| Image-guided robot is a kind of industrial robot with a high degree of autonomy.It not only has the intelligence of vision,touch and force perception,but also has the ability of logical thinking and logical judgment like human beings.It is usually composed of two parts: machine vision system and motion control system.Under the function of image acquisition of the visual system,the image-guided robot can collect the object information on the working platform in real time and complete the picking operation of the object in real time.Image-guided robots are often used in automated production lines to complete stacking,filling,assembly,welding and other operations,and the efficiency of the robot lies in the path planning function.Robot path planning is an important research project in the field of robotics.The path planning of image-guided robots is usually divided into two parts.The second is the path optimization function of the robot.The path planning algorithm is used to optimize the path finding strategy of the robot,so that the robot can reach the designated place faster and complete the specified task.In this paper,an image-guided robot is designed according to the above background,and its working environment is modeled and analyzed with MATLAB.Finally,the path optimization algorithm of the image-guided robot is designed with C#.The main research contents of this paper are as follows:(1)For the purpose of image robot,the machine vision system and motion control system of image guided robot are designed.It includes the selection of hardware,the parameter calculation of the servo system,so that the robot can carry out path movement,and at the same time,the automatic focusing function of the industrial camera in the machine vision system is designed,so that the robot can collect clear working images in real time and analyze the position of objects on the working platform.(2)Analysis of image guided robot working environment,the use of MATLAB software for numerical modeling for the working environment of the robot,the 3 dcomplex to pick up the working environment in the form of digital matrix,and through the analysis of the robot pick up function,and converts the complicated dynamic action on pick up generality of traveling salesman problem(TSP),and the digital matrix using mathematical method to apply to TSP problem of matrix is derived.(3)The analysis and comparison are often used to solve TSP problem of intelligent path optimization algorithm,ant colony algorithm and genetic algorithm,using c # language developed two kinds of algorithm simulation program,to simulate the two algorithms under different conditions of path optimization performance,by comparing the two algorithms is obtained under different circumstances,discussed the way to realize image guided robot path optimization.(4)According to the analysis of path optimization algorithm,we design a heuristic Genetic Algorithm(GA)is adopted in the adaptive ant colony algorithm in image guided robot path optimization,simulation and experiment,through comparing with the traditional ant colony algorithm proves the improved path planning method has more efficiency and robustness,and the ability to find the optimal path is higher than the traditional ant colony algorithm. |
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