Tanmay Shah

modules/bootcamp/decision_simple_waypoint.py

@@ -13,7 +13,6 @@
 from .. import location
 from ..private.decision import base_decision
 
-
 # Disable for bootcamp use
 # No enable
 # pylint: disable=duplicate-code,unused-argument
@@ -37,7 +36,8 @@ def __init__(self, waypoint: location.Location, acceptance_radius: float) -> Non
         # ↓ BOOTCAMPERS MODIFY BELOW THIS COMMENT ↓
         # ============
 
-        # Add your own
+        self.waypoint_found = False
+        self.landing_pad_found = False
 
         # ============
         # ↑ BOOTCAMPERS MODIFY ABOVE THIS COMMENT ↑
@@ -48,7 +48,6 @@ def run(
     ) -> commands.Command:
         """
         Make the drone fly to the waypoint.
-
         You are allowed to create as many helper methods as you want,
         as long as you do not change the __init__() and run() signatures.
 
@@ -61,14 +60,31 @@ def run(
             put_output(command)
         ```
         """
-        # Default command
-        command = commands.Command.create_null_command()
 
         # ============
         # ↓ BOOTCAMPERS MODIFY BELOW THIS COMMENT ↓
         # ============
 
-        # Do something based on the report and the state of this class...
+        status = report.status
+
+        current_position = report.position
+        diff_distance_x = self.waypoint.location_x - current_position.location_x
+        diff_distance_y = self.waypoint.location_y - current_position.location_y
+        distance_net_squared = (diff_distance_x**2) + (diff_distance_y**2)
+
+        if status == drone_status.DroneStatus.HALTED:
+            if distance_net_squared <= self.acceptance_radius**2:  # squaring the acceptance radius
+                command = commands.Command.create_land_command()
+                print("Drone is landing!")
+
+            else:
+                command = commands.Command.create_set_relative_destination_command(
+                    diff_distance_x, diff_distance_y
+                )
+                print("Going to waypoint!")
+
+        else:
+            command = commands.Command.create_null_command()
 
         # ============
         # ↑ BOOTCAMPERS MODIFY ABOVE THIS COMMENT ↑

modules/bootcamp/decision_waypoint_landing_pads.py

@@ -1,7 +1,7 @@
 """
 BOOTCAMPERS TO COMPLETE.
 
-Travel to designated waypoint and then land at a nearby landing pad.
+Travel to the designated waypoint and then land at a nearby landing pad.
 """
 
 from .. import commands
@@ -21,7 +21,7 @@
 
 class DecisionWaypointLandingPads(base_decision.BaseDecision):
     """
-    Travel to the designed waypoint and then land at the nearest landing pad.
+    Travel to the designated waypoint and then land at the nearest landing pad.
     """
 
     def __init__(self, waypoint: location.Location, acceptance_radius: float) -> None:
@@ -33,25 +33,25 @@ def __init__(self, waypoint: location.Location, acceptance_radius: float) -> Non
 
         self.acceptance_radius = acceptance_radius
 
-        # ============
-        # ↓ BOOTCAMPERS MODIFY BELOW THIS COMMENT ↓
-        # ============
+        self.halt_at_initialization = True
+        self.has_reached_waypoint = False
+        self.closest_landing_pad = None
 
-        # Add your own
-
-        # ============
-        # ↑ BOOTCAMPERS MODIFY ABOVE THIS COMMENT ↑
-        # ============
+    def squared_distance(self, point1: location.Location, point2: location.Location) -> float:
+        """
+        Calculate the squared distance between two locations.
+        """
+        diff_distance_x = point1.location_x - point2.location_x
+        diff_distance_y = point1.location_y - point2.location_y
+        distance_net_squared = (diff_distance_x**2) + (diff_distance_y**2)
+        return distance_net_squared
 
     def run(
         self, report: drone_report.DroneReport, landing_pad_locations: "list[location.Location]"
     ) -> commands.Command:
         """
         Make the drone fly to the waypoint and then land at the nearest landing pad.
 
-        You are allowed to create as many helper methods as you want,
-        as long as you do not change the __init__() and run() signatures.
-
         This method will be called in an infinite loop, something like this:
 
         ```py
@@ -61,17 +61,55 @@ def run(
             put_output(command)
         ```
         """
-        # Default command
         command = commands.Command.create_null_command()
 
