多无人机联合三维定位中的目标优化识别

在进行多无人机定位中的目标优化识别时,由于目标高度离散性大,目标距离特征具有较大的随机性,导致传统的采用时空MUSIC算法的多无人机联合三维定位中的目标优化识别方法,无法依据稳定的距离矩阵特征,获取目标高度或俯仰信息,无法准确识别目标,提出一种基于ML的多无人机联合三维定位中的目标优化识别方法,利用多无人机联合三维定位目标动态模型,依据回波数据随时获取目标的径向距离、方位角以及多普勒信息,对多无人机联合三维定位中的目标位置进行最大似然估计,实现目标的准确优化识别。仿真结果表明,所提方法具有很高的精度及有效性。     

Grasping and In-Hand Manipulation: Geometry and Algorithms

This paper addresses the problem of grasping and manipulating three-dimensional objects with a reconfigurable gripper that consists of two parallel plates whose distance can be adjusted by a computer-controlled actuator. The bottom plate is a bare plane, and the top plate carries a rectangular grid of actuated pins that can translate in discrete increments under computer control. We propose to use this gripper to immobilize objects through frictionless contacts with three of the pins and the bottom plate, and to manipulate an object within a grasp by planning the sequence of pin configurations that will bring this object to a desired position and orientation. A detailed analysis of the problem geometry in configuration space is used to devise simple and efficient algorithms for grasp and manipulation planning. The proposed approach has been implemented and preliminary simulation experiments are discussed. Received November 15, 1996; revised February 4, 1998.     

可兼容多种无人机的北斗精确定位系统

本文设计了一种基于嵌入式系统、可安装在无人机上的北斗定位装置,可实现对无人机位置的精准定位,并且能将定位信息和无人机遥测信息进行存储.同时,可以将北斗定位信息以北斗短报文的形式进行发送,从而达到在无人机遥测数据链路出现故障的情况下可以通过北斗定位系统来确定无人机飞行状态及飞行位置的目的.     

Hybrid Adaptive Control for Aerial Manipulation

This paper presents a control scheme to achieve dynamic stability in a mobile manipulating unmanned aerial vehicle (MM-UAV) using a combination of Gain scheduling and Lyapunov based model reference adaptive control (MRAC). Our test flight results indicate that we can accurately model and control our aerial vehicle when both moving the manipulators and interacting with target objects. Using the Lyapunov stability theory, the controller is proven to be stable. The simulation results showed how the MRAC is capable of stabilizing the oscillations produced from the unstable PI-D attitude control loop. Finally a high level control system based on a switching automaton is proposed in order to ensure the saftey of the aerial manipulation missions.     

多无人机任务推演系统研究

研究多无人机任务推演系统的设计与实现过程,在多无人机任务推演系统具体需求的基础上,设计系统的分层体系结构与具体功能模块。针对系统实现过程中的多机协同任务分配及航迹规划问题,建立相应的数学模型并使用改进遗传算法对模型进行求解。使用分布式处理技术解决模型解算与实时数据显示的矛盾。基于MapX控件实现系统中战场地图的显示与操作功能。该系统对制定合理作战方案、发挥无人机的最佳作战效能具有重要意义。     

面向无人机空地通信的无线信道密钥生成技术研究

无人机(unmanned aerial vehicles, UAVs)部署为空中通信节点为地面用户提供服务是未来非常具有吸引力的通信手段,基于信道密钥生成的方式可用于解决无线通信的安全问题.但空地信道的信道特征在短时间内互易性不佳的特点,会导致信道密钥生成性能急剧下降.针对这一问题,本文针对无人机测控单载波频域均衡(signal carrier frequency-domain equalization, SC-FDE)通信体制,提出了一种基于信道频域响应幅度最大值位置变化的单比特信道特征量化方法设计,所提量化方法有效融合了信道频域响应的幅度和位置信息,降低了初始密钥的不一致率.进一步,基于此量化方法设计了一整套可应用于无人机测控通信的密钥生成方案.最后,利用Xilinx的ZYNQ平台,搭建实现了实时的测控信道密钥生成系统,验证了所提方案在无人机空地信道下的可行性和可靠性.特别地,基于搭建的无线信道密钥生成系统,在节点静止、运动等不同无人机空地通信场景下进行了外场测试.结果表明,在终端运动状态下生成的密钥可以通过NIST随机性测试,且其密钥生成速率达28 bps.     

