Localization and Mapping algorithms implemented on a low-power embedded architectures: A case study

Abstract

In this paper we evaluate the promise held by low-power embedded architectures to implement SLAM (Simultaneous Localization and Mapping) algorithms. We map and implement 4 SLAM algorithms, that find utility in very different robot applications and autonomous navigation, on an embedded architecture. Our results show that low-power embedded architectures are indeed, sometimes, attractive alternative for some SLAM algorithms. At the same time, efficient software optimizations are mandatory to allow a real-time execution.