diff --git a/docs/source/overview/gym/event_functors.md b/docs/source/overview/gym/event_functors.md
index f1dfdcc7..cd101cc1 100644
--- a/docs/source/overview/gym/event_functors.md
+++ b/docs/source/overview/gym/event_functors.md
@@ -31,6 +31,8 @@ This page lists all available event functors that can be used with the Event Man
   - Randomize textures, base colors, and material properties (metallic, roughness, IOR). Implemented as a Functor class. Supports both RigidObject and Articulation assets.
 * - ``randomize_light``
   - Vary light position, color, and intensity within specified ranges.
+* - ``randomize_emission_light``
+  - Randomize global emission light color and intensity. Applies the same emission light properties across all environments.
 * - ``randomize_camera_extrinsics``
   - Randomize camera poses for viewpoint diversity. Supports both attach mode (pos/euler perturbation) and look_at mode (eye/target/up perturbation).
 * - ``randomize_camera_intrinsics``
diff --git a/embodichain/lab/gym/envs/embodied_env.py b/embodichain/lab/gym/envs/embodied_env.py
index ca974f92..9eda098d 100644
--- a/embodichain/lab/gym/envs/embodied_env.py
+++ b/embodichain/lab/gym/envs/embodied_env.py
@@ -64,7 +64,7 @@ class EnvLightCfg:
         direct: List[LightCfg] = []
 
         # TODO: support more types of indirect light in the future.
-        # indirect: Dict[str, Any] | None = None
+        indirect: dict[str, Any] | None = None
 
     robot: RobotCfg = MISSING
 
@@ -498,9 +498,15 @@ def _setup_sensors(self, **kwargs) -> Dict[str, BaseSensor]:
 
     def _setup_lights(self) -> None:
         """Setup the lights in the environment."""
+        # Set direct lights.
         for cfg in self.cfg.light.direct:
             self.sim.add_light(cfg=cfg)
 
+        # Set indirect lights.
+        if self.cfg.light.indirect is not None:
+            if "emission_light" in self.cfg.light.indirect:
+                self.sim.set_emission_light(**self.cfg.light.indirect["emission_light"])
+
     def _setup_background(self) -> None:
         """Setup the static rigid objects in the environment."""
         for cfg in self.cfg.background:
diff --git a/embodichain/lab/gym/envs/managers/randomization/visual.py b/embodichain/lab/gym/envs/managers/randomization/visual.py
index a1b1a978..66d3d6fb 100644
--- a/embodichain/lab/gym/envs/managers/randomization/visual.py
+++ b/embodichain/lab/gym/envs/managers/randomization/visual.py
@@ -20,6 +20,8 @@
 import os
 import random
 import copy
+import numpy as np
+
 from typing import TYPE_CHECKING, Literal, Union, Dict
 
 from embodichain.lab.sim.objects import (
@@ -52,6 +54,7 @@
 __all__ = [
     "randomize_camera_extrinsics",
     "randomize_light",
+    "randomize_emission_light",
     "randomize_camera_intrinsics",
     "set_rigid_object_visual_material",
     "set_rigid_object_group_visual_material",
@@ -342,6 +345,50 @@ def randomize_light(
         light.set_intensity(new_intensity, env_ids=env_ids)
 
 
+def randomize_emission_light(
+    env: EmbodiedEnv,
+    env_ids: Union[torch.Tensor, None],
+    color_range: tuple[list[float], list[float]] | None = None,
+    intensity_range: tuple[float, float] | None = None,
+) -> None:
+    """Randomize emission light properties by adding, scaling, or setting random values.
+
+    This function allows randomizing emission light properties in the scene. The function samples random values from the
+    given distribution parameters and adds, scales, or sets the values into the physics simulation based on the
+    operation.
+
+    The distribution parameters are lists of two elements each, representing the lower and upper bounds of the
+    distribution for the r, g, b components of the light color and intensity. The function samples random values for each
+    component independently.
+
+    .. attention::
+        This function applied the same emission light properties for all the environments.
+
+        color_range is the absolute r, g, b value set on the emission light.
+        intensity_range is the absolute intensity value set on the emission light.
+    """
+
+    color = None
+    if color_range:
+        color = torch.zeros((1, 3), dtype=torch.float32)
+        random_value = sample_uniform(
+            lower=torch.tensor(color_range[0]),
+            upper=torch.tensor(color_range[1]),
+            size=color.shape,
+        )
+        color += random_value
+
+    intensity = None
+    if intensity_range:
+        intensity = np.random.uniform(intensity_range[0], intensity_range[1])
+
+    if isinstance(color, torch.Tensor):
+        color_arg = color.squeeze(0).tolist()
+    else:
+        color_arg = None
+    env.sim.set_emission_light(color=color_arg, intensity=intensity)
+
+
 def randomize_camera_intrinsics(
     env: EmbodiedEnv,
     env_ids: Union[torch.Tensor, None],
diff --git a/embodichain/lab/gym/utils/gym_utils.py b/embodichain/lab/gym/utils/gym_utils.py
index d8b4427f..e9823d6e 100644
--- a/embodichain/lab/gym/utils/gym_utils.py
+++ b/embodichain/lab/gym/utils/gym_utils.py
@@ -430,6 +430,7 @@ class ComponentCfg:
         env_cfg.light.direct = [
             LightCfg.from_dict(l) for l in config["light"].get("direct", [])
         ]
+        env_cfg.light.indirect = config["light"].get("indirect", None)
 
     # parser background objects config
     if "background" in config: