isaac-sim-photorealistic

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Isaac Sim Architecture:
┌─────────────────────────────────────────┐
│              Omniverse Core             │
├─────────────────────────────────────────┤
│  PhysX Physics Engine + GPU Acceleration│
├─────────────────────────────────────────┤
│     USD Scene Representation            │
├─────────────────────────────────────────┤
│      Sensor Simulation                  │
│    (Cameras, LiDAR, IMU, etc.)         │
├─────────────────────────────────────────┤
│        ROS 2 Interface                  │
├─────────────────────────────────────────┤
│    AI Training & Synthetic Data         │
└─────────────────────────────────────────┘

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# Example Python code to create a USD stage in Isaac Sim
import omni
from pxr import Usd, UsdGeom, Gf, Sdf

# Create a new stage
stage = Usd.Stage.CreateNew("humanoid_robot.usd")

# Create a root prim
world_prim = stage.DefinePrim("/World", "Xform")

# Create a robot body
robot_prim = stage.DefinePrim("/World/Robot", "Xform")

# Add a link to the robot
body_link = stage.DefinePrim("/World/Robot/Body", "Xform")
mesh = UsdGeom.Mesh.Define(stage, "/World/Robot/Body/Mesh")

# Set mesh properties
mesh.CreatePointsAttr([Gf.Vec3f(-0.5, -0.5, -0.5), Gf.Vec3f(0.5, -0.5, -0.5), ...])
mesh.CreateFaceVertexCountsAttr([4])
mesh.CreateFaceVertexIndicesAttr([0, 1, 2, 3])

# Save the stage
stage.GetRootLayer().Save()

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# System requirements
# - NVIDIA GPU with CUDA support (RTX series recommended)
# - Ubuntu 20.04 or Windows 10/11
# - At least 16GB RAM, 32GB+ recommended
# - NVIDIA driver 495.44 or newer

# Install Isaac Sim (typically done through Omniverse Launcher)
# Download from NVIDIA Developer website

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# launch_isaac_sim.py
import omni
from omni.isaac.core import World
from omni.isaac.core.utils.stage import add_reference_to_stage
from omni.isaac.core.utils.nucleus import get_assets_root_path
from omni.isaac.core.utils.prims import get_prim_at_path
import carb

# Create a world instance
world = World(stage_units_in_meters=1.0)

# Add a robot from the NVIDIA Isaac Sim assets
assets_root_path = get_assets_root_path()
if assets_root_path is None:
    carb.log_error("Could not find Isaac Sim assets. Please check your Isaac Sim installation.")

# Example: Adding a simple robot
robot_path = assets_root_path + "/Isaac/Robots/Franka/fr3.usd"
add_reference_to_stage(usd_path=robot_path, prim_path="/World/Robot")

# Reset the world to apply changes
world.reset()

# Run simulation
for i in range(1000):
    world.step(render=True)
    if i % 100 == 0:
        print(f"Simulation step {i}")

# Cleanup
world.clear()

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# humanoid_robot.py
import omni
from omni.isaac.core import World
from omni.isaac.core.robots import Robot
from omni.isaac.core.utils.stage import add_reference_to_stage
from omni.isaac.core.utils.prims import create_prim
from omni.isaac.core.utils.nucleus import get_assets_root_path
from pxr import Gf, UsdGeom, PhysxSchema
import numpy as np

class HumanoidRobot(Robot):
    def __init__(
        self,
        prim_path: str,
        name: str = "humanoid_robot",
        usd_path: str = None,
        position: np.ndarray = np.array([0.0, 0.0, 0.0]),
        orientation: np.ndarray = np.array([0.0, 0.0, 0.0, 1.0]),
    ) -> None:
        self._usd_path = usd_path
        self._name = name

        super().__init__(
            prim_path=prim_path,
            name=name,
            position=position,
            orientation=orientation,
        )

