Vision-Based Target Localization for a Flapping-Wing Aerial Vehicle

TL;DR

This paper presents a vision-based target localization algorithm tailored for flapping-wing aerial vehicles, addressing their unique constraints and demonstrating effective performance through simulation under noisy conditions.

Contribution

It introduces a novel localization algorithm that accounts for sensor errors and motion artifacts specific to FWAVs, validated via simulation.

Findings

The algorithm maintains accurate localization despite noise and jitter.

Simulation results show good performance of the proposed method.

The approach is suitable for the limited load and endurance of FWAVs.

Abstract

The flapping-wing aerial vehicle (FWAV) is a new type of flying robot that mimics the flight mode of birds and insects. However, FWAVs have their special characteristics of less load capacity and short endurance time, so that most existing systems of ground target localization are not suitable for them. In this paper, a vision-based target localization algorithm is proposed for FWAVs based on a generic camera model. Since sensors exist measurement error and the camera exists jitter and motion blur during flight, Gaussian noises are introduced in the simulation experiment, and then a first-order low-pass filter is used to stabilize the localization values. Moreover, in order to verify the feasibility and accuracy of the target localization algorithm, we design a set of simulation experiments where various noises are added. From the simulation results, it is found that the target localization algorithm has a good performance.