Aggregated changes for open-sourcing

Signed-off-by: Mihir Kulkarni <[email protected]>

aerial_gym/config/asset_config/env_object_config.py

@@ -120,6 +120,64 @@ class panel_asset_params(asset_state_params):
     color = [170, 66, 66]
 
 
+class tile_asset_params(asset_state_params):
+    num_assets = 1
+
+    asset_folder = f"{AERIAL_GYM_DIRECTORY}/resources/models/environment_assets/tile_meshes"
+
+    collision_mask = 1  # objects with the same collision mask will not collide
+
+    min_position_ratio = [0.3, 0.05, 0.05]  # max position as a ratio of the bounds
+    max_position_ratio = [0.85, 0.95, 0.95]  # min position as a ratio of the bounds
+
+    specified_position = [
+        -1000.0,
+        -1000.0,
+        -1000.0,
+    ]  # if > -900, use this value instead of randomizing   the ratios
+
+    min_euler_angles = [0.0, 0.0, 0.0]  # min euler angles
+    max_euler_angles = [0.0, 0.0, 0.0]  # max euler angles
+
+    min_state_ratio = [
+        0.5,
+        0.5,
+        0.5,
+        0.0,
+        0.0,
+        0.0,
+        1.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+    ]
+    max_state_ratio = [
+        0.5,
+        0.5,
+        0.5,
+        0.0,
+        0.0,
+        0.0,
+        1.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+    ]
+
+    keep_in_env = True
+
+    collapse_fixed_joints = True
+    per_link_semantic = False
+    semantic_id = -1  # will be assigned incrementally per instance
+    # color = [170, 66, 66]
+
+
 class thin_asset_params(asset_state_params):
     num_assets = 0
 

aerial_gym/config/controller_config/lee_controller_config.py

@@ -42,4 +42,4 @@ class control:
     ]  # used for lee_position_control, lee_velocity_control and lee_attitude_control
     K_angvel_tensor_min = [0.1, 0.1, 0.1]
 
-    randomize_params = True
+    randomize_params = False

aerial_gym/config/controller_config/lmf2_controller_config.py

@@ -0,0 +1,45 @@
+import numpy as np
+
+
+class control:
+    """
+    Control parameters
+    controller:
+        lee_position_control: command_actions = [x, y, z, yaw] in environment frame scaled between -1 and 1
+        lee_velocity_control: command_actions = [vx, vy, vz, yaw_rate] in vehicle frame scaled between -1 and 1
+        lee_attitude_control: command_actions = [thrust, roll, pitch, yaw_rate] in vehicle frame scaled between -1 and 1
+    kP: gains for position
+    kV: gains for velocity
+    kR: gains for attitude
+    kOmega: gains for angular velocity
+    """
+
+    num_actions = 4
+    max_inclination_angle_rad = np.pi / 3.0
+    max_yaw_rate = np.pi / 3.0
+
+    K_pos_tensor_max = [2.0, 2.0, 1.0]  # used for lee_position_control only
+    K_pos_tensor_min = [2.0, 2.0, 1.0]  # used for lee_position_control only
+
+    K_vel_tensor_max = [
+        3.3,
+        3.3,
+        1.3,
+    ]  # used for lee_position_control, lee_velocity_control only
+    K_vel_tensor_min = [2.7, 2.7, 1.7]
+
+    K_rot_tensor_max = [
+        1.85,
+        1.85,
+        0.4,
+    ]  # used for lee_position_control, lee_velocity_control and lee_attitude_control
+    K_rot_tensor_min = [1.6, 1.6, 0.25]
+
+    K_angvel_tensor_max = [
+        0.5,
+        0.5,
+        0.09,
+    ]  # used for lee_position_control, lee_velocity_control and lee_attitude_control
+    K_angvel_tensor_min = [0.4, 0.4, 0.075]
+
+    randomize_params = True

