Autonomous photogrammetric network design based on changing environment genetic algorithms

In order to get good accuracy, designer used to consider how to place cameras. Usually, cameras placement design is a multidimensional optimal problem, so people used genetic algorithms to solve it. But genetic algorithms could result in premature or convergent problem. Sometime we get local minimum and observe vibrating phenomenon. Those will get inaccurate design. So we try to solve the problem using the changing environment genetic algorithms. The work proposes giving those species groups difference environment during difference stage to improve the property. Computer simulation result shows the acceleration in convergent speed and ability of selecting good individual. This work would be used in other application.