Active Control of Visual Sensor for Aerial Tracking

نویسندگان

  • Chengyu Cao
  • Naira Hovakimyan
  • Johnny Evers
چکیده

This paper addresses the problem of on-board estimation of the state and/or the velocity components of an unknown leader by open-loop control of a single camera installed on the follower aircraft. Unlike the conventional pan-tilt gimbal, a custom-built gimbal is assumed that permits translational movement of the camera. The only information about the unknown leader is deduced from its bearing and subtended angles in the image plane of the camera. An adaptive estimation algorithm is applied to estimate the state vector and the geometric parameters of the unknown object from visual measurements outside the flight control loop of the follower aircraft. Asymptotic convergence of the estimated parameters to the true ones is proven and shown to be independent of the flight controller. The estimated parameters can be used in the guidance law of the follower aircraft without any modifications to it. The main benefit of the proposed paradigm is in this decoupling of estimation from control.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

HyperCube: A Small Lensless Position Sensing Device for the Tracking of Flickering Infrared LEDs

An innovative insect-based visual sensor is designed to perform active marker tracking. Without any optics and a field-of-view of about 60°, a novel miniature visual sensor is able to locate flickering markers (LEDs) with an accuracy much greater than the one dictated by the pixel pitch. With a size of only 1 cm3 and a mass of only 0.33 g, the lensless sensor, called HyperCube, is dedicated to ...

متن کامل

Unmanned aerial vehicles UAVs attitude, height, motion estimation and control using visual systems

This paper presents an implementation of an aircraft pose and motion estimator using visual systems as the principal sensor for controlling an Unmanned Aerial Vehicle (UAV) or as a redundant system for an Inertial Measure Unit (IMU) and gyros sensors. First, we explore the applications of the unified theory for central catadioptric cameras for attitude and heading estimation, explaining how the...

متن کامل

A Gravitational Search Algorithm-Based Single-Center of Mass Flocking Control for Tracking Single and Multiple Dynamic Targets for Parabolic Trajectories in Mobile Sensor Networks

Developing optimal flocking control procedure is an essential problem in mobile sensor networks (MSNs). Furthermore, finding the parameters such that the sensors can reach to the target in an appropriate time is an important issue. This paper offers an optimization approach based on metaheuristic methods for flocking control in MSNs to follow a target. We develop a non-differentiable optimizati...

متن کامل

Target Tracking with Unknown Maneuvers Using Adaptive Parameter Estimation in Wireless Sensor Networks

Abstract- Tracking a target which is sensed by a collection of randomly deployed, limited-capacity, and short-ranged sensors is a tricky problem and, yet applicable to the empirical world. In this paper, this challenge has been addressed a by introducing a nested algorithm to track a maneuvering target entering the sensor field. In the proposed nested algorithm, different modules are to fulfill...

متن کامل

Design of an Intelligent Controller for Station Keeping, Attitude Control, and Path Tracking of a Quadrotor Using Recursive Neural Networks

During recent years there has been growing interest in unmanned aerial vehicles (UAVs). Moreover, the necessity to control and navigate these vehicles has attracted much attention from researchers in this field. This is mostly due to the fact that the interactions between turbulent airflows apply complex aerodynamic forces to the system. Since the dynamics of a quadrotor are non-linear and the ...

متن کامل

Deep Neural Network-based Cooperative Visual Tracking through Multiple Micro Aerial Vehicles

Multi-camera full-body pose capture of humans and animals in outdoor environments is a highly challenging problem. Our approach to it involves a team of cooperating micro aerial vehicles (MAVs) with on-board cameras only. The key enabling-aspect of our approach is the on-board person detection and tracking method. Recent state-of-the-art methods based on deep neural networks (DNN) are highly pr...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2006