aerial_gym/config/env_config/dynamic_environment.py

@@ -0,0 +1,61 @@
+from aerial_gym.config.asset_config.dynamic_env_object_config import *
+
+import numpy as np
+
+
+class DynamicEnvironmentCfg:
+    class env:
+        num_envs = 64  # overridden by the num_envs parameter in the task config if used
+        num_env_actions = 6  # this is the number of actions handled by the environment
+        # potentially some of these can be input from the RL agent for the robot and
+        # some of them can be used to control various entities in the environment
+        # e.g. motion of obstacles, etc.
+        env_spacing = 5.0  # not used with heightfields/trimeshes
+
+        num_physics_steps_per_env_step_mean = 10  # number of steps between camera renders mean
+        num_physics_steps_per_env_step_std = 0  # number of steps between camera renders std
+
+        render_viewer_every_n_steps = 1  # render the viewer every n steps
+        reset_on_collision = (
+            True  # reset environment when contact force on quadrotor is above a threshold
+        )
+        collision_force_threshold = 0.05  # collision force threshold [N]
+        create_ground_plane = True  # create a ground plane
+        sample_timestep_for_latency = True  # sample the timestep for the latency noise
+        perturb_observations = True
+        keep_same_env_for_num_episodes = 1
+        write_to_sim_at_every_timestep = True  # write to sim at every timestep
+
+        use_warp = True
+        lower_bound_min = [-2.0, -4.0, 0.0]  # lower bound for the environment space
+        lower_bound_max = [-1.0, -2.5, 0.0]  # lower bound for the environment space
+        upper_bound_min = [9.0, 2.5, 4.0]  # upper bound for the environment space
+        upper_bound_max = [10.0, 4.0, 5.0]  # upper bound for the environment space
+
+    class env_config:
+        include_asset_type = {
+            "panels": False,
+            "thin": False,
+            "trees": False,
+            "objects": True,
+            "left_wall": False,
+            "right_wall": False,
+            "back_wall": False,
+            "front_wall": False,
+            "top_wall": False,
+            "bottom_wall": False,
+        }
+
+        # maps the above names to the classes defining the assets. They can be enabled and disabled above in include_asset_type
+        asset_type_to_dict_map = {
+            "panels": panel_asset_params,
+            "thin": thin_asset_params,
+            "trees": tree_asset_params,
+            "objects": object_asset_params,
+            "left_wall": left_wall,
+            "right_wall": right_wall,
+            "back_wall": back_wall,
+            "front_wall": front_wall,
+            "bottom_wall": bottom_wall,
+            "top_wall": top_wall,
+        }

aerial_gym/config/env_config/empty_env.py

@@ -21,6 +21,7 @@ class env:
         sample_timestep_for_latency = True  # sample the timestep for the latency noise
         perturb_observations = True
         keep_same_env_for_num_episodes = 1
+        write_to_sim_at_every_timestep = False  # write to sim at every timestep
 
         use_warp = False
         e_s = env_spacing

aerial_gym/config/env_config/env_config_2ms.py

@@ -0,0 +1,37 @@
+# nothing to import here as the no other modules are needed to define base class
+
+
+class EnvCfg2Ms:
+    class env:
+        num_envs = 3  # number of environments
+        num_env_actions = 0  # this is the number of actions handled by the environment
+        # these are the actions that are sent to environment entities
+        # and some of them may be used to control various entities in the environment
+        # e.g. motion of obstacles, etc.
+        env_spacing = 1.0  # not used with heightfields/trimeshes
+        num_physics_steps_per_env_step_mean = 5  # number of steps between camera renders mean
+        num_physics_steps_per_env_step_std = 0  # number of steps between camera renders std
+        render_viewer_every_n_steps = 2  # render the viewer every n steps
+        collision_force_threshold = 0.010  # collision force threshold
+        manual_camera_trigger = False  # trigger camera captures manually
+        reset_on_collision = (
+            True  # reset environment when contact force on quadrotor is above a threshold
+        )
+        write_to_sim_at_every_timestep = False
+        create_ground_plane = False  # create a ground plane
+        sample_timestep_for_latency = True  # sample the timestep for the latency noise
+        perturb_observations = True
+        keep_same_env_for_num_episodes = 1
+        write_to_sim_at_every_timestep = False
+
+        use_warp = False
+        e_s = env_spacing
+        lower_bound_min = [-e_s, -e_s, -e_s]  # lower bound for the environment space
+        lower_bound_max = [-e_s, -e_s, -e_s]  # lower bound for the environment space
+        upper_bound_min = [e_s, e_s, e_s]  # upper bound for the environment space
+        upper_bound_max = [e_s, e_s, e_s]  # upper bound for the environment space
+
+    class env_config:
+        include_asset_type = {}
+
+        asset_type_to_dict_map = {}

