基于仿生双目的无人旋翼机自主着陆方法

基于仿生双目理论提出一种仿双眼异向运动的变视轴夹角双目视觉系统,通过对实时采集的目标图像的处理,研究其双目摄像机夹角的在线自标定,实现获取无人旋翼机的实时高度信息。实验结果表明,该方法获得的光轴夹角信息相对误差小于5%,能准确控制双目摄像机的转动,避免由于双目视觉盲区所造成的着陆误差,系统所标定出的旋翼机高度信息也为其安全着陆提供了有力保障。     

Feedback linearization of the nonlinear model of a small-scale helicopter

In order to design a nonlinear controller for small-scale autonomous helicopters, the dynamic characteristics of a model helicopter are investigated, and an integrated nonlinear model of a small-scale helicopter for hovering control is presented. It is proved that the nonlinear system of the small-scale helicopter can be transformed to a linear system using the dynamic feedback linearization technique. Finally, simulations are carried out to validate the nonlinear controller.     

微型直升机自主飞行辅助视觉系统研究

为了实现微型直升机自主飞行,论文设计了实时的计算机视觉系统。该系统包括机载上的硬件设备和软件算法,能够实现目标识别、特征点提取和位置估计。文中设计了特定图标,并主要依据颜色来进行快速识别。此外,通过检测4个共面的图像特征点,能够在单目单帧的基础上计算出直升机相对于特定目标的三维位置信息。视觉系统任务由位于机载上的IntelSitsang板来执行。由于受到板子运算能力的限制,每秒钟可以处理5帧160×120的彩色图像。飞行实验结果表明,该视觉系统的目标识别率高达93%,角点计算偏差小于3个像素,同时自身定位的三维位置坐标平均偏差为8cm、13cm和6cm。因此,该视觉系统通过精确自身定位,能够很好的辅助微型直升机完成自主悬停、起飞和降落等飞行任务。     

基于LQR的直升机悬停控制律设计与仿真

建立了某型直升机数学模型,并将该模型分解为纵向模型和横侧向模型两部分,提出了悬停控制律应该达到的稳态指标;以该型直升机为被控对象,采用输出反馈线性二次型调节器(LQR)技术设计了由纵向控制律和横侧向控制律组成的悬停控制律,使得直升机能取得满意的悬停性能指标;以该型直升机模型、执行器模型以及设计的悬停控制器构成全数字闭环仿真系统进行控制律仿真验证;仿真结果表明,文中设计的悬停控制律正确有效,能够较好地实现直升机的悬停功能,另外,由于该悬停控制律是基于输出反馈的,在工程上也比较容易实现。     

A method for ego-motion estimation in micro-hovering platforms flying in very cluttered environments

We aim at developing autonomous miniature hovering flying robots capable of navigating in unstructured GPS-denied environments. A major challenge is the miniaturization of the embedded sensors and processors that allow such platforms to fly by themselves. In this paper, we propose a novel ego-motion estimation algorithm for hovering robots equipped with inertial and optic-flow sensors that runs in real-time on a microcontroller and enables autonomous flight. Unlike many vision-based methods, this algorithm does not rely on feature tracking, structure estimation, additional distance sensors or assumptions about the environment. In this method, we introduce the translational optic-flow direction constraint, which uses the optic-flow direction but not its scale to correct for inertial sensor drift during changes of direction. This solution requires comparatively much simpler electronics and sensors and works in environments of any geometry. Here we describe the implementation and performance of the method on a hovering robot equipped with eight 0.65 g optic-flow sensors, and show that it can be used for closed-loop control of various motions.     

舰尾流随高扰动模型对直升机着舰悬停控制的影响研究

大海况下存在的复杂舰尾流严重影响直升机着舰时的飞行姿态,针对常规舰尾流模型仅适用于研究直升机纵向运动受干扰的问题,在美军标MIL-F-8785C描述的舰尾流模型基础上,提出增加随高度变化的垂向扰动分量,建立舰尾流随高扰动模型,以便切合实际地反映垂向干扰的作用强度;将该模型引入直升机着舰悬停系统后,针对传统PID控制对高度保持和位置控制效果不佳的问题,提出基于前馈补偿的改进PID控制;对比仿真结果表明,所提控制方法抗舰尾流干扰性强,具有良好的鲁棒性,控制精度优于传统的PID控制,实现了舰尾流干扰下直升机着舰悬停的稳定控制,有效提高了着舰飞行的安全性。     

Image-Based Visual PID Control of a Micro Helicopter Using a Stationary Camera

This paper proposes an image-based visual servo control method for a micro helicopter. The helicopter does not have any sensors to measure its position or posture on the body. A stationary camera is placed on the ground and it obtains image features of the helicopter. The differences between current features and given reference features are computed. PID controllers then make control input voltages for helicopter control and they drive the helicopter. The proposed controller can avoid some major difficulties in computer vision such as numerical instability due to image noise or model uncertainties, since the reference is defined in the image frames. An experimental result demonstrates that the proposed controller can keep the helicopter in a stable hover.     

