def __init__(self):
self.simage = np.zeros((20, 100), dtype=np.uint8)
self.svelocity = np.zeros((3, ), dtype=np.float32)
self.sdistance = np.zeros((3, ), dtype=np.float32)
self.sgeofence = np.zeros((6, ), dtype=np.float32)
self.stotalvelocity = np.zeros((12, ), dtype=np.float32)
self.stotaldistance = np.zeros((12, ), dtype=np.float32)
self.stotalgeofence = np.zeros((24, ), dtype=np.float32)
self.action_space = spaces.Discrete(6)
self.goal = [137.5, -48.7]
self.distance = np.sqrt(
np.power((self.goal[0]), 2) + np.power((self.goal[1]), 2))
self.episodeN = 0
self.stepN = 0
'''
Additional log info
self.allLogs = { 'reward':[0] }
self.allLogs['distance'] = [self.distance]
self.allLogs['track'] = [-2]
self.allLogs['action'] = [1]
self.allLogs['svelocity'] = self.svelocity
self.allLogs['sdistance'] = self.sdistance
self.allLogs['sgeofence'] = self.sgeofence
'''
self._seed()
global airgym
airgym = myAirSimClient()
def __init__(self):
#self.cum_reward = 0.0
#self.discount = 0.8 #check others
self.simage = np.zeros((20, 100), dtype=np.uint8)
self.svelocity = np.zeros((2, ), dtype=np.float32)
self.sdistance = np.zeros((3, ), dtype=np.float32)
self.sgeofence = np.zeros((4, ), dtype=np.float32)
self.sAE = np.zeros((2, ), dtype=np.float32)
self.action_space = spaces.Discrete(5)
self.goal = [112, 10]
self.episodeN = 0
self.stepN = 0
self.allLogs = {'reward': [0]}
self.allLogs['track'] = [-2]
self.allLogs['action'] = [1]
self.seed()
global airgym
airgym = myAirSimClient()
def __init__(self):
global airgym
airgym = myAirSimClient()
self.drone1_vehicle_name = "Drone1"
self.target1_vehicle_name = "Target1"
self.target_thershold=2.5
self.simage = np.zeros((90, 256,1), dtype=np.uint8)
self.rgbimage = np.zeros((90, 256,3), dtype=np.uint8)
self.svelocity = np.zeros((3,), dtype=np.float32)
self.sdistance = np.zeros((3,), dtype=np.float32)
self.sgeofence = np.zeros((6,), dtype=np.float32)
self.stotalvelocity = np.zeros((12,), dtype=np.float32)
self.stotaldistance = np.zeros((12,), dtype=np.float32)
self.stotalgeofence = np.zeros((24,), dtype=np.float32)
self.action_space = spaces.Discrete(6)
#self.drone = trackgym.simGetGroundTruthKinematics(self.drone1_vehicle_name).position
self.init_goal = airgym.simGetGroundTruthKinematics(self.target1_vehicle_name).position #[137.5, -48.7,-4]
self.goal={'x_val':self.init_goal.x_val+offset.x_val, 'y_val':self.init_goal.y_val+offset.y_val,'z_val':self.init_goal.z_val}
self.goal = dotdict(self.goal)
self.distance = np.sqrt(np.power((self.goal.x_val),2) + np.power((self.goal.y_val),2) + np.power((self.goal.z_val),2))
self.episodeN = 0
self.stepN = 0
#Additional log info
self.allLogs = { 'reward':[0] }
self.allLogs['distance'] = [self.distance]
self.allLogs['track'] = [-2]
self.allLogs['action'] = [1]
self.allLogs['svelocity'] = self.svelocity
self.allLogs['sdistance'] = self.sdistance
self.allLogs['sgeofence'] = self.sgeofence
self.seed()
def __init__(self):
# left depth, center depth, right depth, yaw
self.observation_space = spaces.Box(low=0, high=255, shape=(30, 100))
self.state = np.zeros((30, 100), dtype=np.uint8)
self.action_space = spaces.Discrete(3)
self.goal = [221.0, -9.0] # global xy coordinates
self.episodeN = 0
self.stepN = 0
self.allLogs = {'reward': [0]}
self.allLogs['distance'] = [221]
self.allLogs['track'] = [-2]
self.allLogs['action'] = [1]
self._seed()
global airgym
airgym = myAirSimClient()
import logging
import numpy as np
import random
import gym
from gym import spaces
from gym.utils import seeding
from gym.spaces import Tuple, Box, Discrete, MultiDiscrete, Dict
from gym.spaces.box import Box
from gym_airsim.envs.myAirSimClient import *
from airsim.client import *
logger = logging.getLogger(__name__)
global airgym
airgym = myAirSimClient()
class AirSimEnv(gym.Env):
airgym = None
def __init__(self):
# left depth, center depth, right depth, yaw
self.observation_space = spaces.Box(low=0, high=255, shape=(1,))
self.state = np.zeros((1,), dtype=np.uint8)
self.action_space = spaces.Discrete(3)
self.goal = [221.0, -9.0] # global xy coordinates
self.episodeN = 0
self.stepN = 0
import gym
from gym import spaces
from gym.utils import seeding
from gym_airsim.envs.myAirSimClient import *
from airsim.client import *
import random
logger = logging.getLogger(__name__)
airSimClient = myAirSimClient()
class AirSimEnv(gym.Env):
def __init__(self):
# x_pos, y_pos, direction to goal, distance to goal, distance_sensor.front
self.observation_space = spaces.Box(low=-500, high=500, shape=(5, ))
self.state = np.zeros((5, ), dtype=np.uint8)
self.action_space = spaces.Discrete(3)
# self.obstacle_list = [[0.0, -7.0], [0.0, 5.0], [10.0, -7.0], [10.0, -1.0], [10.0, 5.0], [5, -3.0], [5.0, 3.0]]
# index = np.random.randint(0, len(self.goal_list) - 1)
# self.goal = self.goal_list[index] # global xy coordinates
self.x_goal = random.uniform(-2, 16)
self.y_goal = random.uniform(-10, 8)
self.goal = [self.x_goal, self.y_goal]
self.episodeN = 0
self.stepN = 0
self.dis = np.sqrt(
np.power((self.goal[0] - airSimClient.home_pos.x_val), 2) +
np.power((self.goal[1] - airSimClient.home_pos.y_val), 2))
self.allLogs = {
'reward': [0],