diff --git a/carla_environment.py b/carla_environment.py index d53652009945ebc8a5968954e4f61774e772ff50..8c93ae3c41f557daf65891580f69702d34442620 100644 --- a/carla_environment.py +++ b/carla_environment.py @@ -246,28 +246,31 @@ class World: carla.Location(x=-25.534311, y=54.460903, z=0.112781), \ carla.Rotation(pitch=0.000000, yaw=-175.922913, roll=-6.221135)) - pos_diff = math.sqrt((target.location.x - x)**2 + (target.location.y - y)**2) - v = math.sqrt((vx)**2 + (vy)**2) + pos_diff = math.sqrt((target.location.x - x)**2 + (target.location.y - y)**2) + target_yaw = (-175.922913) / 180 + yaw_dif = math.sqrt((target_yaw - yaw)**2) r = -0.1 r += -0.01 * pos_diff - LEARN_FINAL_ORIENTATION = False + LEARN_FINAL_ORIENTATION = True if LEARN_FINAL_ORIENTATION: - target_yaw = (-175.922913) / 180 - yaw_dif = math.sqrt((target_yaw**2) - (yaw**2)) r += -0.01 * yaw_dif - INSENTIVE_MOVING = False + INSENTIVE_MOVING = True if v < 0.01 and INSENTIVE_MOVING: r -= 0.02 done = False - if pos_diff < 1.5: + if pos_diff < 1.2: done = True r += 100 - + if yaw_dif < 0.01: + r+= 100 + if v < 0.01: + r+=50 + if self.collision_sensor.collision is not None: r -= 100 done = True diff --git a/run_scripts/manual_carla.py b/run_scripts/manual_carla.py index 3836c48ddef51f6712feb01a4d4b8d5ddf75ea2a..d09a7b14e31ef3914843c32ab879347a50afb811 100644 --- a/run_scripts/manual_carla.py +++ b/run_scripts/manual_carla.py @@ -19,25 +19,61 @@ c.load_from = 'Carla_2_256__128__128_0.9995_0.001_1DBL' c.load_mem = True c.load_ann = True +# o = copy.deepcopy(c) +# o.name = 'JTAP_4' +# o.force_cpu = True +# o.render = True +# o.learn = True +# o.env_type = 'Carla' +# o.net_layout = [256, 128, 128] +# o.save_to = 'simple/' +# o.load_from = 'Carla_JTAP_0_256__128__32_0.9995_0.001_1DBL' +# o.load_mem = True +# o.load_ann = False +# o.learn_offline = True +# o.offline_epochs = 75000 +# o.offline_batchsize = 256 +# o.learn_iterations = 1 +# o.offline_validate_every_x_iteration = -1 +# o.learn_online = False +# o.eps_decay = 0.9995 +# o.learn_rate= 0.001 +# o.run_episodes = 15 + o = copy.deepcopy(c) -o.name = 'JTAP_5' +o.name = 'JTAP_0' +o.force_cpu = True o.render = True o.learn = True o.env_type = 'Carla' -o.net_layout = [128, 32, 32] -o.save_to = 'test/' -o.load_from = 'Carla_JTAP_4_128__32__32_0.9999_0.0005_1' -o.load_mem = True +o.net_layout = [256, 128] +o.save_to = 'orientation/' +o.load_from = '' +o.load_mem = False o.load_ann = False -o.learn_offline = True -o.offline_epochs = 1500 -o.learn_iterations = 1 -o.offline_validate_every_x_iteration = -1 o.learn_online = True -o.eps_decay = 0.9999 -o.learn_rate= 0.0005 -o.run_episodes = 500 +o.eps_decay = 0.9995 +o.learn_rate= 0.001 +o.run_episodes = 750 +validate = copy.deepcopy(c) +validate.name = 'JTAP_Validate' +validate.render = True +validate.learn = True +validate.env_type = 'Carla' +validate.net_layout = [256, 128] +validate.save_to = 'simple/' +validate.load_from = 'Carla_JTAP_0_256__128__32_0.9995_0.001_1DBL' +validate.load_mem = False +validate.load_ann = True +validate.learn_offline = False +validate.offline_epochs = 1500 +validate.learn_iterations = 1 +validate.offline_validate_every_x_iteration = -1 +validate.learn_online = True +validate.eps_decay = 0.9995 +validate.learn_rate= 0.001 +validate.run_episodes = 10 # t = copy.deepcopy(c) # t.render = True