    def add_to_stage(self, stage, prefix=None):
        """Add humanoid robot to stage"""
        if self._usd_path:
            add_reference_to_stage(self._usd_path, self.prim_path)
        else:
            # Create a simple humanoid model from primitives
            self._create_simple_humanoid()

    def _create_simple_humanoid(self):
        """Create a simple humanoid robot using USD prims"""
        # Create body parts
        self._create_body_part("torso", [0.0, 0.0, 1.0], [0.3, 0.3, 0.6])
        self._create_body_part("head", [0.0, 0.0, 1.45], [0.2, 0.2, 0.2])
        self._create_body_part("left_arm_upper", [-0.2, 0.0, 1.2], [0.08, 0.08, 0.4])
        self._create_body_part("left_arm_lower", [-0.2, 0.0, 0.9], [0.06, 0.06, 0.35])
        self._create_body_part("right_arm_upper", [0.2, 0.0, 1.2], [0.08, 0.08, 0.4])
        self._create_body_part("right_arm_lower", [0.2, 0.0, 0.9], [0.06, 0.06, 0.35])
        self._create_body_part("left_leg_upper", [-0.1, 0.0, 0.5], [0.09, 0.09, 0.5])
        self._create_body_part("left_leg_lower", [-0.1, 0.0, 0.1], [0.08, 0.08, 0.4])
        self._create_body_part("right_leg_upper", [0.1, 0.0, 0.5], [0.09, 0.09, 0.5])
        self._create_body_part("right_leg_lower", [0.1, 0.0, 0.1], [0.08, 0.08, 0.4])
        self._create_body_part("left_foot", [-0.1, 0.0, -0.15], [0.15, 0.1, 0.06])
        self._create_body_part("right_foot", [0.1, 0.0, -0.15], [0.15, 0.1, 0.06])

    def _create_body_part(self, name, position, size):
        """Create a single body part"""
        # Create a rigid body prim
        prim_path = f"{self.prim_path}/{name}"
        create_prim(
            prim_path=prim_path,
            prim_type="Xform",
            position=position
        )

        # Add collision and visual shapes
        collision_path = f"{prim_path}/collision"
        visual_path = f"{prim_path}/visual"

        # Collision mesh (simplified for performance)
        create_prim(
            prim_path=collision_path,
            prim_type="Cube",
            position=[0, 0, 0],
            attributes={"size": min(size)}
        )

        # Visual mesh (detailed for rendering)
        create_prim(
            prim_path=visual_path,
            prim_type="Cube",
            position=[0, 0, 0],
            attributes={"size": min(size)}
        )

        # Apply physics properties
        self._apply_physics_properties(prim_path, size)

    def _apply_physics_properties(self, prim_path, size):
        """Apply physics properties to a prim"""
        # Calculate mass based on size (assuming density of 1000 kg/m^3)
        volume = size[0] * size[1] * size[2]
        mass = volume * 1000  # kg

        # Get the prim and apply rigid body properties
        prim = get_prim_at_path(prim_path)
        rigid_api = PhysxSchema.PhysxConeAttachmentAPI.Apply(prim)

        # Set mass properties
        rigid_api.GetMassAttr().Set(mass)

# Example usage
def create_humanoid_world():
    world = World(stage_units_in_meters=1.0)

    # Create and add humanoid robot
    robot = HumanoidRobot(
        prim_path="/World/HumanoidRobot",
        name="humanoid_robot",
        position=np.array([0.0, 0.0, 0.5])
    )

    world.scene.add(robot)

    # Add ground plane
    world.scene.add_default_ground_plane()

    return world, robot

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// Example MDL material definition for humanoid robot
mdl {
  material humanoid_metal =
    mdl::surface(
      base = color(0.8, 0.8, 0.9),
      metallic = 0.7,
      roughness = 0.2,
      normal = texture::get_normal()
    );
}

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# lighting_setup.py
from omni.isaac.core.utils.prims import create_prim
from omni.isaac.core.utils.stage import get_current_stage
from pxr import UsdLux, Gf

def setup_photorealistic_lighting():
    """Set up photorealistic lighting for the scene"""
    stage = get_current_stage()

