Fix main

.gitignore

@@ -4,4 +4,5 @@ install
 .vscode
 __pycache__
 .env
-IsaacSim-ros_workspaces/build_ws
+IsaacSim-ros_workspaces/build_ws
+envs

README.md

@@ -39,6 +39,20 @@ Real-time RTX lidar stream:
 </p>
 
 
+Custom envs (Office):
+
+<p align="center">
+<img width="1200" height="440" src="https://github.com/abizovnuralem/go2_omniverse/assets/33475993/e2e9bdd0-1f40-41a8-86bc-c1097ab3fd7b" alt='Go2'>
+</p>
+
+
+Custom envs (Warehouse):
+
+<p align="center">
+<img width="1200" height="440" src="https://github.com/abizovnuralem/go2_omniverse/assets/33475993/5db6f331-60be-40bd-9b4b-ead44064ee44" alt='Go2'>
+</p>
+
+
 ## Project RoadMap:
 1. PPO balancing algorithm :white_check_mark: 
 2. Keyboard real time control :white_check_mark: 
@@ -49,7 +63,7 @@ Real-time RTX lidar stream:
 7. Foot force data stream :white_check_mark:
 8. Real-time control from ROS2
 9. Nav2 with Slam_toolbox
-10. Bunch of RL-envs for custom dog training
+10. Bunch of RL-envs for custom dog training :white_check_mark:
 
 ## Your feedback and support mean the world to us. 
 
@@ -105,6 +119,12 @@ You can control the dog using "WASD" keyboard commands
 
 You can use https://github.com/abizovnuralem/go2_ros2_sdk or https://github.com/unitreerobotics/unitree_ros2 as a basement for your ROS2 setup.
 
+
+## Select custom env
+
+To use predifined custom envs, you need to download files from https://drive.google.com/drive/folders/1vVGuO1KIX1K6mD6mBHDZGm9nk2vaRyj3?usp=sharing and place them to /envs folder.
+Then you can execute it via python main.py --custom_env=office or python main.py --custom_env=warehouse commands
+
 ## Easy start
 
 For you convenience I wrote two launche files: run_orbit.sh and build_and_run_orbit.sh

main.py

@@ -47,6 +47,7 @@
 parser.add_argument("--num_envs", type=int, default=1, help="Number of environments to simulate.")
 parser.add_argument("--task", type=str, default="Isaac-Velocity-Rough-Unitree-Go2-v0", help="Name of the task.")
 parser.add_argument("--seed", type=int, default=None, help="Seed used for the environment")
+parser.add_argument("--custom_env", type=str, default="office", help="Setup the environment")
 
 
 # append RSL-RL cli arguments
@@ -81,7 +82,7 @@
 import usdrt.Sdf
 
 
-from omni.isaac.orbit_tasks.utils import get_checkpoint_path, parse_env_cfg
+from omni.isaac.orbit_tasks.utils import get_checkpoint_path
 from omni.isaac.orbit_tasks.utils.wrappers.rsl_rl import (
     RslRlOnPolicyRunnerCfg,
     RslRlVecEnvWrapper
@@ -117,7 +118,6 @@
 
 from omnigraph import create_front_cam_omnigraph
 from agent_cfg import unitree_go2_agent_cfg
-from terrain_cfg import ROUGH_TERRAINS_CFG
 
 
 import rclpy
@@ -136,22 +136,10 @@ class MySceneCfg(InteractiveSceneCfg):
     # ground terrain
     terrain = TerrainImporterCfg(
         prim_path="/World/ground",
-        terrain_type="generator",
-        terrain_generator=ROUGH_TERRAINS_CFG,
-        max_init_terrain_level=5,
-        collision_group=-1,
-        physics_material=sim_utils.RigidBodyMaterialCfg(
-            friction_combine_mode="multiply",
-            restitution_combine_mode="multiply",
-            static_friction=1.0,
-            dynamic_friction=1.0,
-        ),
-        visual_material=sim_utils.MdlFileCfg(
-            mdl_path="{NVIDIA_NUCLEUS_DIR}/Materials/Base/Architecture/Shingles_01.mdl",
-            project_uvw=True,
-        ),
+        terrain_type="plane",
         debug_vis=False,
     )
+
     # robots
     robot: ArticulationCfg = MISSING
 
@@ -317,7 +305,8 @@ class EventCfg:
 @configclass
 class CurriculumCfg:
     """Curriculum terms for the MDP."""
-    terrain_levels = CurrTerm(func=mdp.terrain_levels_vel)
+    pass
+    # terrain_levels = CurrTerm(func=mdp.terrain_levels_vel)
 
 @configclass
 class ViewerCfg:
@@ -351,7 +340,7 @@ class LocomotionVelocityRoughEnvCfg(RLTaskEnvCfg):
     rewards: RewardsCfg = RewardsCfg()
     terminations: TerminationsCfg = TerminationsCfg()
     events: EventCfg = EventCfg()
-    curriculum: CurriculumCfg = CurriculumCfg()
+    # curriculum: CurriculumCfg = CurriculumCfg()
 
     def __post_init__(self):
         """Post initialization."""
@@ -362,6 +351,7 @@ def __post_init__(self):
         self.sim.dt = 0.005
         self.sim.disable_contact_processing = True
         self.sim.physics_material = self.scene.terrain.physics_material
+
         # update sensor update periods
         # we tick all the sensors based on the smallest update period (physics update period)
         if self.scene.height_scanner is not None:
@@ -436,6 +426,19 @@ def update_meshes_for_cloud2(position_array, origin, rot):
     return rotated_vectors
 
 
+def setup_custom_env():
+    try:
+        if (args_cli.custom_env == "warehouse"):
+            cfg_scene = sim_utils.UsdFileCfg(usd_path="./envs/warehouse.usd")
+            cfg_scene.func("/World/warehouse", cfg_scene, translation=(0.0, 0.0, 0.0))
+
+        if (args_cli.custom_env == "office"):
+            cfg_scene = sim_utils.UsdFileCfg(usd_path="./envs/office.usd")
+            cfg_scene.func("/World/office", cfg_scene, translation=(0.0, 0.0, 0.0))
+    except:
+        print("Error loading custom environment. You should download custom envs folder from: https://drive.google.com/drive/folders/1vVGuO1KIX1K6mD6mBHDZGm9nk2vaRyj3?usp=sharing")
+
+
 def main():
 
     # acquire input interface
@@ -446,6 +449,7 @@ def main():
 
     """Play with RSL-RL agent."""
     # parse configuration
+
     env_cfg = UnitreeGo2CustomEnvCfg()
     env_cfg.scene.num_envs = 1
 
@@ -456,6 +460,8 @@ def main():
     # wrap around environment for rsl-rl
     env = RslRlVecEnvWrapper(env)
 
+
+
     # specify directory for logging experiments
     log_root_path = os.path.join("logs", "rsl_rl", agent_cfg["experiment_name"])
     log_root_path = os.path.abspath(log_root_path)
@@ -494,6 +500,8 @@ def main():
 
     start_time = time.time()
 
+    setup_custom_env()
+
     # simulate environment
     while simulation_app.is_running():
         # run everything in inference mode