Mérida Floriano, Macarena (Universidad Pablo de Olavide), Caballero, Fernando (University of Seville), García Morales, Diana (Consejo Superior de Investigaciones Científicas (CSIC) - Univers), Casares, Fernando (Consejo Superior de Investigaciones Científicas (CSIC) - Univers), Merino, Luis (Universidad Pablo de Olavide)

Bioinspired Vision-Only UAV Attitude Rate Estimation Using Machine Learning

Scheduled for presentation during the "Bio Inspired UASs, Autonomy, and Training" (FrB1), Friday, June 16, 2017, 14:05−14:25, Salon E

2017 International Conference on Unmanned Aircraft Systems, June 13-16, 2017, Miami Marriott Biscayne Bay, Miami, FL,

This information is tentative and subject to change. Compiled on April 25, 2024

Abstract

This paper presents a bioinspired system for attitude rate estimation using visual sensors for aerial vehicles. The sensorial system consists of three small low-resolution cameras (10x8 pixels), and is based on insect ocelli, a set of three simple eyes related to flight stabilization. Most previous approaches inspired by the ocellar system use model-based techniques and consider different assumptions, like known light source direction. Here, a learning approach is employed, using Artificial Neural Networks, in which the system is trained to recover the angular rates in different illumination scenarios with unknown light source direction. We present an study using real data in an indoor setting, in which we evaluate different network architectures and inputs.