diff --git a/control/smart_mpc_trajectory_follower/README.md b/control/smart_mpc_trajectory_follower/README.md
index f2e97992f54e2..66d2e03c2cfe0 100644
--- a/control/smart_mpc_trajectory_follower/README.md
+++ b/control/smart_mpc_trajectory_follower/README.md
@@ -255,7 +255,7 @@ In `run_sim.py`, the following parameters can be set:
| Parameter | Type | Description |
| ------------------------- | ---- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| USE_TRAINED_MODEL_DIFF | bool | Whether the derivative of the trained model is reflected in the control |
-| DATA_COLLECTION_MODE | str | Which method will be used to collect the training data
"ff": Straight line driving with feed-forward input
"pp": Figure eight driving with pure pursuit control
"mpc": Slalom driving with mpc |
+| DATA_COLLECTION_MODE | str | Which method will be used to collect the training data
"ff": Straight line driving with feed-forward input
"pp": Figure eight driving with pure pursuit control
"mpc": Slalom driving with mpc |
| USE_POLYNOMIAL_REGRESSION | bool | Whether to perform polynomial regression before NN |
| USE_SELECTED_POLYNOMIAL | bool | When USE_POLYNOMIAL_REGRESSION is True, perform polynomial regression using only some preselected polynomials.
The choice of polynomials is intended to be able to absorb the contribution of some parameter shifts based on the nominal model of the vehicle. |
| FORCE_NN_MODEL_TO_ZERO | bool | Whether to force the NN model to zero (i.e., erase the contribution of the NN model).
When USE_POLYNOMIAL_REGRESSION is True, setting FORCE_MODEL_TO_ZERO to True allows the control to reflect the results of polynomial regression only, without using NN models. |
@@ -295,18 +295,18 @@ ros2 topic pub /pympc_reload_mpc_param_trigger std_msgs/msg/String "data: ''" --
The main parameters among the control parameters are as follows.
-### `mpc_param.yaml`:
+### `mpc_param.yaml`
| Parameter | Type | Description |
| ------------------------------------ | ----------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
-| mpc_parameter:system:mode | str | control mode
"ilqr": iLQR mode
"mppi": MPPI mode
"mppi_ilqr": the initial value of iLQR is given by the MPPI solution. |
+| mpc_parameter:system:mode | str | control mode
"ilqr": iLQR mode
"mppi": MPPI mode
"mppi_ilqr": the initial value of iLQR is given by the MPPI solution. |
| mpc_parameter:cost_parameters:Q | list[float] | Stage cost for states.
List of length 8, in order: straight deviation, lateral deviation, velocity deviation, yaw angle deviation, acceleration deviation, steer deviation, acceleration input deviation, steer input deviation cost weights. |
| mpc_parameter:cost_parameters:Q_c | list[float] | Cost in the horizon corresponding to the following timing_Q_c for the states.
The correspondence of the components of the list is the same as for Q. |
| mpc_parameter:cost_parameters:Q_f | list[float] | Termination cost for the states.
The correspondence of the components of the list is the same as for Q. |
| mpc_parameter:cost_parameters:R | list[float] | A list of length 2 where R[0] is weight of cost for the change rate of acceleration input value and R[1] is weight of cost for the change rate of steer input value. |
| mpc_parameter:mpc_setting:timing_Q_c | list[int] | Horizon numbers such that the stage cost for the states is set to Q_c. |
-### `trained_model_param.yaml`:
+### `trained_model_param.yaml`
| Parameter | Type | Description |
| ------------------------------------------------------------------ | ---- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |