Research on innovative applications and challenges of key technologies of intelligent vision systems in industrial robots

With the development of computer intelligent vision system technology and the broadening of its application scope, the emotional computing ability of robots has become an important way to enhance the operational capabilities of industrial robots. [Purpose] This study aims to further investigate the innovative applications of robot emotional computing technology, enabling industrial robots to make intelligent judgments about specific operational environments and there by improving the quality of industrial robot applications. [Method] Taking industrial robots engaged in sorting tasks as the research subject, this study constructs an image clustering and deduplication algorithm along with the Canny edge detector to allow sorting robots to intelligently recognize their surroundings and make intelligent judgments about sorting objects. The improved Canny algorithm is further refined and embedded into the visual system of industrial sorting robots to enhance the accuracy of their intelligent sorting. [Results] Experimental validation of the algorithm reveals that its application improves the efficiency and accuracy of sorting tasks, effectively overcoming the impact of illumination changes on the visual system. [Conclusion] The use of the improved Canny algorithm to optimize the intelligent vision system effectively enhances the adaptability of robots in sorting tasks, boosts production efficiency, and improves the calibration and recognition accuracy of sorting robots.