Vision-based navigation of an unmanned surface vehicle with object detection and tracking abilities

The paper discusses autocalibration, object detection, and object tracking for unmanned surface vehicles. Input data are recorded with a wide-baseline stereo vision system providing accuracy for distance estimations. The paper reports about followed ways and novel contributions for ensuring a working system solution. Automatic self-calibration is used for the wide-baseline stereo vision system. Robust sea surface estimation and the detection of the horizon support the understanding of the given scene environment. Long-range (i.e. up to 500 m) object detection and tracking are supported by the used wide-baseline stereo system. The paper informs about the complete system design, informs about applied or designed methods, and also about experiments which verify that the system achieved an operational state.     

Intelligent unmanned ground vehicle navigation via information evaluation

Sensor-centric navigation of unmanned ground vehicles (UGVs) operating in rugged and expansive terrains requires the competency to evaluate the utility of sensor information such that it results in intelligent behavior of the vehicles. Highly imperfect, inconsistent information and incomplete a priori knowledge introduce uncertainty in such unmanned navigation systems. Understanding and quantifying uncertainty yields a measure of useful information that plays a critical role in several robotic navigation tasks such as sensor fusion, mapping, localization, path planning and control. In this article, within a probabilistic framework, the utility of estimation and information-theoretic concepts towards quantifying uncertainty using entropy and mutual information metrics in various contexts of UGV navigation via experimental results is demonstrated.     

RUR53: an unmanned ground vehicle for navigation,recognition, and manipulation

ABSTRACT

This paper proposes RUR53: an Unmanned Ground Vehicle able to navigate through, identify, and reach areas of interest. There, it can recognize, localize, and manipulate work tools to perform both indoor and outdoor complex tasks. Indeed, a wide range of sensors composes the robot and enables it to perceive vast workspaces, reach distant targets, and face the uncertainties of the real world. Precise object detection is also guaranteed, essential to manipulate objects of different shapes and materials. Moreover, a customized 3-finger gripper makes the gripping mode suitable for any lightweight object. Two modalities are proposed: autonomous and teleoperated, letting both unskilled and skilled human operators easily adapt the system to complete personalized tasks. The paper exhaustively describes RUR53 architecture and demonstrates its good performance while executing both indoor and outdoor navigation and manipulation tasks. A specific case study is described where the proposed modular architecture allows to easily switch to a semi-teleoperated mode: the 2017 Mohamed Bin Zayed International Robotics Challenge, where our team ranked third in the Grand Challenge in collaboration with the Czech Technical University in Prague, the University of Pennsylvania, and the University of Lincoln (UK).     

In-flight alignment of a strapdown inertial navigation system of an unmanned aerial vehicle

The alignment system of a strapdown inertial navigation system for an unmanned aerial vehicle installed on a carrier aircraft is studied. The aim is to develop alignment techniques for the strapdown inertial navigation system that improve the accuracy of alignment and reduce the alignment time. A technique for constructing the initial alignment system for a strapdown inertial navigation system of an unmanned aerial vehicle is proposed.     

Path‐following algorithms and experiments for an unmanned surface vehicle

This paper addresses the problem of path following in two‐dimensional space for underactuated unmanned surface vehicles (USVs), defining a set of guidance laws at the kinematic level. The proposed nonlinear Lyapunov‐based control law yields convergence of the path‐following error coordinates to zero. Furthermore, the introduction of a virtual controlled degree of freedom for the target to be followed on the path removes singularity behaviors present in other guidance algorithms proposed in the literature. Some heuristic approaches are then proposed to face the problem of speed of advance adaptation based on path curvature measurement and steering action prediction. Finally a set of experimental results of all the proposed guidance laws, carried out with the Charlie USV, demonstrates the feasibility of the proposed approach and the performance improvements, in terms of precision in following the reference path and transient reduction, obtained by introducing speed adaptation heuristics. © 2009 Wiley Periodicals, Inc.     

