Design of robot automatic navigation under computer intelligent algorithm and machine vision

This work aims to explore the robot automatic navigation model under computer intelligent algorithms and machine vision, so that mobile robots can better serve all walks of life. In view current situation high cost poor flexibility robots, this innovatively researches improves image processing algorithm control algorithm. line edge detection stage, aiming at low efficiency traditional ant colony algorithm, Canny is combined improve it, a Canny-based proposed detect trajectory edge. addition, Single Shot MultiBox Detector (SSD) adopted obstacles in robot. The performance analyzed through simulation. results show accuracy basically stable 89.62%, its running time shortest. Further analysis SSD neural network comparison with other networks suggests feature recognition reaches 92.90%. least 3.74% higher versus algorithms, about 37.99 s, packet loss rate close 0. Therefore, constructed achieve premise ensuring error. Moreover, data transmission effect ideal. It provide experimental basis for later promotion adoption various fields.