Forward Displacement Solution of Parallel Robot Based on Self-configuration Quick BP Neural Network

To optimize the structure of neural network, this paper improves the quick BP network by self-configuration method, which overcomes the restrictions of selecting the number of suitable hidden nodes only through experiments in the past and makes it more reasonable to select the number of hidden nodes of neural network. On this basis, this paper proposes a method for forward displacement solution of parallel robot based on self-configuration quick BP neural network. As an example, the forward displacement solution of novel 6-HURU parallel robot is resolved, and the results show that its average errors are less than 0.15mm and 0.06°, and meet the precision requirement of general applications. The validity and feasibility of the proposed method are proved.