JSAI2018

Presentation information

Oral presentation

General Session » [General Session] 13. AI Application

[2M3] [General Session] 13. AI Application

Wed. Jun 6, 2018 3:20 PM - 5:00 PM Room M (2F Amethyst Hall Hoo)

座長:荒井 幸代(千葉大学)

3:20 PM - 3:40 PM

[2M3-01] Drone Flying Area Estimation Method based on Deep Learning II

〇Masatoshi Hamanaka1 (1. RIKEN)

Keywords:drone, deep learning, lidar

This paper describes a method for estimating the flight area of drones based on deep learning. The position of a drone can be detected by using the global positioning system (GPS). However, GPS sometimes has problems capturing signals from satellites that are shielded by mountains and/or buildings. Moreover, GPS signals are very weak and subject to a variety of disturbances. Such problems increase the chance of a crash when flying a GPS controlled drone. As a solution to this problem, we propose a flight area estimation method using a 3D map created on the basis of deep learning. Our method could estimate the flight area with 98.4 percent accuracy in a field experiment.