    # Create dome light for environment lighting
    dome_light = UsdLux.DomeLight.Define(stage, "/World/DomeLight")
    dome_light.CreateIntensityAttr(1000)
    dome_light.CreateTextureFileAttr("path/to/hdr/environment.hdr")

    # Create key light (main light source)
    key_light = UsdLux.DistantLight.Define(stage, "/World/KeyLight")
    key_light.AddTranslateOp().Set(Gf.Vec3f(5, 5, 10))
    key_light.CreateIntensityAttr(3000)
    key_light.CreateColorAttr(Gf.Vec3f(1.0, 0.98, 0.9))

    # Create fill light (softens shadows)
    fill_light = UsdLux.DistantLight.Define(stage, "/World/FillLight")
    fill_light.AddTranslateOp().Set(Gf.Vec3f(-3, 2, 5))
    fill_light.CreateIntensityAttr(1000)
    fill_light.CreateColorAttr(Gf.Vec3f(0.8, 0.85, 1.0))

def setup_sensor_lighting():
    """Set up lighting specifically for sensor simulation"""
    stage = get_current_stage()

    # Create lighting that affects sensor data
    sensor_light = UsdLux.RectLight.Define(stage, "/World/SensorLight")
    sensor_light.CreateWidthAttr(2.0)
    sensor_light.CreateHeightAttr(2.0)
    sensor_light.CreateIntensityAttr(500)
    sensor_light.CreateColorAttr(Gf.Vec3f(1.0, 1.0, 1.0))
    sensor_light.AddTranslateOp().Set(Gf.Vec3f(0, 0, 3))

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# environment_creation.py
from omni.isaac.core.utils.stage import add_reference_to_stage
from omni.isaac.core.utils.prims import create_prim
from pxr import Gf, UsdGeom
import numpy as np

def create_office_environment():
    """Create a photorealistic office environment"""

    # Create office floor
    create_prim(
        prim_path="/World/OfficeFloor",
        prim_type="Plane",
        position=[0, 0, 0],
        attributes={"size": 20.0}
    )

    # Add realistic floor material
    floor_material = create_prim(
        prim_path="/World/Looks/FloorMaterial",
        prim_type="Material"
    )

    # Add office furniture
    add_office_furniture()

    # Add realistic textures and materials
    apply_realistic_materials()

def add_office_furniture():
    """Add realistic office furniture"""
    # Desk
    create_prim(
        prim_path="/World/Desk",
        prim_type="Cube",
        position=[3, 0, 0.75],
        attributes={"size": 2.0}
    )

    # Chair
    create_prim(
        prim_path="/World/Chair",
        prim_type="Cylinder",
        position=[2, -1, 0.5],
        attributes={"radius": 0.3, "height": 1.0}
    )

    # Bookshelf
    create_prim(
        prim_path="/World/Bookshelf",
        prim_type="Cube",
        position=[-4, 2, 1.0],
        attributes={"size": 1.5}
    )

def apply_realistic_materials():
    """Apply realistic materials to environment objects"""
    # This would involve setting up MDL materials for realistic surfaces
    # such as wood, metal, glass, fabric, etc.
    pass

def create_warehouse_environment():
    """Create a warehouse environment with realistic lighting"""

    # Large floor area
    create_prim(
        prim_path="/World/WarehouseFloor",
        prim_type="Plane",
        position=[0, 0, 0],
        attributes={"size": 50.0}
    )

    # Industrial lighting
    for i in range(10):
        for j in range(5):
            create_prim(
                prim_path=f"/World/Lights/HangLight_{i}_{j}",
                prim_type="Sphere",
                position=[i*5 - 20, j*8 - 16, 8],
                attributes={"radius": 0.2}
            )