波浪干扰下固定双桨无人水面艇的路径跟踪方法

无人水面艇在路径跟踪过程中容易受到波浪环境的干扰,针对该问题提出一种基于可变船长比的直线路径跟踪方法。首先,建立了固定双桨无人水面艇在二阶波浪力下的运动模型;根据视距导航原理,设计了跟踪期望航向角的PD控制器,通过融合路径方向,距离偏差及船长比等信息,实时调整左右两侧推进电机的控制电压,实现无人水面艇直线路径跟踪。然后,针对不同船长比对直线路径跟踪的影响,在PD控制器中增加了以跟踪过程中的距离偏差和距离偏差变化率为输入,以船长比为输出的模糊推理模块,对船长比进行实时在线调整,提高了系统的抗波浪干扰性能。仿真结果表明,较之固定船长比的路径跟踪方法,所提方法使跟踪过程具有更好的动态性能,并且可减小波浪干扰下的路径跟踪偏差,有效克服波浪的干扰作用。     

Autonomous landing on a moving vehicle with an unmanned aerial vehicle

This paper addresses the perception, control, and trajectory planning for an aerial platform to identify and land on a moving car at 15 km/hr. The hexacopter unmanned aerial vehicle (UAV), equipped with onboard sensors and a computer, detects the car using a monocular camera and predicts the car future movement using a nonlinear motion model. While following the car, the UAV lands on its roof, and it attaches itself using magnetic legs. The proposed system is fully autonomous from takeoff to landing. Numerous field tests were conducted throughout the year‐long development and preparations for the Mohamed Bin Zayed International Robotics Challenge (MBZIRC) 2017 competition, for which the system was designed. We propose a novel control system in which a model predictive controller is used in real time to generate a reference trajectory for the UAV, which are then tracked by the nonlinear feedback controller. This combination allows to track predictions of the car motion with minimal position error. The evaluation presents three successful autonomous landings during the MBZIRC 2017, where our system achieved the fastest landing among all competing teams.     

无人机多源导航信息自主管理方法研究

完全依赖卫星导航信息融合的方案自主性差、完好性难以保证;而完全利用其它自主导航的方式,精度也难以保证,针对这些问题,提出了基于混合式架构的多源导航信息自主管理方法.利用联合故障检测方法,解决了对卫星干扰的有效检测,使完好性得到保证;设计了基于D–S证据推理的信息优选策略,针对典型无人机任务场景进行了仿真分析,结果表明信息优选策略降低了多故障检测方法同时应用的虚警率,提高了导航精度.     

推进器饱和/故障下的无人艇固定时间指定性能容错控制

针对系统动态未知的无人艇(USV)在推进器故障与饱和约束下轨迹跟踪问题,本文提出一种基于固定时间扩张状态观测器的积分滑模容错控制方法.首先,构造固定时间扩张状态观测器,实现未知速度信息、集总未知非线性的准确估计.进而,通过引入一种新型设定时间性能函数,约束位姿跟踪误差,并利用误差转换函数将其转化为无约束误差动态系统.在此基础上,结合固定时间积分滑动模态与饱和补偿动态系统,设计固定时间控制策略,保证系统实际固定时间稳定且位姿跟踪误差严格位于指定范围内.最后,仿真验证所提出控制方法的有效性与优越性.     

多方向无人水面艇路径规划算法

针对海洋环境下无人水面艇路径（USV）规划安全性与平滑性问题,提出一种多方向A^*路径规划算法以获得全局最优路径。首先,结合电子海图生成栅格化环境信息,并根据安全航行距离约束建立USV安全区域模型,在传统A^*算法基础上设计一种带安全距离约束的A^*启发函数来保证生成的路径节点的安全;其次,改进传统A^*算法的八方向搜索模式,提出一种多方向搜索模式来调整生成路径中的冗余点与拐点;最后,采用路径平滑算法对路径拐点进行平滑处理以获得满足实际航行要求的连续平滑路径。在仿真实验中,改进A^*算法规划的路径距离为7 043 m,相较于Dijkstra算法、传统A^*四方向搜索算法和传统A^*八方向搜索算法分别降低了9.7%、26.6%和7.9%。仿真结果表明改进后的多方向A^*搜索算法能够有效减小路径距离,更适用于USV路径规划问题。     

