Initial Commit (tested training, testing, and TRT conversion)

flightlib/configs/quadrotor_env.yaml

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+quadrotor_env:
+  collect_data: yes       # yes in Data Collection (random init state); no in Imitation Learning and Testing
+  bounding_box: [60.0, 60.0, 2.0]     # spawn quadrotor within this bounding box
+  bounding_box_origin: [-10, 20, 2.5]
+  sim_dt: 0.1             # sim_dt in imitation learning and testing
+
+data_collection:
+  roll_var: 0.01
+  pitch_var: 0.01
+
+rgb_camera_left:
+  on: yes 
+  t_BC: [0.0, 0.0, 0.1]   # translational vector of the camera with repect to the body frame
+  r_BC: [0.0, 0.0, -90]   # rotational angle (roll, pitch, yaw) of the camera in degree.
+  width: 160
+  height: 90
+  fov: 90.0               # Horizontal FOV
+  enable_depth: yes 
+  enable_segmentation: no # not used
+  enable_opticalflow: no  # not used
+
+# Enable Stereo depth when rgb_camera_right on.
+rgb_camera_right:
+  on: no
+  t_BC: [0.0, -0.2, 0.1]  # translational vector of the camera with repect to the body frame
+  r_BC: [0.0, 0.0, -90]   # rotational angle (roll, pitch, yaw) of the camera in degree.

flightlib/configs/quadrotor_ros.yaml

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+main_loop_freq: 30
+unity_render: yes
+scene_id: 4               # 0 wasteland, 1 japanese street, 4 emptyforest in standalone (SR)
+odom_topic: /juliett/ground_truth/odom
+quad_size: 0.1
+ply_path: "/flightrender/RPG_Flightmare/pointcloud_data/"
+
+rgb_camera_left:
+  on: yes 
+  t_BC: [0.0, 0.0, 0.1]   # translational vector of the camera with repect to the body frame
+  r_BC: [0.0, -5.0, -90]  # rotational angle (roll, pitch, yaw) of the camera in degree.
+  width: 160
+  height: 90
+  fov: 90.0               # Horizontal FOV
+  enable_depth: yes
+  enable_segmentation: no
+  enable_opticalflow: no
+
+# enable stereo depth when rgb_camera_right on (If use, please use larger resolution (e.g., 640x360)).
+rgb_camera_right:
+  on: no
+  t_BC: [0.0, -0.2, 0.1]  # translational vector of the camera with repect to the body frame
+  r_BC: [0.0, -5.0, -90]  # rotational angle (roll, pitch, yaw) of the camera in degree.
+
+unity:
+  spawn_trees: true
+  avg_tree_spacing: 4.0
+  bounding_box: [80.0, 80.0, 11.0]    # spawn objects within this bounding box
+  bounding_box_origin: [-10, 20, 2.5]
+  pointcloud_resolution: 0.2

flightlib/configs/traj_opt.yaml

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+vel_max: 6.0
+# segment_time = 2 * radio / vel_max
+
+# IMPORTANT PARAM: weight of penalties (6m/s)
+ws: 0.00004
+wc: 0.001
+wl: 0.00
+wg: 0.0002
+
+#ws: 0.00004
+#wc: 0.001
+#wl: 0.02
+#wg: 0.0001
+
+# trajectory and primitive parma
+horizon_num: 5
+vertical_num: 3
+horizon_camera_fov: 90.0
+vertical_camera_fov: 60.0
+horizon_anchor_fov: 30
+vertical_anchor_fov: 30
+goal_length: 10
+radio_range: 4.0    # planning horizon: 2 * radio_range
+vel_fov: 90.0       # not use currently
+radio_num: 1        # 1 just ok
+vel_num: 1          # 1 just ok
+vel_prefile: 0.0    # 0 just ok
+
+# For data efficiency, we randomly sample multiple vel and acc for each depth image with the following the distribution.
+# values at normalized speed (actual speed can be denormalized by multiplying v_multiple)
+# 单位数据倍数： v_multiple = 0.5 * v_max = radio / time
+# v数据的均值： v_mean = v_multiple * v_mean_unit
+# v数据的方差： v_var = v_multiple^2 * v_var_unit
+# a数据的均值： v_mean = v_multiple^2 * a_mean_unit
+# a数据的方差： v_var = v_multiple^4 * a_var_unit
+vx_mean_unit: 1.5
+vy_mean_unit: 0.0
+vz_mean_unit: 0.0
+vx_var_unit: 0.15
+vy_var_unit: 0.45
+vz_var_unit: 0.1
+ax_mean_unit: 0.0
+ay_mean_unit: 0.0
+az_mean_unit: 0.0
+ax_var_unit: 0.0278
+ay_var_unit: 0.05
+az_var_unit: 0.0278
+
+# penalties
+alpha: 10.0
+d0: 1.2
+r: 0.6
+
+alphav: 2.0
+v0: 3.5
+rv: 1.5
+
+alphaa: 2.0
+a0: 3.5
+ra: 1.5
+
+# deprecated weight
+wv: 0.0
+wa: 0.0

flightlib/configs/vec_env.yaml

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+env:
+  seed: 1
+  scene_id: 4   # 0 wasteland, 1 japanese street, 4 emptyforest in SR standalone
+  num_envs: 16  # Important: same to batch size!
+  num_threads: 16
+  dataset_path: "/run/yopo_sim/"
+  ply_path: "/run/yopo_sim/"
+
+unity:
+  spawn_trees: true
+  avg_tree_spacing: 4
+  # larger than the position to generate the drone to ensure the completeness of the point cloud in edge.
+  bounding_box: [80.0, 80.0, 11]      # spawn objects within this bounding box
+  bounding_box_origin: [-10, 20, 2.5]
+  pointcloud_resolution: 0.2