    # Pallets and boxes
    for i in range(20):
        create_prim(
            prim_path=f"/World/Pallet_{i}",
            prim_type="Cube",
            position=[np.random.uniform(-20, 20), np.random.uniform(-20, 20), 0.1],
            attributes={"size": 1.2}
        )

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# sensor_integration.py
from omni.isaac.sensor import Camera, RayFrameReader
from omni.isaac.range_sensor import LidarRtx
import numpy as np

class IsaacSensors:
    def __init__(self, robot_prim_path):
        self.robot_prim_path = robot_prim_path
        self.cameras = []
        self.lidars = []
        self.imus = []

    def add_rgb_camera(self, name, position, orientation):
        """Add a high-fidelity RGB camera"""
        camera = Camera(
            prim_path=f"{self.robot_prim_path}/{name}",
            position=position,
            orientation=orientation,
            resolution=(1920, 1080),
            frequency=30
        )

        # Configure camera properties for photorealism
        camera.get_sensor().set_focal_length(24.0)  # mm
        camera.get_sensor().set_horizontal_aperture(36.0)  # mm
        camera.get_sensor().set_f_stop(2.8)

        self.cameras.append(camera)
        return camera

    def add_lidar(self, name, position, orientation):
        """Add a high-fidelity LiDAR sensor"""
        lidar = LidarRtx(
            prim_path=f"{self.robot_prim_path}/{name}",
            position=position,
            orientation=orientation,
            config="Solid-State-Mixed",
            min_range=0.1,
            max_range=25.0,
            fov=360
        )

        # Configure LiDAR for photorealistic simulation
        lidar.set_max_rays_in_flight(64000000)  # High performance mode
        lidar.set_laser_offset([0.0, 0.0, 0.0])

        self.lidars.append(lidar)
        return lidar

    def add_imu(self, name, position, orientation):
        """Add an IMU sensor"""
        # IMU integration in Isaac Sim typically uses contact sensors
        # and rigid body dynamics for realistic inertial measurements
        imu_prim_path = f"{self.robot_prim_path}/{name}"

        # Create IMU as a reference to a rigid body
        create_prim(
            prim_path=imu_prim_path,
            prim_type="Xform",
            position=position
        )

        self.imus.append(imu_prim_path)
        return imu_prim_path

    def capture_sensor_data(self):
        """Capture data from all sensors"""
        sensor_data = {}

        # Capture camera data
        for camera in self.cameras:
            rgb_data = camera.get_rgb()
            depth_data = camera.get_depth()
            sensor_data[camera.name] = {
                "rgb": rgb_data,
                "depth": depth_data
            }

        # Capture LiDAR data
        for lidar in self.lidars:
            point_cloud = lidar.get_point_cloud()
            sensor_data[lidar.name] = {
                "point_cloud": point_cloud
            }

        return sensor_data

def setup_robot_sensors(robot_path):
    """Setup sensors for the humanoid robot"""
    sensors = IsaacSensors(robot_path)

    # Add head-mounted RGB-D camera
    sensors.add_rgb_camera(
        name="head_camera",
        position=[0, 0, 0.1],  # Position relative to head
        orientation=[0, 0, 0, 1]
    )

    # Add LiDAR to torso
    sensors.add_lidar(
        name="torso_lidar",
        position=[0, 0, 0.2],  # Position relative to torso
        orientation=[0, 0, 0, 1]
    )

    # Add IMU to torso
    sensors.add_imu(
        name="torso_imu",
        position=[0, 0, 0],  # Position relative to torso
        orientation=[0, 0, 0, 1]
    )

    return sensors

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# pbr_materials.py
def create_pbr_materials():
    """Create physically-based materials for realistic rendering"""

    # Robot body material (metallic)
    robot_body_material = {
        "albedo": [0.8, 0.8, 0.9],      # Base color
        "metallic": 0.8,                # Metallic property
        "roughness": 0.2,               # Surface roughness
        "specular": 0.5,                # Specular reflection
        "normal_scale": 1.0             # Normal map strength
    }

