parser.add_argument("-g", "--gui", help="set gui mode.", action="store_true")
parser.add_argument("-t", "--testing", help="set testing mode", action="store_true", default=False)
parser.add_argument("-cp", "--collect_perception", help="collect the data for perception training")
parser.add_argument("-ca", "--collect_detector", help="collect the data for detector training")
parser.add_argument("-p", "--perception", help="set the path of perception neural network")
parser.add_argument("-e", "--episode", help="set the number of episode", type=int, default=1)
args = parser.parse_args()
try:
os.environ["CUDA_DEVICE_ORDER"]="PCI_BUS_ID"
os.environ["CUDA_VISIBLE_DEVICES"]="0" # specify which GPU(s) to be used
collect = args_assertions(args)
env = SetupWorld(mass=1300, wheel_radius=0.04, dt=0.05, collect=collect)
agent = ddpgAgent(Testing=args.testing)
input_preprocessor = InputPreprocessor()
avf=AVF_search()
stopdist=6.0
print('Number of episodes :',args.episode)
for episode in range(args.episode):
#while stopdist>5.0:
agnt_number=2000;
numberofsamples=2000
initial_distance = np.random.normal(100, 1)
initial_speed = np.random.normal(38,11)
#initial_speed = avf.avf_predictor(numberofsamples,agnt_number)
if initial_speed <1 : initial_speed=1
friction=np.random.normal(0.7,0.15)
if friction<=0 : friction=0
variance_fric= np.random.normal(0.2,0.06) # estimate varince between maximum and kinetic friction
if variance_fric<0 : variance_fric=0
type=int,
default=1)
args = parser.parse_args()
try:
os.environ["CUDA_DEVICE_ORDER"] = "PCI_BUS_ID"
os.environ[
"CUDA_VISIBLE_DEVICES"] = "0" # specify which GPU(s) to be used
collect = args_assertions(args)
env = SetupWorld(mass=1300,
wheel_radius=0.04,
dt=0.05,
collect=collect)
agent = ddpgAgent(Testing=args.testing)
input_preprocessor = InputPreprocessor()
rcf = rcf(100)
print('Number of episodes :', args.episode)
plot = Liveplot()
cnt = 0
coDisp = []
#rcf.trainer()
for episode in range(args.episode):
#stopdist=1.0;
#Comment below 3 lines while training , its only for running set of testing
#print('***********************************************************************************************************')
#print('******** Launching failure search test ID:',episode+1)
#np.random.seed()
#while stopdist>0:
##select parameters---------------------------------------------------------------
emergency_brake = False