The Research Of Robot Materials-Detection Method Basedon Artificial Fish

In recent years, with the rapid development of robotics and image processing technology,machine vision applied in the logistics system more and more widely. The automatic, flexibleand intelligent logistics system and the research of which components has become aninevitable trend. Although in the early logistics system robots were also used, generally theywere only applied to the processes of handling and production mechanically and repeatedly.Nowadays,the robots have been able to work independently. Through CCD camera as avisual sensor, they can identify surrounding environment inoder to manufacture and operatethrough specific circumstances.The research of robot materials -detection method based on artificial fish is studied inthe paper. Firstly, the technology of machine vision and image processing is summarized, thenthe research background, research significance and main content are introduced briefly in thestudy.Secondly, Yaskawa's MOTOMAN-HP3 vertical robot with six joints, automatedwarehouse and automatic guided vehicle are linked up to a small local area network, thus thedesign of automated logistics system is completed.Thirdly, the implementation procedure of the small wireless network is developed basedon ZigBee wireless communication technology. The debugging of serial communications andhuman-computer interface design has been achieved by VC++ as programming environment.Ultimately the desired results are fulfilled. In addition, the written procedure of MOTOMANrobot is developed, which makes guarantee on detecting efficient and locating positionaccurate and snatching at materials.Fourthly, image processing technology is analysed. Taking the materials digital photoesof logistics system as object, the materials-detection is achieved triumphantly with image processing algorithms by comparing simulation. A large number of theoretical analysis andsimulation results have proved the effectiveness and feasibility of the algorithm selected.Finally, the intelligent optimization algorithm of artificial fish swarm is analysed andstudied. From the simulation experiments of TSP problem, optimization parameters areselected which make the AFSA (Artificial Fish Swarm Algorithm) find the optimal solution inorder to apply to image segmentation processing. Ideal results of materials-detection areobtained by a large number of experiments eventually.