An evolutionary algorithm for posture estimation of a three-dimensional object

Recently, the automation of picking work has advanced in the factory for the reduction of labor costs. When picking work is automatic, it is very important to estimate posture of target components. Therefore, an algorithm to automatically estimate posture is expected. We propose an efficient method to improve Differential Evolution (DE). Then, we applied the proposal method and DE to experiment to estimate posture of each four three-dimensional (3-D) objects by using the 3-D CAD data. The experimental results show that the proposal method achieves high success rate and efficiency than DE.