An artificial intelligence approach to forward kinematics of Stewart Platforms

Abstract

The Stewart Platform, one of the most successful and popular parallel robots, has attracted the attention of many researchers in recent decades. The solution of the forward kinematics problem in real-time is one of the key aspects that continues to garner interest. In this paper we propose a new approach for solving this particular case using Support Vector Machines, a popular Machine Learning method for classification and regression. The algorithm involves a data generation and preprocessing off-line phase, and a fast on-line evaluation. The experiments show that this method is very accurate and suitable for use in real-time.