diff --git a/vmas/scenarios/discovery.py b/vmas/scenarios/discovery.py
index ef57735c..c3934503 100644
--- a/vmas/scenarios/discovery.py
+++ b/vmas/scenarios/discovery.py
@@ -28,7 +28,11 @@ def make_world(self, batch_dim: int, device: torch.device, **kwargs):
         self._min_dist_between_entities = kwargs.pop("min_dist_between_entities", 0.2)
         self._lidar_range = kwargs.pop("lidar_range", 0.35)
         self._covering_range = kwargs.pop("covering_range", 0.25)
+
         self.use_agent_lidar = kwargs.pop("use_agent_lidar", False)
+        self.n_lidar_rays_entities = kwargs.pop("n_lidar_rays_entities", 15)
+        self.n_lidar_rays_agents = kwargs.pop("n_lidar_rays_agents", 12)
+
         self._agents_per_target = kwargs.pop("agents_per_target", 2)
         self.targets_respawn = kwargs.pop("targets_respawn", True)
         self.shared_reward = kwargs.pop("shared_reward", False)
@@ -74,7 +78,7 @@ def make_world(self, batch_dim: int, device: torch.device, **kwargs):
                     [
                         Lidar(
                             world,
-                            n_rays=15,
+                            n_rays=self.n_lidar_rays_entities,
                             max_range=self._lidar_range,
                             entity_filter=entity_filter_targets,
                             render_color=Color.GREEN,
@@ -86,7 +90,7 @@ def make_world(self, batch_dim: int, device: torch.device, **kwargs):
                                 world,
                                 angle_start=0.05,
                                 angle_end=2 * torch.pi + 0.05,
-                                n_rays=12,
+                                n_rays=self.n_lidar_rays_agents,
                                 max_range=self._lidar_range,
                                 entity_filter=entity_filter_agents,
                                 render_color=Color.BLUE,
diff --git a/vmas/scenarios/flocking.py b/vmas/scenarios/flocking.py
index 713b21e0..c15d3f24 100644
--- a/vmas/scenarios/flocking.py
+++ b/vmas/scenarios/flocking.py
@@ -20,6 +20,8 @@ def make_world(self, batch_dim: int, device: torch.device, **kwargs):
         n_obstacles = kwargs.pop("n_obstacles", 5)
         self._min_dist_between_entities = kwargs.pop("min_dist_between_entities", 0.15)
 
+        self.n_lidar_rays = kwargs.pop("n_lidar_rays", 12)
+
         self.collision_reward = kwargs.pop("collision_reward", -0.1)
         self.dist_shaping_factor = kwargs.pop("dist_shaping_factor", 1)
         ScenarioUtils.check_kwargs_consumed(kwargs)
@@ -51,7 +53,7 @@ def make_world(self, batch_dim: int, device: torch.device, **kwargs):
                 sensors=[
                     Lidar(
                         world,
-                        n_rays=12,
+                        n_rays=self.n_lidar_rays,
                         max_range=0.2,
                         entity_filter=goal_entity_filter,
                     )
diff --git a/vmas/scenarios/navigation.py b/vmas/scenarios/navigation.py
index 9943215c..cbef4234 100644
--- a/vmas/scenarios/navigation.py
+++ b/vmas/scenarios/navigation.py
@@ -41,6 +41,7 @@ def make_world(self, batch_dim: int, device: torch.device, **kwargs):
         self.lidar_range = kwargs.pop("lidar_range", 0.35)
         self.agent_radius = kwargs.pop("agent_radius", 0.1)
         self.comms_range = kwargs.pop("comms_range", 0)
+        self.n_lidar_rays = kwargs.pop("n_lidar_rays", 12)
 
         self.shared_rew = kwargs.pop("shared_rew", True)
         self.pos_shaping_factor = kwargs.pop("pos_shaping_factor", 1)
@@ -115,7 +116,7 @@ def make_world(self, batch_dim: int, device: torch.device, **kwargs):
                     [
                         Lidar(
                             world,
-                            n_rays=12,
+                            n_rays=self.n_lidar_rays,
                             max_range=self.lidar_range,
                             entity_filter=entity_filter_agents,
                         ),