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@@ -11,14 +11,12 @@ The competition spanned 2 months, during which we developed two key modules:
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### Navigation
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The navigation module enables autonomous control of the drone within its environment. The initial objective involves reaching the buoy that delineates the search area where the threat is located. Subsequently, it demonstrates the capability to maneuver the surface drone while effectively tracking the identified threat.
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https://github.com/EthanDelage/aquabot/assets/50496792/67a0170c-d944-461a-99a4-69b9b991643f
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https://github.com/tdameros/aquabot-2023/assets/50496792/53d4a6ee-7184-470c-a88a-2476b1e089b6
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### Perception
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The perception module is designed to detect threats utilizing the camera and estimate their distance using lidar sensor. Threat recognition is achieved through color detection, while distance estimation involves projecting the lidar's 3D points onto the camera rendering. By leveraging the threat's distance and angle, the module can calculate its GPS position.
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https://github.com/EthanDelage/aquabot/assets/50496792/6377734d-59ac-47a8-b206-32733cc76101
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https://github.com/tdameros/aquabot-2023/assets/50496792/5449793f-8295-4d24-8243-e61d992a5d8c
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For additional details, please refer to the report available:
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