diff --git a/examples/13_use_trossen_ai_mobile.md b/examples/13_use_trossen_ai_mobile.md
index 45bdbcea..acd55cec 100644
--- a/examples/13_use_trossen_ai_mobile.md
+++ b/examples/13_use_trossen_ai_mobile.md
@@ -60,11 +60,11 @@ python lerobot/scripts/control_robot.py \
   --robot.max_relative_target=null \
   --control.type=teleoperate
 ```
-By adding `--robot.force_feedback_gain=0.1`, we override the default value for `force_feedback_gain` defined in [`TrossenAIBimanualRobot`](lerobot/common/robot_devices/robots/configs.py). This enables **force feedback** from the follower arm to the leader arm — meaning the user can **feel contact forces** when the robot interacts with external objects (e.g., gripping or bumping into something). A typical starting value is `0.1` for a responsive feel. You can disable this behavior entirely by setting `--robot.force_feedback_gain=0.0` in the command line:
+By adding `--robot.force_feedback_gain=0.1`, we override the default value for `force_feedback_gain` defined in [`TrossenAIMobileRobot`](lerobot/common/robot_devices/robots/configs.py). This enables **force feedback** from the follower arm to the leader arm — meaning the user can **feel contact forces** when the robot interacts with external objects (e.g., gripping or bumping into something). A typical starting value is `0.1` for a responsive feel. You can disable this behavior entirely by setting `--robot.force_feedback_gain=0.0` in the command line:
 
 ```bash
 python lerobot/scripts/control_robot.py \
-  --robot.type=trossen_ai_stationary \
+  --robot.type=trossen_ai_mobile \
   --robot.max_relative_target=null \
   --robot.force_feedback_gain=0.1 \
   --control.type=teleoperate
@@ -110,6 +110,19 @@ python lerobot/scripts/control_robot.py \
   --control.display_cameras=false
 ```
 
+The **Slate base** works in two modes:
+- **Torque OFF** (default): You can push the base around manually.
+- **Torque ON**: Enables the motors so you can control the base using the **Slate remote controller**.
+
+To enable torque-on mode during recording, add the following argument:
+```bash
+--robot.enable_motor_torque=true
+```
+
+For more information about the Slate remote controller, refer to the official documentation:
+[Slate RC Controller Guide](https://docs.trossenrobotics.com/slate_docs/operation/rc_controller.html)
+
+
 ## Visualize a dataset
 
 If you uploaded your dataset to the hub with `--control.push_to_hub=true`, you can [visualize your dataset online](https://huggingface.co/spaces/lerobot/visualize_dataset) by copy pasting your repo id given by:
@@ -138,6 +151,8 @@ python lerobot/scripts/control_robot.py \
   --robot.enable_motor_torque=true
 ```
 
+Note: For replaying an episode, you need to turn on motor torque using ``--robot.enable_motor_torque=true``, so that the robot can actively follow the trajectory instead of remaining in a passive (torque-off) state.
+
 ## Train a policy
 
 To train a policy to control your robot, use the [`python lerobot/scripts/train.py`](../lerobot/scripts/train.py) script. A few arguments are required. Here is an example command:
@@ -178,9 +193,13 @@ python lerobot/scripts/control_robot.py \
   --control.num_episodes=10 \
   --control.push_to_hub=true \
   --control.policy.path=outputs/train/act_trossen_ai_mobile_test/checkpoints/last/pretrained_model \
-  --control.num_image_writer_processes=1
+  --control.num_image_writer_processes=1 \
+  --robot.enable_motor_torque=true
 ```
 
+Note: For evaluation, you need to turn on motor torque using ``--robot.enable_motor_torque=true``, so that the robot can actively follow the trajectory instead of remaining in a passive (torque-off) state.
+
+
 As you can see, it's almost the same command as previously used to record your training dataset. Two things changed:
 1. There is an additional `--control.policy.path` argument which indicates the path to your policy checkpoint with  (e.g. `outputs/train/eval_act_trossen_ai_mobile_test/checkpoints/last/pretrained_model`). You can also use the model repository if you uploaded a model checkpoint to the hub (e.g. `${HF_USER}/act_trossen_ai_mobile_test`).
 2. The name of dataset begins by `eval` to reflect that you are running inference (e.g. `${HF_USER}/eval_act_trossen_ai_mobile_test`).