Evaluating a Visual Simultaneous Localization and Mapping Solution on Embedded Platforms

Abstract

Simultaneous Localization and Mapping (SLAM) is an area of enormous growth in the robotics field. With the current evolution of microprocessors technology and the development of high-speed and precise SLAM solutions, running real-time SLAM algorithms on embedded platforms starts to become a feasible task. For this challenge to be achieved, evaluations on state-of-the-art SLAM methods running on the most up-to-date microcomputers at the moment must be done. This work presents results of ORB-SLAM2 running on both a Raspberry Pi 3B+ board and a NVIDIA Jetson Nano and suggests optimizations to be performed on future works.