bowl and microwave env

examples/run_hang_lifebuoy_teleop.py

@@ -0,0 +1,88 @@
+#!/usr/bin/env python3
+"""
+Teleop script for Hang Lifebuoy environment.
+"""
+
+import genesis as gs
+import torch
+from gs_agent.wrappers.teleop_wrapper import KeyboardWrapper
+from gs_env.sim.envs.config.registry import EnvArgsRegistry
+from gs_env.sim.envs.manipulation.hang_lifebuoy_env import HangLifebuoyEnv
+
+
+def main() -> None:
+    """Run teleop for hang lifebuoy task."""
+    print("Initializing Hang Lifebuoy Teleop System...")
+
+    # Initialize Genesis
+    gs.init(
+        seed=0,
+        precision="32",
+        logging_level="info",
+        backend=gs.cpu,  # type: ignore
+    )
+
+    # Create teleop wrapper first (without environment)
+    print("Creating teleop wrapper...")
+    teleop_wrapper = KeyboardWrapper(
+        env=None,
+        device=torch.device("cpu"),
+        movement_speed=0.01,  # Position movement speed
+        rotation_speed=0.05,  # Rotation speed
+        trajectory_filename_prefix="hang_lifebuoy_",
+    )
+
+    # Start teleop wrapper (keyboard listener) FIRST, before creating Genesis scene
+    teleop_wrapper.start()  # type: ignore
+
+    # Create task environment AFTER teleop wrapper is running
+    env = HangLifebuoyEnv(
+        args=EnvArgsRegistry["hang_lifebuoy_default"],
+        device=torch.device("cpu"),
+    )
+    teleop_wrapper.set_environment(env)
+
+    print("\n" + "=" * 50)
+    print("Hang Lifebuoy TELEOP SYSTEM READY")
+    print("=" * 50)
+    print("📝 TRAJECTORY RECORDING INSTRUCTIONS:")
+    print("   1. Press 'r' to start recording (anytime)")
+    print("   2. Move robot with arrow keys, n/m, space")
+    print("   3. Press 'r' again to stop recording and save")
+    print("   💡 Recording works from any state now!")
+    print("=" * 50)
+
+    # Run the main control loop in the main thread (Genesis viewer requires this)
+    try:
+        step_count = 0
+        while teleop_wrapper.running:
+            # Step the teleop wrapper (this processes input and steps environment)
+            teleop_wrapper.step(torch.tensor([]))
+            step_count += 1
+
+            # Check for quit command
+            if (
+                hasattr(teleop_wrapper, "last_command")
+                and teleop_wrapper.last_command
+                and hasattr(teleop_wrapper.last_command, "quit_teleop")
+                and teleop_wrapper.last_command.quit_teleop
+            ):
+                print("Quit command received, exiting...")
+                break
+
+            # Safety check - exit after 1 hour of running
+            if step_count > 180000:  # 1 hour at 50Hz
+                print("Maximum runtime reached, exiting...")
+                break
+
+    except KeyboardInterrupt:
+        print("\n👋 Teleop interrupted by user")
+
+    finally:
+        # Cleanup
+        teleop_wrapper.stop()
+        print("✅ Teleop session ended")
+
+
+if __name__ == "__main__":
+    main()

