Abstract
For successful assembly of flexible parts, informations about their deformation as well as possible misalignments between the holes and their mating parts are essential. Such informations can be acquired from visual sensors. In the case of deformable part assembly, the corrective assembly motion to compensate for such misalignments needs to be determined from the measured informations. Since this assembly process is difficult to design based on the analysis of flexible parts, this paper presents a visual sensor-based error corrective algorithm using a neural network. The performance of the implemented neural network is verified through a series of experimental work. The results show that the proposed error-corrective algorithm is effective in compensating for the lateral misalignment, and that it can be extended to the assembly tasks carried under more general conditions.
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