Using multi-camera systems in robotics: Efficient solutions to the NPnP problem

This paper introduces two novel solutions to the generalized-camera exterior orientation problem, which has a vast number of potential applications in robotics: (i) a minimal solution requiring only three point correspondences, and (ii) gPnP, an efficient, non-iterative n-point solution with linear complexity in the number of points. Already existing minimal solutions require exhaustive algebraic derivations. In contrast, our novel minimal solution is solved in a straightforward manner using the Gröbner basis method. Existing n-point solutions are mostly based on iterative optimization schemes. Our n-point solution is non-iterative and outperforms existing algorithms in terms of computational efficiency. Our results present an evaluation against state-of-the-art single-camera algorithms, and a comparison of different multi-camera setups. It demonstrates the superior noise resilience achieved when using multi-camera configurations, and the efficiency of our algorithms. As a further contribution, we illustrate a possible robotic use-case of our non-perspective orientation computation algorithms by presenting visual odometry results on real data with a non-overlapping multi-camera configuration, including a comparison to a loosely coupled alternative.