examples/run_put_bowl_teleop.py

@@ -0,0 +1,88 @@
+#!/usr/bin/env python3
+"""
+Teleop script for Put Bowl Inside Microwave environment.
+"""
+
+import genesis as gs
+import torch
+from gs_agent.wrappers.teleop_wrapper import KeyboardWrapper
+from gs_env.sim.envs.config.registry import EnvArgsRegistry
+from gs_env.sim.envs.manipulation.put_bowl_inside_microwave_env import PutBowlInsideMicrowaveEnv
+
+
+def main() -> None:
+    """Run teleop for put bowl inside microwave task."""
+    print("Initializing Put Bowl Inside Microwave Teleop System...")
+
+    # Initialize Genesis
+    gs.init(
+        seed=0,
+        precision="32",
+        logging_level="info",
+        backend=gs.cpu,  # type: ignore
+    )
+
+    # Create teleop wrapper first (without environment)
+    print("Creating teleop wrapper...")
+    teleop_wrapper = KeyboardWrapper(
+        env=None,
+        device=torch.device("cpu"),
+        movement_speed=0.01,  # Position movement speed
+        rotation_speed=0.05,  # Rotation speed
+        trajectory_filename_prefix="put_bowl_microwave_",
+    )
+
+    # Start teleop wrapper (keyboard listener) FIRST, before creating Genesis scene
+    teleop_wrapper.start()  # type: ignore
+
+    # Create task environment AFTER teleop wrapper is running
+    env = PutBowlInsideMicrowaveEnv(
+        args=EnvArgsRegistry["put_bowl_inside_microwave_default"],
+        device=torch.device("cpu"),
+    )
+    teleop_wrapper.set_environment(env)
+
+    print("\n" + "=" * 50)
+    print("Put Bowl Inside Microwave TELEOP SYSTEM READY")
+    print("=" * 50)
+    print("📝 TRAJECTORY RECORDING INSTRUCTIONS:")
+    print("   1. Press 'r' to start recording (anytime)")
+    print("   2. Move robot with arrow keys, n/m, space")
+    print("   3. Press 'r' again to stop recording and save")
+    print("   💡 Recording works from any state now!")
+    print("=" * 50)
+
+    # Run the main control loop in the main thread (Genesis viewer requires this)
+    try:
+        step_count = 0
+        while teleop_wrapper.running:
+            # Step the teleop wrapper (this processes input and steps environment)
+            teleop_wrapper.step(torch.tensor([]))
+            step_count += 1
+
+            # Check for quit command
+            if (
+                hasattr(teleop_wrapper, "last_command")
+                and teleop_wrapper.last_command
+                and hasattr(teleop_wrapper.last_command, "quit_teleop")
+                and teleop_wrapper.last_command.quit_teleop
+            ):
+                print("Quit command received, exiting...")
+                break
+
+            # Safety check - exit after 1 hour of running
+            if step_count > 180000:  # 1 hour at 50Hz
+                print("Maximum runtime reached, exiting...")
+                break
+
+    except KeyboardInterrupt:
+        print("\n👋 Teleop interrupted by user")
+
+    finally:
+        # Cleanup
+        teleop_wrapper.stop()
+        print("✅ Teleop session ended")
+
+
+if __name__ == "__main__":
+    main()

examples/run_sweep_table_teleop.py

@@ -0,0 +1,88 @@
+#!/usr/bin/env python3
+"""
+Teleop script for Sweep Table environment.
+"""
+
+import genesis as gs
+import torch
+from gs_agent.wrappers.teleop_wrapper import KeyboardWrapper
+from gs_env.sim.envs.config.registry import EnvArgsRegistry
+from gs_env.sim.envs.manipulation.sweep_table_env import SweepTableEnv
+
+
+def main() -> None:
+    """Run teleop for sweep table task."""
+    print("Initializing Sweep Table Teleop System...")
+
+    # Initialize Genesis
+    gs.init(
+        seed=0,
+        precision="32",
+        logging_level="info",
+        backend=gs.cpu,  # type: ignore
+    )
+
+    # Create teleop wrapper first (without environment)
+    print("Creating teleop wrapper...")
+    teleop_wrapper = KeyboardWrapper(
+        env=None,
+        device=torch.device("cpu"),
+        movement_speed=0.01,  # Position movement speed
+        rotation_speed=0.05,  # Rotation speed
+        trajectory_filename_prefix="sweep_table_",
+    )
+
+    # Start teleop wrapper (keyboard listener) FIRST, before creating Genesis scene
+    teleop_wrapper.start()  # type: ignore
+
+    # Create task environment AFTER teleop wrapper is running
+    env = SweepTableEnv(
+        args=EnvArgsRegistry["sweep_table_default"],
+        device=torch.device("cpu"),
+    )
+    teleop_wrapper.set_environment(env)
+
+    print("\n" + "=" * 50)
+    print("Sweep Table TELEOP SYSTEM READY")
+    print("=" * 50)
+    print("📝 TRAJECTORY RECORDING INSTRUCTIONS:")
+    print("   1. Press 'r' to start recording (anytime)")
+    print("   2. Move robot with arrow keys, n/m, space")
+    print("   3. Press 'r' again to stop recording and save")
+    print("   💡 Recording works from any state now!")
+    print("=" * 50)
+
+    # Run the main control loop in the main thread (Genesis viewer requires this)
+    try:
+        step_count = 0
+        while teleop_wrapper.running:
+            # Step the teleop wrapper (this processes input and steps environment)
+            teleop_wrapper.step(torch.tensor([]))
+            step_count += 1
+
+            # Check for quit command
+            if (
+                hasattr(teleop_wrapper, "last_command")
+                and teleop_wrapper.last_command
+                and hasattr(teleop_wrapper.last_command, "quit_teleop")
+                and teleop_wrapper.last_command.quit_teleop
+            ):
+                print("Quit command received, exiting...")
+                break
+
+            # Safety check - exit after 1 hour of running
+            if step_count > 180000:  # 1 hour at 50Hz
+                print("Maximum runtime reached, exiting...")
+                break
+
+    except KeyboardInterrupt:
+        print("\n👋 Teleop interrupted by user")
+
+    finally:
+        # Cleanup
+        teleop_wrapper.stop()
+        print("✅ Teleop session ended")
+
+
+if __name__ == "__main__":
+    main()