aerial_gym/config/env_config/env_with_obstacles.py

@@ -3,6 +3,7 @@
     thin_asset_params,
     tree_asset_params,
     object_asset_params,
+    tile_asset_params,
 )
 from aerial_gym.config.asset_config.env_object_config import (
     left_wall,
@@ -37,6 +38,7 @@ class env:
         sample_timestep_for_latency = True  # sample the timestep for the latency noise
         perturb_observations = True
         keep_same_env_for_num_episodes = 1
+        write_to_sim_at_every_timestep = False  # write to sim at every timestep
 
         use_warp = True
         lower_bound_min = [-2.0, -4.0, -3.0]  # lower bound for the environment space
@@ -47,14 +49,15 @@ class env:
     class env_config:
         include_asset_type = {
             "panels": True,
+            "tiles": False,
             "thin": False,
             "trees": False,
             "objects": True,
             "left_wall": True,
             "right_wall": True,
             "back_wall": True,
             "front_wall": True,
-            "top_wall": False,
+            "top_wall": True,
             "bottom_wall": True,
         }
 
@@ -70,4 +73,5 @@ class env_config:
             "front_wall": front_wall,
             "bottom_wall": bottom_wall,
             "top_wall": top_wall,
+            "tiles": tile_asset_params,
         }

aerial_gym/config/env_config/forest_env.py

@@ -28,6 +28,7 @@ class env:
         sample_timestep_for_latency = True  # sample the timestep for the latency noise
         perturb_observations = True
         keep_same_env_for_num_episodes = 1
+        write_to_sim_at_every_timestep = False  # write to sim at every timestep
 
         use_warp = True
         lower_bound_min = [-5.0, -5.0, -1.0]  # lower bound for the environment space

aerial_gym/config/robot_config/base_octarotor_config.py

@@ -191,43 +191,51 @@ class control_allocator_config:
                 0.57735027,
             ],
             [
-                -0.01547005,
-                -0.25773503,
-                0.21547005,
-                -0.14226497,
                 0.14226497,
                 -0.21547005,
                 0.25773503,
                 0.01547005,
+                -0.01547005,
+                -0.25773503,
+                0.21547005,
+                -0.14226497,
             ],
             [
-                -0.21547005,
-                -0.14226497,
-                -0.01547005,
-                0.25773503,
                 -0.25773503,
                 0.01547005,
                 0.14226497,
                 0.21547005,
+                -0.21547005,
+                -0.14226497,
+                -0.01547005,
+                0.25773503,
             ],
             [
-                0.23094011,
-                -0.11547005,
-                -0.23094011,
                 0.11547005,
+                -0.23094011,
                 -0.11547005,
                 0.23094011,
-                0.11547005,
                 -0.23094011,
+                0.11547005,
+                0.23094011,
+                -0.11547005,
             ],
         ]
 
         class motor_model_config:
-            motor_time_constant_min = 0.01
-            motor_time_constant_max = 0.03
+            use_rps = False
+            motor_thrust_constant_min = 0.00000926312
+            motor_thrust_constant_max = 0.00001826312
+            motor_time_constant_increasing_min = 0.01
+            motor_time_constant_increasing_max = 0.03
+            motor_time_constant_decreasing_min = 0.005
+            motor_time_constant_decreasing_max = 0.005
             max_thrust = 6.25
             min_thrust = -6.25
-            max_thrust_rate = 100.0
+            max_thrust_rate = 100000.0
             thrust_to_torque_ratio = (
                 0.01  # thrust to torque ratio is related to inertia matrix dont change
             )
+            use_discrete_approximation = (
+                True  # Setting to false will compute f' based on difference and time constant
+            )