Cooperative Control of Multiple UAVs for Source Seeking

This paper considers the problem of unknown scalar field source seeking using multiple UAVs subject to input constraints. In this problem, each UAV can only measure the scalar field value at its current location. In order to seek the scalar field source, cooperation of multiple UAVs is carried out by adopting a leader-follower formation strategy. A least squares method is introduced to estimate the gradient of the scalar field at the leader UAV location based on the measurements of all UAVs. By using the estimated gradient, this paper proposes a guidance law for the heading of the leader UAV, and a sliding mode based heading rate controller is designed for the leader UAV to follow the desired heading angle. Furthermore, a heading rate controller is developed for each follower UAV to achieve circular formation around the leader UAV. Finally, simulation results are provided to demonstrate the effectiveness of the proposed approach.     

On the Generation of Trajectories for Multiple UAVs in Environments with Obstacles

This paper presents a methodology based on a variation of the Rapidly-exploring Random Trees (RRTs) that generates feasible trajectories for a team of autonomous aerial vehicles with holonomic constraints in environments with obstacles. Our approach uses Pythagorean Hodograph (PH) curves to connect vertices of the tree, which makes it possible to generate paths for which the main kinematic constraints of the vehicle are not violated. These paths are converted into trajectories based on feasible speed profiles of the robot. The smoothness of the acceleration profile of the vehicle is indirectly guaranteed between two vertices of the RRT tree. The proposed algorithm provides fast convergence to the final trajectory. We still utilize the properties of the RRT to avoid collisions with static, environment bound obstacles and dynamic obstacles, such as other vehicles in the multi-vehicle planning scenario. We show results for a set of small unmanned aerial vehicles in environments with different configurations.     

Omnidirectional vision applied to Unmanned Aerial Vehicles (UAVs) attitude and heading estimation

This paper presents an aircraft attitude and heading estimator using catadioptric images as a principal sensor for UAV or as a redundant system for IMU (Inertial Measure Unit) and gyro sensors. First, we explain how the unified theory for central catadioptric cameras is used for attitude and heading estimation, explaining how the skyline is projected on the catadioptric image and how it is segmented and used to calculate the UAV’s attitude. Then, we use appearance images to obtain a visual compass, and we calculate the relative rotation and heading of the aerial vehicle. Finally the tests and results using the UAV COLIBRI platform and the validation of them in real flights are presented, comparing the estimated data with the inertial values measured on board.     

Cooperative Tracking a Moving Target Using Multiple Fixed-wing UAVs

A cooperative tracking scheme is presented in this paper for multiple fixed-wing unmanned aerial vehicles (UAVs) to track an uncooperative, moving target. It is comprised of a target loitering algorithm and a formation flight algorithm. The loitering algorithm enables a constant speed UAV to circle around a moving target, whose speed is allowed to vary up to the UAV’s speed. The formation algorithm enables cooperative tracking using multiple UAVs by keeping them flying in a circular formation with equal inter-vehicle angular separation. Under this formation algorithm, the formation center can be controlled independently to perform target loitering, and the admissible range of the target’s speed would not be affected for given UAVs. The performance of the proposed tracking system is verified in numerical simulations.     

分布式多无人机编队控制系统仿真

研究一种能够控制多无人机编队的分布式控制方法,采用无人机的动态方程转化为跟随机和领航机间相对运动信号与希望的相对运动信号间的误差模型,然后设计了前馈控制器以使误差模型的平衡点位于坐标原点,最后采用反推法设计了反馈控制器以镇定坐标原点的平衡点。上述方法将领航机的信息视为外部系统产生的信号,为前馈控制器部分设计了内部模型以补偿这些外部信号的作用。同时还设计了能够估计所有误差信号的状态观测器以实现需要全部误差信息的反馈控制器。算例仿真表明了应用编队控制律,各无人机能够较快地形成希望的队列,并按希望队形稳定飞行,验证了前馈加反馈的编队控制方法的有效性。     

Predicting Controller Capacity in Supervisory Control of Multiple UAVs

In the future vision of allowing a single operator to remotely control multiple unmanned vehicles, it is not well understood what cognitive constraints limit the number of vehicles and related tasks that a single operator can manage. This paper illustrates that, when predicting the number of unmanned aerial vehicles (UAVs) that a single operator can control, it is important to model the sources of wait times (WTs) caused by human-vehicle interaction, particularly since these times could potentially lead to a system failure. Specifically, these sources of vehicle WTs include cognitive reorientation and interaction WT (WTI), queues for multiple-vehicle interactions, and loss of situation awareness (SA) WTs. When WTs were included, predictions using a multiple homogeneous and independent UAV simulation dropped by up to 67%, with a loss of SA as the primary source of WT delays. Moreover, this paper demonstrated that even in a highly automated management-by-exception system, which should alleviate queuing and WTIs, operator capacity is still affected by the SA WT, causing a 36% decrease over the capacity model with no WT included.     

