A faster relative 3D position and attitude algorithm based on special four-point feature

Computer vision is gaining significant importance as a cheap, passive, and information-rich sensor in research areas such as unmanned vehicle. Using computer vision can estimate relative 3D position and attitude. This paper puts forward a new faster relative 3D position and attitude approach based on special four feature points. This method used prior knowledge of the four feature points of a square and parallel relation, avoided complicated iterative arithmetic in general four feature points' methods, and reduced time of objects position and attitude estimation. The theory and experiments with simulated data showed that the approach is efficient, robust and real-time.