52 lines
1.6 KiB
YAML
52 lines
1.6 KiB
YAML
# IMPORTANT: velocity in testing (modifiable)
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velocity: 6.0
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# IMPORTANT: vel_max and acc_max in training
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# not the actual values in testing, ensure consistency between testing and training, please refer to ../policy/primitive.py
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vel_max_train: 6.0
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acc_max_train: 6.0
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# IMPORTANT: weight of costs for unit speed (can be visualized in tensorboard)
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wg: 0.12 # guidance (approaching the goal)
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ws: 10.0 # smoothness (smaller jerk)
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wa: 1.0 # acceleration (smaller acceleration)
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wc: 1.0 # collision (distance to obstacle)
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# dataset: set image_size = primitive_num × downsampling_factor (×32 for ResNet-18) in each axis
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dataset_path: "../dataset"
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image_height: 96
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image_width: 160
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# trajectory and primitive param (Note: traj_time = 2 * radio / vel_max) (can be visualized in rviz)
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horizon_num: 5
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vertical_num: 3
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horizon_camera_fov: 90.0
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vertical_camera_fov: 60.0
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horizon_anchor_fov: 30.0
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vertical_anchor_fov: 30.0
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radio_range: 5.0 # planning horizon: 2 * radio_range
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radio_num: 1 # only support 1 currently
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# safety penalties
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d0: 1.2
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r: 0.6
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# distribution for unit state sampling (can be visualized by 'python ./policy/yopo_dataset.py')
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vx_mean_unit: 0.4
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vy_mean_unit: 0.0
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vz_mean_unit: 0.0
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vx_std_unit: 2.0
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vy_std_unit: 0.45
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vz_std_unit: 0.3
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ax_mean_unit: 0.0
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ay_mean_unit: 0.0
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az_mean_unit: 0.0
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ax_std_unit: 0.5
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ay_std_unit: 0.5
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az_std_unit: 0.3
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goal_pitch_std: 10.0 # clip goal_length to: 2 * radio_range; 10% probability [0, 2 * radio_range]
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goal_yaw_std: 20.0
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# extend the map to avoid trajectory exceeding bounds (especially in z-axis) and treating the sky outside the map as obstacle
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map_expand_min: [0, 0, 0.2]
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map_expand_max: [0, 0, 6.0] |