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config.yaml
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config.yaml
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unity:
scene_id: 1 # 0 warehouse, 1 garage, 3 natureforest
render: yes
spawn_trees: false
spawn_objects: true
start_area: [16, 1.6]
start_origin: [0, -1.8]
radius_area: 2.2
radius_origin: 1.7
end_area: [16, 1.6]
end_origin: [0, 28]
bounding_box: [20.0, 30.0] # spawn objects within this bounding box
bounding_box_origin: [-10.0, 3.0] # relative to the quadrotor start position
min_object_scale: [0.5, 0.5, 2.6] # scale of objects in meters, will sample uniformly between bounds
max_object_scale: [1.0, 1.0, 3.8] # scale of objects in meters, will sample uniformly between bounds
basic_size: [1.0, 1.0, 2]
if_get_pointcloud: true
range: [20, 38, 9]
origin: [0.0, 16.5, 4.5]
res: 0.10
ros:
input_update_freq: 10
use_depth: true
velocity_frame: wf
seq_len: 1
goal_obs_dim: 7
trial: 2 # if you want to load the checkpoint for the file of 'Recurrent_2'
iter: 200 # if you want to load the checkpoint named as 'iter_00600.pth'
pre_steps: 4
drone:
length: 0.2
width: 0.2
simulation:
seed: 21
sim_dt: 0.1
max_t: 5.0
action_mode: 1 # 0 velocity, 1 acceleration
num_envs: 4
num_threads: 4
act_max: [4.0, 4.0, 1.0, 0.6]
act_min: [-4.0, -4.0, -1.0, -0.6]
reset_if_collide: true
use_stereo_vision: true
rewards:
colli_coeff: -0.00 # reward coefficient for position
distance_coeff: -0.000 # reward coefficient for orientation
vel_coeff: -0.000 # reward coefficient for linear velocity
vert_coeff: -0.002 # reward coefficient for changes of input
angle_vel_coeff: -0.000 # reward coefficient for angular velocity
input_coeff: -0.0003 # reward coefficient for changes of input
yaw_coeff: -0.000
names:
[
"goal_penalty",
"speed_penalty",
"vertical_penalty",
"angular_penalty",
"input_penalty",
"yaw_penalty",
"total",
]
rgb_camera:
on: yes
t_BC: [0.0, 0.0, 0.3] # translational vector of the camera with repect to the body frame
r_BC: [0.0, 0.0, 0.0] # rotational angle (roll, pitch, yaw) of the camera in degree.
channels: 3
width: 256
height: 256
fov: 70.0
enable_depth: no
enable_segmentation: no
enable_opticalflow: no
use_stereo_vision: false