diff --git a/tutorials/obstacle_detector.py b/tutorials/obstacle_detector.py
new file mode 100755
index 0000000..5a6d01c
--- /dev/null
+++ b/tutorials/obstacle_detector.py
@@ -0,0 +1,94 @@
+#!/usr/bin/env python3
+"""
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+Monash Nova Rover Team
+
+Subscriber node that finds the average Z value of
+ points with 0.3 < Z < 3.0, -0.15 < X < 0.15, and
+ -0.15 < Y < 0.15, then publishes this average to 
+ obstacle_proximity as a float. Uses floatify_bytes
+ to convert byte array to little endian float.
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+NODE: Obstacle_Subscriber
+TOPICS:
+  - /D435/depth/color/points [sensor_msgs.msg.PointCloud2]
+SERVICES:
+  - None
+ACTIONS: None
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+PACKAGE: 	induction_task
+AUTHOR(S):	Max Tory
+CREATION:       20/09/2021
+EDITED:		21/09/2021
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+"""
+import struct
+import rclpy
+from rclpy.node import Node
+from sensor_msgs.msg import PointCloud2
+from std_msgs.msg import Float32
+from std_msgs.msg import String
+from typing import List
+from time import perf_counter as time
+
+
+class Obstacle_Subscriber(Node):
+    def __init__(self):
+        super().__init__('obstacle_subscriber')
+        self.subscription = self.create_subscription(PointCloud2, '/D435/depth/color/points', self.parse_points, 10)
+        # for logging results
+        self.publisher = self.create_publisher(String, 'obstacle_proximity', 10)
+        self.counter = 0
+
+    def parse_points(self, msg: PointCloud2):
+        output_info = String()
+        # timer to check performance
+        start_time = time()
+        self.counter += 1
+
+        z_sum = 0
+        num_points = 0
+        data = msg.data
+        skip_amount = 1 # in case we want to skip some points for efficiency
+        for i in range(0, len(data), skip_amount * 20):
+            x = floatify_bytes(data[i : i + 4])
+            y = floatify_bytes(data[i + 4 : i + 8])
+            z = floatify_bytes(data[i + 8 : i + 12])
+        
+            if (-0.15 < x < 0.15) and (-0.15 < y < 0.15) and (0.3 < z < 3.0):
+                # We consider this point in our average
+                z_sum += z
+                num_points += 1
+
+        avg = z_sum/num_points
+        time_elapsed = time() - start_time
+        output_info.data = str(self.counter) + ": Average z: " + str(avg) + " computed in " + str(round(time_elapsed, 4)) + " s."
+        
+        self.publisher.publish(output_info)
+
+
+def floatify_bytes(bytes_list: List[int]):
+    """
+    :param list of 4 bytes as decimal numbers
+    :return: float representation of bytes in little endian format
+    """
+    decimal = 0
+    # combine 4 bytes into a single decimal integer
+    for i in range(4):
+        decimal <<= 8        # bit shifting previous byte over by 8 
+        decimal += bytes_list[i]
+    # store as unsigned int, then interpret as if it were a little endian float
+    return struct.unpack('<f', struct.pack('>I', decimal))[0]
+
+def main():
+    rclpy.init(args = None)
+    obstacle_subscriber = Obstacle_Subscriber()
+    rclpy.spin(obstacle_subscriber)
+
+if __name__ == "__main__":
+    main()
+
+
+
+
+