3D real-time positioning for autonomous navigation using a nine-point landmark

The objective of this paper is to propose a new monocular-vision strategy for real-time positioning applications. This is an important aspect whose solution is still necessary in many autonomous landmark-based navigation systems that run in non-controlled environments. The method is based on the analysis of the properties of the projected image of a single pattern consisting of eight small dots belonging to the vertices of an octagon and one more dot in the centre of it. The paper discusses how the pose is calculated by using the parameters of the ellipse that best fits the dots of the pattern and the relative position of the dots in it. The first part of this document provides a qualitative comparison with regard to other similar approaches. The method presented here has several notable properties. Firstly, the pattern can be easily recognized in the image and, more importantly, works under occlusion and noise circumstances. Secondly, it is capable of working in real-time conditions and deals with ranges of 30–700 cm. Finally, the method can be used on different applications (mobile robots and augmented reality systems) and yields better accuracy than others. An extensive report on experiments conducted in real situations is shown at the end of the paper. In order to make our method more compelling, an experimental comparison under occlusion and noise conditions is also made with one of the most widely used pose solutions, the ARToolkit method.