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behaviors.py
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behaviors.py
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__author__ = 'ohodegaa'
from abc import ABCMeta, abstractmethod
from robotic_controller import BBCON
from sensor_object import *
from random import randint
from imager2 import *
class Behavior(metaclass=ABCMeta):
def __init__(self, bbcon: BBCON, priority: float):
self.bbcon = bbcon
self.active_flag = True
self.motor_recommendations = {} # dict[key:motob object, val: [(motob function, [arg1, arg2..]), (...)]
self.halt_request = False
self.priority = priority
self.match_degree = 1
self.motor = self.bbcon.belts
self.weight = self.priority * self.match_degree
self.sensor_value = None
@abstractmethod
def gather_sensor_values(self):
pass
@abstractmethod
def consider_deactivation(self):
pass
@abstractmethod
def consider_activation(self):
pass
@abstractmethod
def sense_and_act(self):
pass
def update_weight(self):
self.weight = self.priority * self.match_degree
def update(self):
if self.active_flag:
self.consider_deactivation()
else:
self.consider_activation()
if self.active_flag:
self.gather_sensor_values()
self.sense_and_act()
self.update_weight()
class FollowLine(Behavior):
def __init__(self, bbcon: BBCON, priority: float):
super().__init__(bbcon, priority)
self.floor_sensor = None
for senOb in bbcon.sensobs:
if isinstance(senOb, FloorSensor):
self.floor_sensor = senOb
break
if self.floor_sensor is None:
print("Floor sensos not found")
def consider_activation(self):
pass
def consider_deactivation(self):
pass
def gather_sensor_values(self):
print("floor_sensor.get_value", self.floor_sensor.get_value())
self.sensor_value = self.floor_sensor.get_value()
def sense_and_act(self):
# produce motor recommendations
self.motor_recommendations = {self.motor: [(self.motor.forward, [0.1])]}
check = [
self.sensor_value[2] and self.sensor_value[3],
self.sensor_value[2], self.sensor_value[3],
self.sensor_value[1], self.sensor_value[4],
self.sensor_value[0], self.sensor_value[5]
]
motor_action = [
(self.motor.forward, []),
(self.motor.turn_left, [0.5]), (self.motor.turn_right, [0.5]),
(self.motor.turn_left, [0.8]), (self.motor.turn_right, [0.8]),
(self.motor.sharp_left, []), (self.motor.sharp_right, [])
]
for i in range(len(check) - 1, -1, -1):
if check[i]:
if i > 4:
self.match_degree = 1.0
elif i > 2:
self.match_degree = 0.8
else:
self.match_degree = 0.5
self.motor_recommendations = {self.motor: [motor_action[i]]}
break
class AvoidObject(Behavior):
def __init__(self, bbcon: BBCON, priority: float):
super().__init__(bbcon, priority)
self.front_sensor = None
self.camera = None
self.color_limit = 0.50
self.motor_recommendations = {self.motor: [(self.motor.forward, [])]}
for sensOb in bbcon.sensobs:
if isinstance(sensOb, FrontSensor):
self.front_sensor = sensOb
if isinstance(sensOb, CameraSensor):
self.camera = sensOb
def gather_sensor_values(self):
self.sensor_value = self.front_sensor.get_value()
def consider_activation(self):
pass
def consider_deactivation(self):
pass
def analyze_image(self, image):
image = Imager(image=image)
image_percentages = []
for y in range(image.ymax):
for x in range(image.xmax):
pixels = image.get_pixel(x, y)
try:
image_percentages.append(pixels[0] / sum(pixels))
except:
pass
red_mean = sum(image_percentages) / len(image_percentages)
print("red:", red_mean)
return red_mean
def sense_and_act(self):
if self.sensor_value < 20:
print("Object detected")
self.motor.stop()
self.match_degree = 1
image = self.camera.get_image()
red_value = self.analyze_image(image)
if red_value > self.color_limit:
self.motor_recommendations = {self.motor: [(self.motor.backwards, [0.05]), (self.motor.full_turn, []),
(self.motor.forward, [0.05])]}
else:
self.motor_recommendations = {self.motor: [(self.motor.forward, [2.5]), (self.motor.backwards, [2.5])]}
else:
self.match_degree = 0.1
self.motor_recommendations = {self.motor: [(self.motor.forward, [])]}
class SideSight(Behavior):
def __init__(self, bbcon: BBCON, priority: float):
super().__init__(bbcon, priority)
self.side_sensor = None
for senOb in bbcon.sensobs:
if isinstance(senOb, SideSensor):
self.side_sensor = senOb
break
def consider_activation(self):
pass
def consider_deactivation(self):
pass
def gather_sensor_values(self):
self.sensor_value = self.side_sensor.get_value()
def sense_and_act(self):
right = True
if self.sensor_value[0]:
right = False
elif self.sensor_value[1]:
right = True
else:
self.motor_recommendations = {self.motor: [(self.motor.random, [])]}
return
self.match_degree = 0.8
turn = (self.motor.sharp_right, [0.25]) if right else (self.motor.sharp_left, [0.25])
forward = (self.motor.forward, [1])
backwards = (self.motor.backwards, [1])
turn_back = (self.motor.sharp_left, [0.25]) if right else (self.motor.sharp_right, [0.25])
self.motor_recommendations = {self.motor: [turn, forward, backwards, turn_back]}