Autonomous Operation Method of Multi-DOF Robotic Arm Based on Binocular Vision

Abstract

Robotic arms with autonomous operation capabilities are currently widely used in real life, such as fruit picking, cargo handling, and workpiece assembly. However, the common autonomous operation methods of the robotic arm have some disadvantages, such as poor universality, low robustness, and difficult implementation. An autonomous operation method of multi-DOF (Multiple Degree of Freedom) robotic arm is proposed in this study on the basis of binocular vision. First, a target object extraction method based on extracting target feature points is proposed, and combined with the binocular positioning principle to obtain the spatial position of the target object. Second, in order to improve the working efficiency of the robotic arm, the robotic arm motion trajectory is planned on the basis of genetic algorithm in the joint space. Finally, a small physical prototype model is built for experimental verification. The experimental results show that the relative positioning error of the target object can reach 1.19% in the depth of field of 70–200 mm. The average grab error, variance, and grab success rate of the robot arm are 14 mm, 6.5 mm, and 83%, respectively. This shows that the method proposed in this paper has the advantages of high robustness, good versatility and easy implementation.