Development of a Vision Aided Automated Ball Retrieving Robot for Tennis Training Sessions

A single training session of tennis requires 30-40 balls and these scattered balls have to be collected at the end of each session which costs time and induces unnecessary physical stress on players. This paper proposes a method to retrieve the balls which are scattered in the Tennis court back to the user. The proposed method comprises image processing techniques for object localization and the adaptation of Dijkstra's algorithm for optimum path planning for efficient navigation. Both localization and the path planning algorithms are developed on a Python platform and robot's differential drive system is controlled by a microcontroller. Communication between robot and the computer is established through Wi-Fi. Novel development of this research is the implementation of the global view method for a vast range of image acquisition and verifying its suitability in Tennis field. In order to collect balls efficiently, an adaption of an existing mechanism is proposed. Results show that the mechanism is 80% efficient in collecting balls and 100% efficient in object identification for a given environmental condition.