    # Rubber material for feet
    rubber_material = {
        "albedo": [0.2, 0.2, 0.2],      # Dark rubber color
        "metallic": 0.0,                # Non-metallic
        "roughness": 0.9,               # Very rough surface
        "specular": 0.1,                # Low specular
        "clearcoat": 0.3,               # Slight coating
        "clearcoat_roughness": 0.2
    }

    # Plastic material for face/hands
    plastic_material = {
        "albedo": [0.9, 0.7, 0.5],      # Skin-like color
        "metallic": 0.0,                # Non-metallic
        "roughness": 0.4,               # Medium roughness
        "subsurface": 0.1               # Slight subsurface scattering
    }

    return {
        "robot_body": robot_body_material,
        "rubber": rubber_material,
        "plastic": plastic_material
    }

def apply_advanced_materials(stage):
    """Apply advanced materials to objects in the stage"""
    materials = create_pbr_materials()

    # Apply materials to robot parts
    apply_material_to_prim(stage, "/World/HumanoidRobot/Body", materials["robot_body"])
    apply_material_to_prim(stage, "/World/HumanoidRobot/LeftFoot", materials["rubber"])
    apply_material_to_prim(stage, "/World/HumanoidRobot/RightFoot", materials["rubber"])
    apply_material_to_prim(stage, "/World/HumanoidRobot/Head", materials["plastic"])

def apply_material_to_prim(stage, prim_path, material_props):
    """Apply material properties to a USD prim"""
    # This would involve creating USD material nodes and connecting them
    # to the appropriate geometry
    pass

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# performance_optimization.py
class PerformanceOptimizer:
    def __init__(self, world):
        self.world = world
        self.lod_levels = ["high", "medium", "low", "proxy"]
        self.current_lod = "high"

    def adjust_simulation_lod(self, distance_to_camera):
        """Adjust simulation detail based on distance"""
        if distance_to_camera > 20:
            self.set_lod("proxy")
        elif distance_to_camera > 10:
            self.set_lod("low")
        elif distance_to_camera > 5:
            self.set_lod("medium")
        else:
            self.set_lod("high")

    def set_lod(self, level):
        """Set the level of detail for simulation"""
        if level == self.current_lod:
            return

        self.current_lod = level

        if level == "high":
            # Full physics, detailed rendering, all sensors active
            self.world.get_physics_context().set_simulation_dt(1.0/60.0)
            self.enable_all_sensors()
        elif level == "medium":
            # Reduced physics steps, less detailed rendering
            self.world.get_physics_context().set_simulation_dt(1.0/30.0)
            self.reduce_sensor_resolution()
        elif level == "low":
            # Simplified physics, basic rendering
            self.world.get_physics_context().set_simulation_dt(1.0/15.0)
            self.disable_complex_sensors()
        elif level == "proxy":
            # Simplified representation, minimal physics
            self.world.get_physics_context().set_simulation_dt(1.0/10.0)
            self.use_proxy_models()

    def enable_all_sensors(self):
        """Enable all sensor simulations"""
        pass

    def reduce_sensor_resolution(self):
        """Reduce sensor resolution for performance"""
        pass

    def disable_complex_sensors(self):
        """Disable complex sensors"""
        pass

    def use_proxy_models(self):
        """Use simplified proxy models"""
        pass

def setup_performance_monitoring():
    """Setup performance monitoring for Isaac Sim"""
    import carb
    import omni.kit.app as app

    # Enable performance monitoring
    carb.settings.get_settings().set("/app/window/dpiScale", 1.0)
    carb.settings.get_settings().set("/persistent/isaac/app/window/profiling", True)

    # Set rendering quality settings
    carb.settings.get_settings().set("/rtx-defaults/quality", 4)  # Maximum quality
    carb.settings.get_settings().set("/rtx-defaults/resolution/width", 1920)
    carb.settings.get_settings().set("/rtx-defaults/resolution/height", 1080)

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