def __init__(
self,
config,
device=torch.device("cuda:0"),
monocheckpoint="habitat_baselines/slambased/data/mp3d_resnet50.pth",
):
super(ORBSLAM2MonodepthAgent, self).__init__(config)
self.num_actions = config.NUM_ACTIONS
self.dist_threshold_to_stop = config.DIST_TO_STOP
self.slam_vocab_path = config.SLAM_VOCAB_PATH
assert os.path.isfile(self.slam_vocab_path)
self.slam_settings_path = config.SLAM_SETTINGS_PATH
assert os.path.isfile(self.slam_settings_path)
self.slam = orbslam2.System(
self.slam_vocab_path, self.slam_settings_path, orbslam2.Sensor.RGBD
)
self.slam.set_use_viewer(False)
self.slam.initialize()
self.device = device
self.map_size_meters = config.MAP_SIZE
self.map_cell_size = config.MAP_CELL_SIZE
self.pos_th = config.DIST_REACHED_TH
self.next_wp_th = config.NEXT_WAYPOINT_TH
self.angle_th = config.ANGLE_TH
self.obstacle_th = config.MIN_PTS_IN_OBSTACLE
self.depth_denorm = config.DEPTH_DENORM
self.planned_waypoints = []
self.mapper = DirectDepthMapper(
camera_height=config.CAMERA_HEIGHT,
near_th=config.D_OBSTACLE_MIN,
far_th=config.D_OBSTACLE_MAX,
h_min=config.H_OBSTACLE_MIN,
h_max=config.H_OBSTACLE_MAX,
map_size=config.MAP_SIZE,
map_cell_size=config.MAP_CELL_SIZE,
device=device,
)
self.planner = DifferentiableStarPlanner(
max_steps=config.PLANNER_MAX_STEPS,
preprocess=config.PREPROCESS_MAP,
beta=config.BETA,
device=device,
)
self.slam_to_world = 1.0
self.timestep = 0.1
self.timing = False
self.checkpoint = monocheckpoint
if not os.path.isfile(self.checkpoint):
mp3d_url = "http://cmp.felk.cvut.cz/~mishkdmy/navigation/mp3d_ft_monodepth_resnet50.pth"
# suncg_me_url = "http://cmp.felk.cvut.cz/~mishkdmy/navigation/suncg_me_resnet.pth"
# suncg_mf_url = "http://cmp.felk.cvut.cz/~mishkdmy/navigation/suncg_mf_resnet.pth"
url = mp3d_url
print("No monodepth checkpoint found. Downloading...", url)
download(url, self.checkpoint)
self.monodepth = MonoDepthEstimator(self.checkpoint)
self.reset()
return
def __init__(self, config, device=torch.device("cuda:0")):
self.num_actions = config.NUM_ACTIONS
self.dist_threshold_to_stop = config.DIST_TO_STOP
self.slam_vocab_path = config.SLAM_VOCAB_PATH
assert os.path.isfile(self.slam_vocab_path)
self.slam_settings_path = config.SLAM_SETTINGS_PATH
assert os.path.isfile(self.slam_settings_path)
self.slam = orbslam2.System(self.slam_vocab_path,
self.slam_settings_path,
orbslam2.Sensor.RGBD)
self.slam.set_use_viewer(False)
self.slam.initialize()
self.device = device
self.map_size_meters = config.MAP_SIZE
self.map_cell_size = config.MAP_CELL_SIZE
self.pos_th = config.DIST_REACHED_TH
self.next_wp_th = config.NEXT_WAYPOINT_TH
self.angle_th = config.ANGLE_TH
self.obstacle_th = config.MIN_PTS_IN_OBSTACLE
self.depth_denorm = config.DEPTH_DENORM
self.planned_waypoints = []
self.mapper = DirectDepthMapper(
camera_height=config.CAMERA_HEIGHT,
near_th=config.D_OBSTACLE_MIN,
far_th=config.D_OBSTACLE_MAX,
h_min=config.H_OBSTACLE_MIN,
h_max=config.H_OBSTACLE_MAX,
map_size=config.MAP_SIZE,
map_cell_size=config.MAP_CELL_SIZE,
device=device,
)
self.planner = DifferentiableStarPlanner(
max_steps=config.PLANNER_MAX_STEPS,
preprocess=config.PREPROCESS_MAP,
beta=config.BETA,
device=device,
)
self.slam_to_world = 1.0
self.timestep = 0.1
self.timing = False
self.reset()
# print('self', self, dir(self))
for attr_name in dir(self):
if '__' not in attr_name:
print(attr_name, getattr(self, attr_name),
type(getattr(self, attr_name)))
type_name = str(type(getattr(self, attr_name)))
if 'numpy' in type_name or 'ensor' in type_name:
print(getattr(getattr(self, attr_name), 'shape'))
return
def __init__(self, config, follower, device=torch.device("cuda:0")):
self.slam_vocab_path = config.SLAM_VOCAB_PATH
assert os.path.isfile(self.slam_vocab_path)
self.slam_settings_path = config.SLAM_SETTINGS_PATH
assert os.path.isfile(self.slam_settings_path)
self.slam = orbslam2.System(self.slam_vocab_path,
self.slam_settings_path,
orbslam2.Sensor.RGBD)
self.slam.set_use_viewer(False)
self.slam.initialize()
self.device = device
self.map_size_meters = config.MAP_SIZE
self.map_cell_size = config.MAP_CELL_SIZE
self.obstacle_th = config.MIN_PTS_IN_OBSTACLE
self.depth_denorm = config.DEPTH_DENORM
self.mapper = DirectDepthMapper(
camera_height=config.CAMERA_HEIGHT,
near_th=config.D_OBSTACLE_MIN,
far_th=config.D_OBSTACLE_MAX,
h_min=config.H_OBSTACLE_MIN,
h_max=config.H_OBSTACLE_MAX,
map_size=config.MAP_SIZE,
map_cell_size=config.MAP_CELL_SIZE,
device=device,
)
self.slam_to_world = 1.0
self.timestep = 0.1
self.timing = False
self.follower = follower
self.reset()
return