Vision-Based Multirotor Control for Spherical Target Tracking: A Bearing-Angle Approach

TL;DR

This paper presents a novel bearing-angle based visual servo control method for multirotor drones to track moving spherical targets with unknown radii, using a new coordinate transformation and adaptive nonlinear control.

Contribution

It introduces a new bearing-angle transformation and an adaptive nonlinear control algorithm for spherical target tracking with unknown size.

Findings

Simulation results demonstrate effective target tracking performance.

The proposed method accurately estimates relative distance to the target.

The control algorithm adapts to target motion modeled as constant acceleration.

Abstract

This work addresses the problem of designing a visual servo controller for a multirotor vehicle, with the end goal of tracking a moving spherical target with unknown radius. To address this problem, we first transform two bearing measurements provided by a camera sensor into a bearing-angle pair. We then use this information to derive the system's dynamics in a new set of coordinates, where the angle measurement is used to quantify a relative distance to the target. Building on this system representation, we design an adaptive nonlinear control algorithm that takes advantage of the properties of the new system geometry and assumes that the target follows a constant acceleration model. Simulation results illustrate the performance of the proposed control algorithm.