一种基于视觉的移动机器人定位系统

具有自主的全局定位能力是自主式稳定机器人传感器系统的一项重要功能,为了实现这个目的,国内外均在不断地研究发展各种定位传感器系统,这里介绍了一种采用光学蝗全方位位置传感器系统,该传感器系统由主动式路标、视觉传感器、图象采集与数据处理系统组成,其视觉传感器和数据处理系统可安装在移动机器人上,然后可通过观测路标物「视角定位的方法,计算出机器人在世界坐标系中的位置和方向,实验证明,该系统可以只的在线定位,     

Passive range estimation for rotorcraft low-altitude flight

The automation of rotorcraft low-altitude flight presents challenging problems in control, computer vision, and image understanding. A critical element in this problem is the ability to detect and locate obstacles, using on-board sensors, and to modify the nominal trajectory. This requirement is also necessary for the safe landing of an autonomous lander on Mars. This paper examines some of the issues in the location of objects, using a sequence of images from a passive sensor, and describes a Kalman filter approach to estimate range to obstacles. The Kalman filter is also used to track features in the images leading to a significant reduction of search effort in the feature-extraction step of the algorithm. The method can compute range for both straightline and curvilinear motion of the sensor. An experiment is designed in the laboratory to acquire a sequence of images along with the sensor motion parameters under conditions similar to helicopter flight. The paper presents range estimation results using this imagery.     

Multi-Sensory Motion Estimation and Control of an Autonomous Quadrotor

In this paper, a fully autonomous quadrotor in a heterogeneous air–ground multi-robot system is established only using minimal on-board sensors: a monocular camera and inertial measurement units (IMUs). Efficient pose and motion estimation is proposed and optimized. A continuous-discrete extended Kalman filter is applied, in which the high-frequency IMU data drive the prediction, while the estimates are corrected by the accurate and steady vision data. A high-frequency fusion at 100 Hz is achieved. Moreover, time delay analysis and data synchronizations are conducted to further improve the pose/motion estimation of the quadrotor. The complete on-board implementation of sensor data processing and control algorithms reduces the influence of data transfer time delay, enables autonomous task accomplishment and extends the work space. Higher pose estimation accuracy and smaller control errors compared to the standard works are achieved in real-time hovering and tracking experiments.     

小型无人直升机的模型预测控制算法研究

针对无人直升机在阵风干扰环境中的姿态控制精度低的问题.本文将非线性刚体动力学模型在悬停点应用小扰动理论得到了线性化数学模型.考虑系统输入输出和控制量约束,采用模型预测控制将控制器的设计问题转化为每个采样时刻求解一个带不等式和等式约束的凸二次规划问题.通过设计终端状态约束解决了有限时域模型预测控制(model predictive control, MPC)算法的稳定性问题,并通过引入松弛变量使得约束优化问题更容易求解.随机和常值阵风干扰下无人机悬停仿真验证了本文MPC预测控制器具有幅度不超过0.25 m/s的良好干扰抑制能力,性能明显优于线性二次型调节器(linear-quadratic regulator, LQR).     

Dynamics of RC helicopter and control

It is hard to fly an RC helicopter desirably because of its dynamical instability and the fast responce of motion, so that some stabilizing control system has to be developed. The first step of design is the derivation of the mathematical model. Dynamics of a helicopter is much complicated due to the rotating blades and its validity is difficult to be evaluated. In this paper, the mathematical model of a hovering RC helicopter is derived and its validity is confirmed experimentally by designing the stabilizing control system of the gimbal equipment which has three degrees of freedom, rolling, pitching and yawing. At the same time, two kinds of small sensors are investigated and used to control the above equipment.     

