCE*factor_distance
if ( d < dist_avoid ) and (aux != index):
#f = (self.velocity - self.velocity.normalize()*self.max_speed )/ SAMPLE_TIME
#f = limit(f,self.max_force)
#self.velocity *= d/(AVOID_DISTANCE*factor_distance)
f_repulsion = derivativeBivariate(0.001,.001, p.location , self.location )/SAMPLE_TIME
#print(f_repulsion)
f_repulsion = limit(f_repulsion,self.max_force*1.8)
self.applyForce(-f_repulsion)
#print(f'Alerta de colisão drone {index} com drone {aux}')
break
aux +=1
# --- Repulsion obstacles
for p in pos_obstacles:
d = (self.location - p).length()
factor_repulsion = 0.005
dist_avoid = RADIUS_OBSTACLES*1.6 + AVOID_DISTANCE
if ( d < dist_avoid ) :
f_repulsion = derivativeBivariate(factor_repulsion,factor_repulsion, p, self.location )/SAMPLE_TIME
#print(f_repulsion)
f_repulsion = limit(f_repulsion,self.max_force*1.8)
#----
# This condition checks if drone collided with wall
# if collided, this avoids that the drone goes over the obstacle
if (d < RADIUS_OBSTACLES + SIZE_DRONE):
self.velocity *= -1
self.applyForce(-f_repulsion)
# Deleting (Calling destructor)
def __del__(self):
print('Drone Deleted')
class VehiclePF(object):
def __init__(self, x,y, behavior, window):
"""
This is a class that can be used to test new methods
:param x and y: represents inicial target
:param behavior: State Machine
:param window: pygame screen were it will be draw
"""
self.debug = False # debug lines is Off
# Variables used to move drone
self.location = vec2(x,y) # Random position in screen
self.velocity = vec2(0.1,0) # Inicial speed
self.target = vec2(x,y)
self.acceleration = vec2(0,0)
self.radius = SIZE_DRONE # Drone Size
self.desired = vec2()
self.memory_location = [] # To draw track
self.rotation = atan2(self.location.y,self.location.x) # inicital rotation
# Arbitrary values
self.max_speed = FORWARD_SPEED
self.max_force = SEEK_FORCE
self.angular_speed = ANGULAR_SPEED
# Picks a random color for target, is used to differentiate visually during simulation
self.color_target = random_color()
# Variables related to State Machine
self.behavior = behavior
self.window = window # tela em que esta acontecendo a simulaçao
self.theta = 0 # variavel para o eight somada no seek_around
self.count = 0
# Variables to draw drone using Sprites
self.drone = Aircraft()
self.all_sprites = pg.sprite.Group()
self.all_sprites.add(self.drone)
def update(self):
"""
Standart Euler integration
Updates bahavior tree
"""
# updates behavior in machine state
self.behavior.update(self)
# Updates velocity at every step and limits it to max_speed
self.velocity += self.acceleration * 1
self.velocity = limit(self.velocity, self.max_speed)
# updates position
self.location += self.velocity
# Prevents it from crazy spinning due to very low noise speeds
if self.velocity.length() > 0.8:
self.rotation = atan2(self.velocity.y,self.velocity.x)
# Constrains position to limits of screen
self.location = constrain(self.location,SCREEN_WIDTH,SCREEN_HEIGHT)
self.acceleration *= 0
# Memory of positions to draw Track
self.memory_location.append((self.location.x,self.location.y))
# size of track
if len(self.memory_location) > SIZE_TRACK:
self.memory_location.pop(0)
def applyForce(self, force):
"""
Applies vetor force to vehicle
Newton's second law -> F=m.a
You can divide by mass
"""
self.acceleration += force/MASS
def seek(self, target):
"""
Seek Steering force Algorithm
"""
try:
