This paper presents the design and construction of a robotic arm that plays chess against a\nhuman opponent, based on an artificial vision system. The mechanical design was an adaptation of\nthe robotic arm proposed by the rapid prototyping laboratory FabLab RUC (Fabrication Laboratory\nof the University of Roskilde). Using the software Solidworks, a gripper with 4 joints was designed.\nAn artificial vision system was developed for detecting the corners of the squares on a chessboard and\nperforming image segmentation. Then, an image recognition model was trained using convolutional\nneural networks to detect the movements of pieces on the board. An image-based visual servoing\nsystem was designed using the Kanadeâ??Lucasâ??Tomasi method, in order to locate the manipulator.\nAdditionally, an Arduino development board was programmed to control and receive information\nfrom the robotic arm using Gcode commands. Results show that with the Stockfish chess game\nengine, the system is able to make game decisions and manipulate the pieces on the board. In this\nway, it was possible to implement a didactic robotic arm as a relevant application in data processing\nand decision-making for programmable automatons.
Loading....