diff --git a/Readme.md b/Readme.md
index e97d34d..9a9c54f 100644
--- a/Readme.md
+++ b/Readme.md
@@ -2,7 +2,7 @@
 ### 1. Requirements
 python version 3.9 or higher
 ```bash
-python3 -v
+python3 --version
 ```
 ### 2. Create virtual environments and install libs
 ```bash
@@ -35,14 +35,14 @@ VERTICAL_NUM_OF_FIELDS = 3
 HORIZONTAL_NUM_OF_FIELDS = 3
 ```
 \
-####4.1 Save generated map:
+#### 4.1 Save generated map:
 ```bash
 python main.py --save-map
 ```
 Map will be saved in maps directory. 
 Generated filename: map-uuid
 
-####4.2 Load map
+#### 4.2 Load map
 ```bash
 python main.py --load-map=name_of_map
 ```
diff --git a/app/neural_network.py b/app/neural_network.py
index f2e517e..d3db826 100644
--- a/app/neural_network.py
+++ b/app/neural_network.py
@@ -28,9 +28,9 @@ class NeuralNetwork:
         self.input_shape = (self.img_width, self.img_height, self.img_num_channels)
 
         # labels
-        self.labels = ["cabbage", "carrot", "corn", "lettuce", "paprika", "potato", "sunflower" , "tomato"]
+        self.labels = ["cabbage", "carrot", "corn", "lettuce", "paprika", "potato", "sunflower", "tomato"]
 
-    def init_model(self):
+    def init_model(self) -> None:
         if not self.model_dir_is_empty():
             # Load the model
             self.model = load_model(
@@ -60,9 +60,9 @@ class NeuralNetwork:
                 shuffle=False)
 
         # Display a model summary
-        #self.model.summary()
+        # self.model.summary()
 
-    def load_images(self):
+    def load_images(self) -> None:
         # Create a generator
         self.train_datagen = ImageDataGenerator(
             rescale=1. / 255
diff --git a/app/tractor.py b/app/tractor.py
index a5f6442..9e14138 100644
--- a/app/tractor.py
+++ b/app/tractor.py
@@ -210,7 +210,7 @@ class Tractor(BaseField):
             time.sleep(TIME_OF_MOVING)
         is_running.clear()
 
-    def move_or_rotate(self, movement: str):
+    def move_or_rotate(self, movement: str) -> None:
         print(f"Move {movement}")
         if movement == M_GO_FORWARD:
             self.move()
@@ -267,14 +267,25 @@ class Tractor(BaseField):
         board.get_fields()[x][y] = obj()
         return obj()
 
-    def harvest_checked_fields_handler(self, is_running: threading.Event):
+    def harvest_checked_fields_handler(self, is_running: threading.Event) -> None:
         thread = threading.Thread(target=self.harvest_checked_fields, args=(is_running,), daemon=True)
         thread.start()
 
-    def harvest_checked_fields(self, is_running: threading.Event):
-        moves = [M_GO_FORWARD, M_ROTATE_LEFT, M_ROTATE_RIGHT]
-        distribution=[0.6,0.2,0.2]
+    def go_forward_is_legal_move(self) -> bool:
+        flag = False
+        if (self.__direction == D_EAST and self.__pos_y - self.__move >= 0) or \
+                (self.__direction == D_NORTH and self.__pos_y + self.__move + FIELD_SIZE <= HEIGHT) or \
+                (self.__direction == D_WEST and self.__pos_x - self.__move >= 0) or \
+                (self.__direction == D_SOUTH and self.__pos_x + self.__move + FIELD_SIZE <= WIDTH):
+            flag = True
+
+        return flag
+
+    def harvest_checked_fields(self, is_running: threading.Event) -> None:
         while True:
+            moves = [M_GO_FORWARD, M_ROTATE_LEFT, M_ROTATE_RIGHT]
+            distribution = [0.6, 0.2, 0.2]
+
             field = self.get_field_from_board()
 
             self.__neural_network = NeuralNetwork()
@@ -283,8 +294,12 @@ class Tractor(BaseField):
             if prediction.capitalize() in CROPS:
                 self.harvest()
                 break
-            chosen_move = random.choices(moves,distribution)
 
+            if not self.go_forward_is_legal_move():
+                moves = moves[1:]
+                distribution = distribution[1:]
+
+            chosen_move = random.choices(moves, distribution)
             self.move_or_rotate(chosen_move[0])
             time.sleep(1)