self.desired = (target - self.location).normalize()*self.max_speed
except: # if you try to normalize a null vector it will catch
self.desired = (target - self.location)*self.max_speed
# Calculates steering force
steer = self.desired - self.velocity
# Limit the magnitude of the steering force.
steer = limit(steer,self.max_force)
# Applies steering force to drone
self.applyForce(steer)
# Draws current target being seeked
pg.draw.circle(self.window, self.color_target ,target ,5, 0)
def arrive(self, target):
"""
Arrive using potential fields
"""
# Calculates vector desired
velocity_attract = vec2(0,0)
velocity_repulsion= vec2(0,0)
velocity_attract = derivativeBivariate(.1,.1,target,self.location)
#acc_atract = ( desired_velocity - self.velocity )/SAMPLE_TIME
distance = (target - self.location).length()
#calculates repulsion
if distance < RADIUS_TARGET:
omega = 0.3
f = normalFunction(omega,target,self.location)
velocity_repulsion = f * (-2*omega*(self.location-target))
#acc_repulsion = (d - self.velocity) / SAMPLE_TIME
desired_velocity = (velocity_attract - velocity_repulsion)
error = (desired_velocity - self.velocity) / SAMPLE_TIME
accelerate = limit(error, self.max_force)
self.applyForce(accelerate)
# Draws current target as a point
pg.draw.circle(self.window, self.color_target ,target ,5, 0)
def arrive_old(self, target):
"""
Arrive Steering Behavior
"""
# Calculates vector desired
self.desired = (target - self.location)
# get the distance to the target
d = self.desired.magnitude()
try:
dist = copy.deepcopy(self.desired.normalize()) # obtem direção
except: # If the magnitude of desired is zero it cant be normalized
dist = copy.deepcopy(self.desired)
r = RADIUS_TARGET
# Modulates the force
if d < r : # close to target it will reduce velocty till stops
# interpolation
dist *= self.max_speed*(1 + 1/r*(d-r))
else:
dist *= self.max_speed
# Steering force
steer = dist - self.velocity
#Limit the magnitude of the steering force.
steer = limit(steer, self.max_force)
# apply force to the vehicle
self.applyForce(steer)
# Simulates Wind - random Noise
wind = vec2(random.uniform(-0.15,0.15) , random.uniform(-0.15,0.15) )
self.applyForce(wind)
# Draws current target as a point
pg.draw.circle(self.window, self.color_target ,target ,5, 0)
def stay_at(self, center, r = RADIUS_TARGET):
"""
Drone Behavior - it will orbit a given target (center)
"""
posToCenter = center - self.location
#ok
if self.debug == True:
pg.draw.line(self.window,BLACK, self.location ,center,1)
# se o veiculo se encontra mais longue q o raio de rotaçao
if posToCenter.length() > r :
self.seek(center)
#self.target =copy.deepcopy(center)
else: # se ele esta dentro do raio de rotaçao
# reinicia forças
centerToPerimeter = posToCenter.normalize()*(-1*r )
#ok
pg.draw.line(self.window,(0,0,255),center,center+centerToPerimeter,5 )
posToPerimeter = centerToPerimeter + posToCenter
#pg.draw.line(window,(255,0,0),center,center+posToPerimeter,5 )
print(f'distancia até perimetro {posToPerimeter.length()}')
# new target is on the radius
# theta is the angle of the vector center to perimeter
theta = atan2(centerToPerimeter.y, centerToPerimeter.x)
theta += self.angular_speed
new_target = vec2(0,0)
# new target
new_target.x += r * cos(theta)
new_target.y += r * sin(theta)
new_target += center
if self.debug == True:
pg.draw.line(self.window,(0,255,0), center, new_target ,5)# verde é o target
pg.draw.line(self.window,BLACK, self.location, new_target, 2 )
self.seek(new_target)
def seek_around(self, center, radius_target = RADIUS_TARGET):
"""
Drone Behavior - it will orbit a given target (center) with prevision
:param center: position of target to orbite
:param radius_target: distance till center, default = RADIUS_TARGET from constants
"""
# Calculating the max speed
self.angular_speed = FORWARD_SPEED / radius_target
# future positiom
hop_ahead = HOP_AHEAD #o quanto se ve a frente
fut_pos = self.velocity.normalize()*(hop_ahead)
fut_pos += self.location
if self.debug == True:
pg.draw.line(self.window,(0,255,50),self.location,fut_pos,5)
#print(f'center: {center}')
posToCenter = center - fut_pos
# line from drone to center
if self.debug == True:
pg.draw.line(self.window,BLACK, self.location ,center,1)
# se o veiculo se encontra mais longue q o raio de rotaçao
if posToCenter.length() > radius_target:
self.seek(center)
#self.target =copy.deepcopy(center)
else: # se ele esta dentro do raio de rotaçao
# reinicia forças
centerToPerimeter = posToCenter.normalize()*(-1*radius_target)
#ok
if self.debug == True:
pg.draw.line(self.window,(0,0,255),center,center+centerToPerimeter,5 )
posToPerimeter = centerToPerimeter + posToCenter
#pg.draw.line(window,(255,0,0),center,center+posToPerimeter,5 )
#print(f'distancia até perimetro {posToPerimeter.length()}')
# new target is on the radius
# theta is the angle of the vector center to perimeter
self.theta = atan2(centerToPerimeter.y, centerToPerimeter.x)
self.theta += self.angular_speed
new_target = vec2(0,0)
# new target
new_target.x += radius_target * cos(self.theta)
new_target.y += radius_target * sin(self.theta)
new_target += center
if self.debug == True:
pg.draw.line(self.window,(0,255,0), center, new_target ,5)# verde é o target
pg.draw.line(self.window,BLACK, self.location, new_target, 2 )
self.seek(new_target)
def get_position(self):
return self.location
def set_target(self, target):
self.target = target
def get_target(self):
try:
return self.target
except:
return None
def set_debug(self):
"""
Method to view debug lines . Assists the developer.
"""
self.debug = not self.debug
def get_debug(self):
return str(self.debug)
def collision_avoidance(self, all_positions, index):
"""
This method avoids collisions with other drones
During simulation it receives all the positions from all drones
index: is the current id of drone being checked
"""
# gets all positions of simultaneos drones
aux = 0
soma = vec2(0,0) # sums up all directions of close drones
count = 0 # counts the number of drones that are close
for p in all_positions:
# compares current position to all the drones
# aux != index -> avoids the auto-collision check
d = (self.location - p.location).magnitude()
separation_factor = 2
if ( (d > 0) and (d < AVOID_DISTANCE*separation_factor) and (aux != index) ) :
diff = (self.location - p.location).normalize()
diff = diff/d # proporcional to the distance. The closer the stronger needs to be
soma += diff
count += 1 # p drone is close
aux+=1
if count > 0:
media = soma / count
media = media.normalize()
media *= self.max_speed
steer = (media - self.velocity)
steer = limit(steer,self.max_force)
#----
#----
self.applyForce(steer)
def check_collision(self, positions_drones , pos_obstacles , index):
# check drones
f = 1
aux = 0
for p in positions_drones:
d = (self.location - p.location).length()
factor_distance = 1.8
dist_avoid = AVOID_DISTANCE*factor_distance
if ( d < dist_avoid ) and (aux != index):
f = (self.velocity - self.velocity.normalize()*self.max_speed )/ SAMPLE_TIME
f = limit(f,self.max_force)
#self.velocity *= d/(AVOID_DISTANCE*factor_distance)
self.applyForce(f)
print(f'Alerta de colisão drone {index} com drone {aux}')
break
aux +=1
# check obstacles
for p in pos_obstacles:
d = (self.location - p).length()
factor_distance = 1.3
dist_avoid = 100 * factor_distance
if ( d < dist_avoid ) :
diff = (self.location - p).normalize()
#f = -self.velocity/ SAMPLE_TIME
diff *= self.max_speed
steer = (diff - self.velocity)
steer = limit(steer,self.max_force)
#----
#----
self.applyForce(steer)
#self.velocity *= d/(AVOID_DISTANCE*factor_distance)
#self.applyForce(f)
def draw(self, window):
"""
Defines shape of vehicle and draw it to screen
"""
# draws track
# Drawing drone's outer circle as a hitbox?
if self.debug == True:
pg.draw.circle(self.window, (100, 100, 100), self.location, AVOID_DISTANCE, 1)
if len(self.memory_location) >= 2:
pg.draw.lines(self.window, self.color_target, False, self.memory_location, 1)
#pg.draw.line(self.window, (100, 100, 100), self.location, self.location+self.desired , 1)
# Draw Direction
pg.draw.line(self.window, (100, 100, 100), self.location, self.location + self.velocity.normalize()*50 , 1)
# usar sprite para desenhar drone
self.all_sprites.draw(self.window)
self.all_sprites.update(self.location,self.rotation)
# Deleting (Calling destructor)
def __del__(self):
print('Drone Deleted')