src/agent/gs_agent/wrappers/teleop_wrapper.py

@@ -207,22 +207,27 @@ def get_observations(self) -> torch.Tensor:
 
     def _convert_observation_to_dict(self) -> dict[str, Any]:
         """Convert tensor observation to dictionary format for teleop compatibility."""
-
-        # Get cube position
-        cube_pos = np.array(self._env.entities["cube"].get_pos())
-        cube_quat = np.array(self._env.entities["cube"].get_quat())
-
         # Create observation dictionary (for teleop compatibility)
         observation = {
             "ee_pose": self._env.entities["robot"].ee_pose,
-            # "end_effector_pos": robot_obs["end_effector_pos"],
-            # "end_effector_quat": robot_obs["end_effector_quat"],
-            "cube_pos": cube_pos,
-            "cube_quat": cube_quat,
             "rgb_images": {},  # No cameras in this simple setup
             "depth_images": {},  # No depth sensors in this simple setup
         }
 
+        # Add all object positions dynamically (excluding robot, plane, table, ee_frame)
+        excluded_entities = {"robot", "plane", "table", "ee_frame"}
+        for entity_name, entity in self._env.entities.items():
+            if entity_name not in excluded_entities:
+                try:
+                    obj_pos = np.array(entity.get_pos())
+                    obj_quat = np.array(entity.get_quat())
+                    observation[f"{entity_name}_pos"] = obj_pos
+                    observation[f"{entity_name}_quat"] = obj_quat
+                except Exception as e:
+                    # Skip entities that don't have get_pos/get_quat methods
+                    print(f"Warning: Could not get pose for entity '{entity_name}': {e}")
+                    continue
+
         return observation
 
     def _process_input(self) -> KeyboardCommand:

src/env/gs_env/sim/envs/__init__.py

@@ -0,0 +1,15 @@
+from .manipulation import (
+    GoalReachingEnv,
+    HangLifebuoyEnv,
+    PickCubeEnv,
+    PutBowlInsideMicrowaveEnv,
+    SweepTableEnv,
+)
+
+__all__ = [
+    "GoalReachingEnv",
+    "HangLifebuoyEnv",
+    "PickCubeEnv",
+    "PutBowlInsideMicrowaveEnv",
+    "SweepTableEnv",
+]

src/env/gs_env/sim/envs/config/registry.py

@@ -56,3 +56,36 @@
     reward_args={},
     img_resolution=(480, 270),
 )
+
+
+EnvArgsRegistry["put_bowl_inside_microwave_default"] = EnvArgs(
+    gs_init_args=GenesisInitArgsRegistry["default"],
+    scene_args=SceneArgsRegistry["flat_scene_default"],
+    robot_args=RobotArgsRegistry["franka_teleop"],
+    objects_args=[],  # Objects are created directly in the environment
+    sensors_args=[],
+    reward_args={},
+    img_resolution=(480, 270),
+)
+
+
+EnvArgsRegistry["hang_lifebuoy_default"] = EnvArgs(
+    gs_init_args=GenesisInitArgsRegistry["default"],
+    scene_args=SceneArgsRegistry["flat_scene_default"],
+    robot_args=RobotArgsRegistry["franka_teleop"],
+    objects_args=[],  # Objects are created directly in the environment
+    sensors_args=[],
+    reward_args={},
+    img_resolution=(480, 270),
+)
+
+
+EnvArgsRegistry["sweep_table_default"] = EnvArgs(
+    gs_init_args=GenesisInitArgsRegistry["default"],
+    scene_args=SceneArgsRegistry["flat_scene_default"],
+    robot_args=RobotArgsRegistry["franka_teleop"],
+    objects_args=[],  # Objects are created directly in the environment
+    sensors_args=[],
+    reward_args={},
+    img_resolution=(480, 270),
+)

src/env/gs_env/sim/envs/manipulation/__init__.py

@@ -1,5 +1,13 @@
 from .goal_reaching_env import GoalReachingEnv
+from .hang_lifebuoy_env import HangLifebuoyEnv
+from .pick_cube_env import PickCubeEnv
+from .put_bowl_inside_microwave_env import PutBowlInsideMicrowaveEnv
+from .sweep_table_env import SweepTableEnv
 
 __all__ = [
     "GoalReachingEnv",
+    "HangLifebuoyEnv",
+    "PickCubeEnv",
+    "PutBowlInsideMicrowaveEnv",
+    "SweepTableEnv",
 ]