A Neural Net-based Assembly Algorithm for Flexible Parts Assembly
Journal of Intelligent and Robotic Systems
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Flexible parts comparing with rigid parts can be deformed by contact force during assembly. For successful assembly, information about their deformation as well as possible misalignment between mating parts is essential. However, because of the nonlinear and complex relationship between parts deformation and reaction forces, it is difficult to acquire all required information from the reaction forces alone. In this paper, we propose an algorithm that can measure parts deformation and misalignment by using a visual sensing system in flexible parts assembly. Simulation results show that the system is effective in measuring parts deformation and misalignment, thereby dramatically increasing the rate of success in assembly operations.