Research on Assembly Method of Threaded Fasteners Based on Visual and Force Information

Abstract

Threaded fastening operations are widely used in assembly and are typically time-consuming and costly. In low-volume, high-value manufacturing, fastening operations are carried out manually by skilled workers. The existing approaches are found to be less flexible and robust for performing assembly in a less structured industrial environment. This paper introduces a novel algorithm for detecting the position and orientation of threaded holes and a new method for tightening bolts. First, the elliptic arc fitting method and the three-point method are used to estimate the initial position and orientation of the threaded hole, and the force impact caused by switching from the free space to the constrained space during bolt tightening is solved. Second, by monitoring the deformation of passive compliance, the position information is introduced into the control process to better control the radial force between the bolt and the threaded hole in the tightening process. The constant force controller and orientation compliance controller are designed according to the adaptive control theory. A series of experiments are carried out. The results show that the proposed method can estimate the initial position and orientation of an M24 bolt with an average position error of 0.36 mm, 0.43 mm and 0.46 mm and an orientation error of 0.65°, 0.46° and 0.59°, and it can tighten the bolt with a success rate of 98.5%.

Optimization of Bolted Joints: A Literature Review

“…Zhou et al proposed a novel automated method for faastening threaded joints based on visual and force data [69]. A new tightening machine was made to tighten the bolts for the automobile differential mechanism based on the PLC as a core controller and two screwed shafts by the Profibus-DP communication (Figure 15).…”

A new novel recognition and positioning system of black light-absorbing volute for automation depalletizing development

“…For objects with complex shapes, irregular surface structures or uneven textures, traditional grasp strategies are no longer applicable. Therefore, many scholars have carried out different researches on the improvement and optimization of recognition algorithm for irregular object [9][10][11][12]. Poss et al developed a modular algorithm to achieve a successful grasping rate of 72% when handling various types of express packages, including dirty, labeled, or damaged ones [13].…”

Robot Motion Planning and Control for Thread Hole Cleaning Tasks

“…Pavol Martik [7] proposed to use a threedimensional coordinate system to determine the geometric position deviation of the threaded holes. Yibang Zhou [8] and others focused on preinsertion alignment of the threaded holes and adjustment of the bolt position and direction during the fastening stage. They explored a combined visual and force-based approach to monitor the position and direction of the bolt during the assembly process.…”