无人水面艇双目立体视觉系统设计

针对雷达不能利用目标的颜色等属性和水面多路径反射的干扰等问题,建立无人水面艇双目立体视觉系统,为实现无人水面艇的自主避障和目标跟踪等任务提供基础。采用两个IEEE1394接口的数字摄像机在无人水面艇上构建双目立体视觉系统,进而编程拍摄左右两幅图像并标定摄像机。结果表明,所构建的双目立体视觉系统可以用于无人水面艇视觉技术的研究。所设计的双目立体视觉系统对无人水面艇具有重要的研究意义。     

多方向无人水面艇路径规划算法

针对海洋环境下无人水面艇路径（USV）规划安全性与平滑性问题，提出一种多方向A^*路径规划算法以获得全局最优路径。首先，结合电子海图生成栅格化环境信息，并根据安全航行距离约束建立USV安全区域模型，在传统A^*算法基础上设计一种带安全距离约束的A^*启发函数来保证生成的路径节点的安全；其次，改进传统A^*算法的八方向搜索模式，提出一种多方向搜索模式来调整生成路径中的冗余点与拐点；最后，采用路径平滑算法对路径拐点进行平滑处理以获得满足实际航行要求的连续平滑路径。在仿真实验中，改进A^*算法规划的路径距离为7 043 m，相较于Dijkstra算法、传统A^*四方向搜索算法和传统A^*八方向搜索算法分别降低了9.7%、26.6%和7.9%。仿真结果表明改进后的多方向A^*搜索算法能够有效减小路径距离，更适用于USV路径规划问题。     

Field demonstration of advanced autonomous navigation technique for a fully unmanned surface vehicle in complex coastal traffic areas

This study introduces an advanced autonomous navigation algorithm for unmanned surface vehicle (USV) operations in complex coastal traffic areas. To facilitate the undertaking of tests for innovative technologies, the Korean government has designated regulation-free special zones, thereby enabling field tests for USV demonstrations without an onboard safety person on real manned-ship navigation routes. To enable real-world USV operation without onboard safety person, an existing autonomous navigation algorithm is extended to achieve sufficiently reliable and robust USV operation. Accordingly, berthing and unberthing algorithms are newly developed for unmanned operation, and enhanced situational awareness algorithms are applied to detect all types of obstacles, including small-sized floating objects spread over a wide range, such as a fish farm. In particular, the Korean intelligent maritime transportation service, called e-Navigation, is incorporated into the autonomous navigation algorithms to overcome the limitations of vehicle autonomy based on onboard sensors. To demonstrate the capability of fully unmanned operation in real marine traffic scenarios, long-distance navigation (54 km on a single voyage) was conducted by running several missions, including navigation in complex fish farm areas, maritime surveys, collision avoidance, navigation on real traffic routes, and emergency response. The extended navigation algorithms and results of the field tests are presented and discussed in this paper.     

推进器饱和约束的水面无人艇固定时间精准跟踪控制

针对复杂扰动、完全未知系统动态以及推进器饱和约束的水面无人艇高精度跟踪控制问题,提出一种基于固定时间非奇异终端滑模的无模型固定时间精准跟踪控制(MFPTC)方案.首先,设计有限时间集总观测器,精确重构和补偿集总未知项;其次,引入自适应辅助系统消除推进器饱和特性,使得MFPTC方案在饱和约束下实现期望时间内对预定轨迹的精准跟踪;进而,基于反正切函数构造固定时间幂次趋近律,加快滑模变量收敛速度且有效削弱控制抖振;最后,采用CyberShip Ⅱ实验模型进行仿真研究,结果验证所提出MFPTC方案的有效性与优越性.     

基于有限时间扰动观测器的无人水面艇精确航迹跟踪控制

针对复杂航行环境下的无人水面艇系统,提出一种基于有限时间扰动观测器的无人水面艇精确航迹跟踪控制策略.该控制方法具有以下显著特点:能够精确补偿未知海洋干扰,可实现精确跟踪控制;相比传统的渐近收敛控制算法,有限时间稳定性确保跟踪控制系统具有更快的收敛速度和更强的扰动抑制能力;能够同时确保扰动观测误差和航迹跟踪误差在有限时间内精确收敛到零.仿真结果验证了所提出控制方法的有效性和优越性.     

