High Precision Positioning with Multi-Camera Setups: Adaptive Kalman Fusion Algorithm for Fiducial Markers

Abstract

The paper addresses the problem of fusing the measurements from multiple cameras in order to estimate the position of fiducial markers. The objectives are to increase the precision and to extend the working area of the system. The proposed fusion method employs an adaptive Kalman algorithm which is used for calibrating the setup of cameras as well as for estimating the pose of the marker. Special measures are taken in order to mitigate the effect of the measurement noise. The proposed method is further tested in different scenarios using a Monte Carlo simulation, whose qualitative precision results are determined and compared. The solution is designed for specific positioning and alignment tasks in physics experiments, but also, has a degree of generality that makes it suitable for a wider range of applications.

Advanced Intelligent Control through Versatile Intelligent Portable Platforms

“…Advanced intelligent control opens new approaches for high precision positioning, based on the adaptive Kalman fusion algorithm for multiple cameras and fiducial markers using multiple sensor data in complex infrastructures, in which the issue of proper information implies complex considerations with respect to system dynamics, flexibility, efficiency, safety and in defining the emergent interaction with a highly dynamic and sparsely defined environment [ 6 ]. The use of solid target alignment, in which multiple optical diagnostics are positioned using motorized 3–6 DOF manipulators, utilizes multiple instruments which need to be precisely positioned relative to each other during the experiment.…”