Nonlinear modelling and control of helicopters

This paper presents the development of a nonlinear model and of a nonlinear control strategy for a VARIO scale model helicopter. Our global interest is a 7-DOF (degree-of-freedom) general model to be used for the autonomous forward-flight of helicopter drones. However, in this paper we focus on the particular case of a reduced-order model (3-DOF) representing the scale model helicopter mounted on an experimental platform. Both cases represent underactuated systems ( for the 7-DOF model and for the 3-DOF model studied in this paper). The proposed nonlinear model possesses quite specific features which make its study an interesting challenge, even in the 3-DOF case. In particular aerodynamical forces result in input signals and matrices which significantly differ from what is usually considered in the literature on mechanical systems control. Numerical results and experiments on a scale model helicopter illustrate the theoretical developments, and robustness with respect to parameter uncertainties is studied.     

旋翼空中机器人系统架构及设计

设计并验证了某型旋翼空中机器人的系统架构。整个空中机器人系统由直升机和地面站两部分组成。直升机是空中机器人的主体,可以自主飞行并完成指定任务。地面站用于监控无人直升机的飞行,并实现人机交互等多项功能。此外,地面站还可通过视觉导航系统引导直升机的自主着陆。直升机与地面站之间通过指令数字链路和视频模拟链路进行信息交互和实时通讯。经实际飞行验证,该空中机器人系统具有鲁棒和实时的特点,能实现直升机自主飞行和自主起降功能。     

直升机自动过渡悬停系统方案设计

为了实现直升机自动过渡悬停功能,首先运用模糊建模方法建立全包线飞机特性的T-S模型;然后基于增稳控制系统,实现飞机姿态角的稳定;在此基础上引入“多普勒”地速与无线电高度信号,设计高度和速度控制器,使飞机实际输出跟踪指令信号;最后提出了两种合理的高度速度指令设计方案,使得飞机能快速平稳地悬停到预定高度.仿真结果表明,该设计方法有效可行.     

基于ESO的无人直升机高精度姿态控制

针对小型无人直升机存在模型参数不确定性、电磁干扰影响的问题,设计了一种基于ESO（扩张状态观测器）的高精度姿态控制方法．直升机姿态通道中的不确定部分及外界复合扰动被视为总扰动,通过ESO进行实时估计,结合状态反馈控制器实现扰动消除．试验结果表明,在0.1 s内姿态角可从0°快速跟踪到5°且无超调．最后将设计的控制器应用于研制的高精度无人驾驶系统,实现系统参数变动等条件下直升机的全自主定点悬停和航迹飞行．     

Stability of small-scale UAV helicopters and quadrotors with added payload mass under PID control

The application of rotorcraft to autonomous load carrying and transport is a new frontier for Unmanned Aerial Vehicles (UAVs). This task requires that hovering vehicles remain stable and balanced in flight as payload mass is added to the vehicle. If payload is not loaded centered or the vehicle properly trimmed for offset loads, the robot will experience bias forces that must be rejected. In this paper, we explore the effect of dynamic load disturbances introduced by instantaneously increased payload mass and how those affect helicopters and quadrotors under Proportional-Integral-Derivative flight control. We determine stability bounds within which the changing mass-inertia parameters of the system due to the acquired object will not destabilize these aircraft with this standard flight controller. Additionally, we demonstrate experimentally the stability behavior of a helicopter undergoing a range of instantaneous step payload changes.     

Dynamic omnidirectional vision for mobile robots

Mobile robotic devices hold great promise for a variety of applications in industry. A key step in the design of a mobile robot is to determine the navigation method for mobility control. The purpose of this paper is to describe a new algorithm for omnidirectional vision navigation. A prototype omnidirectional vision system and the implementation of the navigation techniques using this modern sensor and an advanced automatic image processor is described. The significance of this work is in the development of a new and novel approach—dynamic omnidirectional vision for mobile robots and autonomous guided vehicles.     

基于双目视觉的小型无人直升机位姿检测

无人直升机的位置与姿态检测是直升机自主飞行控制的基础。基于双目视觉原理,对直升机标志点进行检测并跟踪,利用基于顺序一致性的极线约束匹配方法,对检测到的多个标志点进行立体匹配,计算标志点三维坐标从而得到无人直升机的位置与姿态信息。设计一个基于双目视觉的小型无人直升机空间位姿测量托架,用于飞行控制模型及飞行控制算法的研究及验证。     

基于视频的倒立摆摆起控制

在视觉信息用于连续反馈中,人们提出了基于视觉的伺服控制形式,对视觉传感器得到的图像进行快速处理,在尽量短的时间内给出反馈信息,构成系统的位置闭环控制。本文基于视频的倒立摆摆起控制,提供了一个视觉反馈倒立摆摆杆位置来控制的途径。文中对视频采集系统和软件设计进行了详细介绍,并给出了实际效果图。