SingTown's AI "Ball Boy" Arrives on the Tennis Court: A Precise, Fast, and Interference-Resistant Automatic Ball Retrieval Solution

In the realm of intelligent sports equipment and robotics, enabling autonomous vehicles to identify and gather scattered tennis balls is a pivotal challenge in the realisation of an intelligent ball retrieval system.

Traditional solutions rely on infrared or ultrasonic sensing, which have limited recognition ranges and cannot distinguish target types.

To this end, intelligent robot manufacturers have adopted SingTown's OpenMV intelligent camera recognition technology, integrating AI machine vision, image recognition, and path planning algorithms to construct a system capable of identifying multiple tennis balls within a 15-metre range, calculating their coordinates, and planning automated ball retrieval trajectories.

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 meets the flexible requirements for edge deployment. By simply installing the camera above the ball-collecting cart, the camera's on-device AI can independently complete recognition tasks. Using a wide-angle lens to capture court images, it employs a composite algorithm combining 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.

The system's recognition range extends up to half a tennis court (approximately 15 metres). To address variations in lighting and interference factors on the court (such as shoes, boundary lines, shadows, etc.), the system employs filtering and target tracking mechanisms, enabling the algorithm to maintain stable and precise recognition capabilities in complex scenarios.

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.