My Submission #126
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My Submission #126
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AaronWang04
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Nov 16, 2024
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| if ( | ||
| abs(self.waypoint.location_x - report.position.location_x) <= self.acceptance_radius | ||
| and abs(self.waypoint.location_y - report.position.location_y) | ||
| <= self.acceptance_radius |
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note that this is an acceptance RADIUS
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| elif not self.waypoint_reached: | ||
| command = commands.Command.create_set_relative_destination_command( | ||
| self.waypoint.location_x - report.position.location_x, | ||
| self.waypoint.location_y - report.position.location_y, | ||
| ) | ||
| print("Drone is moving") |
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if dorne halts and have not reached waypoint, then does it get stuck in a loop of doing nothing?
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| def l2_norm(self, x1: float, y1: float, x2: float, y2: float) -> float: | ||
| """ | ||
| Calculate the L2 norm between two points. | ||
| """ | ||
| return ((x1 - x2) ** 2 + (y1 - y2) ** 2) ** 0.5 | ||
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| def closest_pad( | ||
| self, landing_pad_locations: "list[location.Location]", position: location.Location | ||
| ) -> "tuple[float, float]": | ||
| """ | ||
| Find the closest landing pad. | ||
| """ | ||
| min_distance = float("inf") | ||
| closest_pad_coords = (None, None) | ||
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| for landing_pad in landing_pad_locations: | ||
| distance = self.l2_norm( | ||
| position.location_x, | ||
| position.location_y, | ||
| landing_pad.location_x, | ||
| landing_pad.location_y, | ||
| ) | ||
| if distance < min_distance: | ||
| min_distance = distance | ||
| closest_pad_coords = (landing_pad.location_x, landing_pad.location_y) | ||
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| return closest_pad_coords |
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you can make these methods static, generally a good thing to do
otherwise, good formatting and naming of functions
| @@ -67,8 +97,70 @@ def run( | |||
| # ============ | |||
| # ↓ BOOTCAMPERS MODIFY BELOW THIS COMMENT ↓ | |||
| # ============ | |||
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| # Do something based on the report and the state of this class... | |||
| if report.status == drone_status.DroneStatus.HALTED: | |||
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issue dittoed from decision simple waypoint
| for i in range(0, boxes_cpu.shape[0]): | ||
| result, box = bounding_box.BoundingBox.create(boxes_cpu[i]) | ||
| if not result: | ||
| return [], image_annotated |
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