无人机的自动着陆控制

无人机的自动着陆控制是无人机控制中的一个难点,文中给出了一种无人机自动着陆的控制方法,并在某型无人机上得到了应用.基于无人机真实的风洞试验数据,利用MATLAB建立了无人机自动着陆的线性化模型和非线性模型,设计了无人机自动着陆导引控制方案及控制律,并在实际飞行试验中得到了验证,最终的飞行试验结果表明了所设计的自动着陆控制律能满足自动着陆的要求,并具有很好的静态和动态特性.     

Partial camera automation in an unmanned air vehicle

The present study focused on an intelligent, semiautonomous, interface for a camera operator of a simulated unmanned air vehicle (UAV). This interface used system “knowledge” concerning UAV motion in order to assist a camera operator in tracking an object moving through the landscape below. The semiautomated system compensated for the translations of the UAV relative to the earth. This compensation was accompanied by the appropriate joystick movements ensuring tactile (haptic) feedback of these system interventions. The operator had to superimpose self-initiated joystick manipulations over these system-initiated joystick motions in order to track the motion of a target (a driving truck) relative to the terrain. Tracking data showed that subjects performed substantially better with the active system. Apparently, the subjects had no difficulty in maintaining control, i.e. “following” the active stick while superimposing self-initiated control movements over the system-interventions. Furthermore, tracking performance with an active interface was clearly superior relative to the passive system. The magnitude of this effect was equal to the effect of update-frequency (2-5 Hz) of the monitor image. The benefits of update frequency enhancement and semiautomated tracking were the greatest under difficult steering conditions. Mental workload scores indicated that, for the difficult tracking-dynamics condition, both semiautomation and update frequency increase resulted in less experienced mental effort. For the easier dynamics this effect was only seen for update frequency     

非线性变参数无人船艏向$H_infty$鲁棒控制

针对水流冲击引起无人船(unmanned surface vehicle,USV)转艏呈现非线性特点,建立基于转艏运动的非线性变参数(nonlinear parameter-varying,NPV)USV模型,并提出一种NPV $H_\infty$ 艏向控制方法,以提高艏向调节的快速性和鲁棒性.首先,考虑低展弦比机翼理论能较好地描述船体受水流冲击的特点,建立基于水动力阻尼的非线性Fossen模型.通过忽略横荡速度和横流阻力将动力学模型简化为操纵动力学模型,并引入艏向角,建立NPV艏向模型.其次,构造与艏向控制系统状态和纵荡速度变参相关的Lyapunov函数,推导出满足艏向闭环控制系统$H_\infty$鲁棒稳定的非线性控制器求解条件,该条件是一个非线性矩阵不等式(nonlinear matrix inequality,NLMI).由于NLMI难以求解,根据平方和(sums of squares,SOS)理论,用多项式矩阵代替NLMI中的非线性矩阵,并将NLMI 转化为可使用SOS工具求解的多项式线性矩阵不等式.仿真结果表明,NPV $H_\infty$控制器在艏向调节时具有较快的系统响应和更高的准确性.     

欠驱动无人船非奇异固定时间鲁棒包容控制

针对外界干扰下的欠驱动无人船包容控制问题,提出一种新型非奇异固定时间滑模控制策略.整个控制器设计过程分为运动学回路设计和动力学回路设计.在运动学回路设计中,利用图论知识和固定时间稳定性理论设计非奇异固定时间分布式虚拟控制律,使得所有跟随船在固定时间内收敛于领导船张成的凸包内;在动力学回路设计中,为实现对虚拟控制律的跟踪控制,利用固定时间滑模控制法设计鲁棒包容控制律.最后,证明系统跟踪误差在固定时间收敛于平衡点,且与船舶的初始状态无关.仿真结果验证了所提出控制策略的有效性.