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GithubIn the field of intelligent sports equipment and robotics, enabling autonomous vehicles to identify and collect scattered tennis balls is a key challenge in realising an intelligent ball retrieval system.
傳統解決方案依賴紅外線或超聲波感應,其識別範圍有限且無法區分目標類型。
為此,智能機械人製造商採用了SingTown的OpenMV智能相機識別技術,整合AI機器視覺、圖像識別及路徑規劃算法,構建出一套能夠在15米範圍內識別多個網球、計算其座標並規劃自動拾球軌跡的系統。
This solution is widely applied in scenarios such as tennis training courts, intelligent sports robots, and unmanned auxiliary training equipment, significantly enhancing ball retrieval efficiency and the level of intelligence.

Intelligent robot manufacturers utilise SingTown Technology's OpenMV smart camera recognition technology to achieve automatic identification, positioning, and path planning for tennis balls.
This embedded vision system fulfills the flexible requirements for edge deployment. By simply installing the camera above the ball-collecting trolley, the camera's on-device AI can independently accomplish recognition tasks. Utilising a wide-angle lens to capture court images, it employs a composite algorithm integrating colour recognition, circular feature detection, and distance calculation to identify and locate multiple tennis balls within the frame.
Upon completion of identification, the OpenMV module calculates the actual spatial coordinates of the tennis ball using image coordinates and a geometric conversion model, and transmits the results via serial port to the STM32 control unit.
STM32 integrates real-time coordinate data with kinematic planning algorithms to compute the optimal ball-collection path (such as prioritising proximity, obstacle avoidance, etc.), controlling the vehicle to sequentially navigate to target points and execute the picking action.
系統嘅識別範圍可達半個網球場(約15米)。為咗應對球場上光線變化同干擾因素(例如鞋、邊界線、陰影等),系統採用咗過濾同目標追蹤機制,令算法能夠喺複雜場景下保持穩定同精準嘅識別能力。
This solution achieves a complete closed loop from visual recognition to coordinate calculation, path planning, and automatic ball collection, enabling the ball-collecting robot to truly possess AI vision and decision-making capabilities characterised by "accurate perception, precise movement, and efficient retrieval.

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