This paper considers the problems of the integration of independent manipulator control systems. Areas of control of the manipulator are: recognition of objects and obstacles, identification of objects to be grasped, determination of reliable positions by the grasping device, planning of movement of the manipulator to certain positions with avoidance of obstacles, and recognition of slipping or determination of reliable grasping. This issue is a current problem primarily in industry, general-purpose robots, and experimental robots. This paper considers current publications that address these issues. Existing algorithms and approaches have been found in the management of both parts of the robot manipulator and solutions that combine several areas, or the integration of several existing approaches. There is a brief review of current literature and publications on the above algorithms and approaches. The advantages and disadvantages of the considered methods and approaches are determined. There are solutions that cover either some areas or only one of them, which does not meet the requirements of the problem. Using existing approaches, integration points of existing implementations are identified to get the best results. In the process, a system was developed that analyzes the environment, finds obstacles, objects for interaction, poses for grasping, plans the movement of the manipulator to a specific position, and ensures reliable grasping of the object. The next step was to test the system, test the performance, and adjust the parameters for the best results. The resulting system was developed by the research team of RT-Lions, Technik University, Reutlingen. The hardware research robot includes an Intel Realsense camera, a Sawyer Arm manipulator from Rethink Robotics, and an internally grabbing device.
Development of Algorithms of Automatic Recognition of Objects in Control Systems Using Fuzzy Logic in Terms of Uncertainties