-        # ============
-        # ↓ BOOTCAMPERS MODIFY BELOW THIS COMMENT ↓
-        # ============
-
-        # Do something based on the report and the state of this class...
-
-        # ============
-        # ↑ BOOTCAMPERS MODIFY ABOVE THIS COMMENT ↑
-        # ============
-
+        # get  current position
+        current_position = report.position
+        distance_net_squared = self.squared_distance(self.waypoint, current_position)
+
+        if report.status == drone_status.DroneStatus.HALTED:
+            # check if at the waypoint
+            if not self.has_reached_waypoint and distance_net_squared <= self.acceptance_radius**2:
+                command = commands.Command.create_land_command()
+                print("Drone is landing at the waypoint!")
+                self.has_reached_waypoint = True
+
+            elif not self.has_reached_waypoint:
+                diff_distance_x = self.waypoint.location_x - current_position.location_x
+                diff_distance_y = self.waypoint.location_y - current_position.location_y
+                command = commands.Command.create_set_relative_destination_command(
+                    diff_distance_x, diff_distance_y
+                )
+                print("Going to waypoint!")
+                self.has_reached_waypoint = False
+
+            # find the closest landing pad
+            if self.has_reached_waypoint and not self.closest_landing_pad:
+                closest_distance_squared = float("inf")  # infinity
+
+                for landing_pad in landing_pad_locations:
+                    distance_from_waypoint_squared = self.squared_distance(
+                        landing_pad, self.waypoint
+                    )
+
+                    # update  closest_landing_pad
+                    if distance_from_waypoint_squared < closest_distance_squared:
+                        closest_distance_squared = distance_from_waypoint_squared
+                        self.closest_landing_pad = landing_pad
+
+                # EGDE CASE: landing pad is on the waypoint
+                if closest_distance_squared == 0:
+                    command = commands.Command.create_land_command()
+                    print("Drone is landing directly on the waypoint!")
+                else:
+                    diff_distance_x = (
+                        self.closest_landing_pad.location_x - current_position.location_x
+                    )
+                    diff_distance_y = (
+                        self.closest_landing_pad.location_y - current_position.location_y
+                    )
+                    command = commands.Command.create_set_relative_destination_command(
+                        diff_distance_x, diff_distance_y
+                    )
+                    print("Moving to closest landing pad!")
         return command

modules/bootcamp/detect_landing_pad.py

@@ -19,8 +19,7 @@
 # Bootcampers remove the following lines:
 # Allow linters and formatters to pass for bootcamp maintainers
 # No enable
-# pylint: disable=unused-argument,unused-private-member,unused-variable
-# ============
+# # ============
 # ↑ BOOTCAMPERS MODIFY ABOVE THIS COMMENT ↑
 # ============
 
@@ -94,35 +93,38 @@ def run(self, image: np.ndarray) -> "tuple[list[bounding_box.BoundingBox], np.nd
 
         # Use the model's predict() method to run inference
         # Parameters of interest:
-        # * source
-        # * conf
-        # * device
+        # * source: image
+        # * conf: 0.7 as outlined by the bootcamp
+        # * device:
         # * verbose
-        predictions = ...
+        predictions = self.__model.predict(image, conf=0.7, device=self.__DEVICE, verbose=False)
 
-        # Get the Result object
-        prediction = ...
+        # Get the Result object: need to loop through the predictions
+        prediction = predictions[0]
 
         # Plot the annotated image from the Result object
-        # Include the confidence value
-        image_annotated = ...
+        # Include the confidence value --> defaulted to be true anyways
+        image_annotated = prediction.plot()
 
         # Get the xyxy boxes list from the Boxes object in the Result object
-        boxes_xyxy = ...
+        boxes_xyxy = prediction.boxes.xyxy
+        # boxes.xyxyn not needed
 
         # Detach the xyxy boxes to make a copy,
         # move the copy into CPU space,
         # and convert to a numpy array
-        boxes_cpu = ...
+        boxes_cpu = boxes_xyxy.detach().cpu().numpy()
 
         # Loop over the boxes list and create a list of bounding boxes
         bounding_boxes = []
-        # Hint: .shape gets the dimensions of the numpy array
-        # for i in range(0, ...):
-        #     # Create BoundingBox object and append to list
-        #     result, box = ...
 
-        return [], image_annotated
+        for i in range(0, boxes_cpu.shape[0]):
+            # Create BoundingBox object and append to list
+            result, box = bounding_box.BoundingBox.create(boxes_cpu[i])
+            if result:  # this way only valid boxes are added
+                bounding_boxes.append(box)
+
+        return bounding_boxes, image_annotated
         # ============
         # ↑ BOOTCAMPERS MODIFY ABOVE THIS COMMENT ↑
         # ============

requirements.txt

@@ -17,7 +17,6 @@ pytest
 # If you are on MacOS, don't have a CUDA capable GPU,
 # or if things don't work and you just want to use the CPU,
 # comment out the "--extra-index-url" option
---extra-index-url https://download.pytorch.org/whl/cu124
 
 # ============
 # ↑ BOOTCAMPERS MODIFY ABOVE THIS COMMENT ↑