diff --git a/brax/envs/humanoid.py b/brax/envs/humanoid.py
index e1ba0ed5..0e2600c1 100644
--- a/brax/envs/humanoid.py
+++ b/brax/envs/humanoid.py
@@ -255,6 +255,12 @@ def reset(self, rng: jax.Array) -> State:
 
   def step(self, state: State, action: jax.Array) -> State:
     """Runs one timestep of the environment's dynamics."""
+    
+    # Scale action from [-1,1] to actuator limits
+    action_min = self.sys.actuator.ctrl_range[:, 0]
+    action_max = self.sys.actuator.ctrl_range[:, 1]
+    action = (action + 1) * (action_max - action_min) * 0.5 + action_min
+    
     pipeline_state0 = state.pipeline_state
     pipeline_state = self.pipeline_step(pipeline_state0, action)
 
diff --git a/brax/envs/humanoidstandup.py b/brax/envs/humanoidstandup.py
index 777e863e..5fd28dc9 100644
--- a/brax/envs/humanoidstandup.py
+++ b/brax/envs/humanoidstandup.py
@@ -219,6 +219,12 @@ def reset(self, rng: jax.Array) -> State:
 
   def step(self, state: State, action: jax.Array) -> State:
     """Runs one timestep of the environment's dynamics."""
+    
+    # Scale action from [-1,1] to actuator limits
+    action_min = self.sys.actuator.ctrl_range[:, 0]
+    action_max = self.sys.actuator.ctrl_range[:, 1]
+    action = (action + 1) * (action_max - action_min) * 0.5 + action_min
+    
     pipeline_state = self.pipeline_step(state.pipeline_state, action)
 
     pos_after = pipeline_state.x.pos[0, 2]  # z coordinate of torso
diff --git a/brax/envs/inverted_double_pendulum.py b/brax/envs/inverted_double_pendulum.py
index a546512f..8916fd21 100644
--- a/brax/envs/inverted_double_pendulum.py
+++ b/brax/envs/inverted_double_pendulum.py
@@ -46,14 +46,14 @@ class InvertedDoublePendulum(PipelineEnv):
 
   The agent take a 1-element vector for actions.
 
-  The action space is a continuous `(action)` in `[-3, 3]`, where `action`
+  The action space is a continuous `(action)` in `[-1, 1]`, where `action`
   represents the numerical force applied to the cart (with magnitude
   representing the amount of force and sign representing the direction)
 
   | Num | Action                    | Control Min | Control Max | Name (in
   corresponding config) | Joint | Unit      |
   |-----|---------------------------|-------------|-------------|--------------------------------|-------|-----------|
-  | 0   | Force applied on the cart | -3          | 3           | slider
+  | 0   | Force applied on the cart | -1          | 1           | slider
   | slide | Force (N) |
 
   ### Observation Space
diff --git a/brax/envs/inverted_pendulum.py b/brax/envs/inverted_pendulum.py
index 30692177..58c396cf 100644
--- a/brax/envs/inverted_pendulum.py
+++ b/brax/envs/inverted_pendulum.py
@@ -129,6 +129,12 @@ def reset(self, rng: jax.Array) -> State:
 
   def step(self, state: State, action: jax.Array) -> State:
     """Run one timestep of the environment's dynamics."""
+
+    # Scale action from [-1,1] to actuator limits
+    action_min = self.sys.actuator.ctrl_range[:, 0]
+    action_max = self.sys.actuator.ctrl_range[:, 1]
+    action = (action + 1) * (action_max - action_min) * 0.5 + action_min
+    
     pipeline_state = self.pipeline_step(state.pipeline_state, action)
     obs = self._get_obs(pipeline_state)
     reward = 1.0
diff --git a/brax/envs/pusher.py b/brax/envs/pusher.py
index d30e3511..5d3db9dd 100644
--- a/brax/envs/pusher.py
+++ b/brax/envs/pusher.py
@@ -193,6 +193,14 @@ def reset(self, rng: jax.Array) -> State:
     return State(pipeline_state, obs, reward, done, metrics)
 
   def step(self, state: State, action: jax.Array) -> State:
+    
+    # Scale action from [-1,1] to actuator limits
+    action_min = self.sys.actuator.ctrl_range[:, 0]
+    action_max = self.sys.actuator.ctrl_range[:, 1]
+    action = (action + 1) * (action_max - action_min) * 0.5 + action_min
+    
+    pipeline_state = self.pipeline_step(state.pipeline_state, action)
+    
     assert state.pipeline_state is not None
     x_i = state.pipeline_state.x.vmap().do(
         base.Transform.create(pos=self.sys.link.inertia.transform.pos)
@@ -205,8 +213,6 @@ def step(self, state: State, action: jax.Array) -> State:
     reward_ctrl = -jp.square(action).sum()
     reward = reward_dist + 0.1 * reward_ctrl + 0.5 * reward_near
 
-    pipeline_state = self.pipeline_step(state.pipeline_state, action)
-
     obs = self._get_obs(pipeline_state)
     state.metrics.update(
         reward_near=reward_near,