Cooperative Control of Multiple UAVs for Moving Source Seeking

Advances in multi-agent technologies and UAV technologies make it possible to take advantage of cooperation of multiple UAVs for source seeking. This paper focuses on moving source seeking using multiple UAVs with input constraints. Firstly, a least-squares method is introduced to estimate the gradient of the scalar field at the leader UAV location based on the measurements of all UAVs. Since the moving source velocity is unknown, an adaptive estimator is designed to obtain the velocity. Based on the estimated gradient and source velocity, a guidance law and a sliding mode based heading rate controller are proposed for the leader UAV to achieve level tracking. Heading rate controller for each follower UAV is also developed to achieve circular formation around the leader UAV. Furthermore, the gradient estimation error is analyzed and its influence on moving source velocity estimation and level tracking accuracy is explored as well. Finally, simulation results are provided to verify the proposed approach.     

Toward a Natural Language Interface for Transferring Grasping Skills to Robots

In this paper, we report on the findings of a human-robot interaction study that aims at developing a communication language for transferring grasping skills from a nontechnical user to a robot. Participants with different backgrounds and education levels were asked to command a five-degree-of-freedom human-scale robot arm to grasp five small everyday objects. They were allowed to use either commands from an existing command set or develop their own equivalent natural language instructions. The study revealed several important findings. First, individual participants were more inclined to use simple, familiar commands than more powerful ones. In most cases, once a set of instructions was found to accomplish the grasping task, few participants deviated from that set. In addition, we also found that the participant's background does appear to play a role during the interaction process. Overall, participants with less technical backgrounds require more time and more commands on average to complete a grasping task as compared to participants with more technical backgrounds.     

基于故障观测器的多无人机姿态一致性控制

在多个固定翼无人机姿态主从式一致性控制过程中,给出单个固定翼无人机在理想情况下的姿态动力学模型,即名义模型.考虑到无人机在实际运行过程中存在的外部干扰、状态测量误差、控制器微小故障以及无人机实际模型与名义模型之间的偏移,提出一种基于观测器和神经网络的故障检测方法,以实时检测出无人机中存在的故障、模型不确定以及干扰情况....     

一种支持多目标的数据流操作语言

随着数据流在各个应用领域的涌现和广泛应用，数据流相关的研究已经成为数据库技术中一个新的研究方向，并得到了越来越多的关注．数据流的操作语言作为用户与数据流管理系统之问进行语义交换的桥梁，从很大程度上体现出了数据流处理的特点．提出了一种数据流管理系统中支持多目标的数据流操作语言．它可以同时完成对数据流和关系表的操作．此外针对数据流的特性，语言中还引入了时间戳，时间粒度，连续查询，近似查询等相关概念，并以丰富灵活的语法支持了各种相关技术．     

基于长机—僚机模式的无人机编队方法及飞行实验研究

针对目前无人机编队方法无法在实际飞行实验中应用的问题,设计了基于长机—僚机跟踪模式的双机 协同编队算法,以双机的空间距离为控制对象,将所有的控制指令转化为速度、航向和高度指令．为实现实际编队 飞行,基于实验室自行研发的小型无人机,建立双串口地面控制系统硬件平台,重点解决了双串口的实现及双机数 据同步问题．地面跑车实验和实际飞行实验表明：该地面控制系统可以很好地实现双机的数据通信,控制指令实时 上传准确,协同算法正确有效．     

3D Path Planning for Multiple UAVs for Maximum Information Collection

This paper addresses the problem of path planning for multiple UAVs. The paths are planned to maximize collected amount of information from Desired Regions (DR) while avoiding Forbidden Regions (FR) violation and reaching the destination. The approach extends prior study for multiple UAVs by considering 3D environment constraints. The path planning problem is studied as an optimization problem. The problem has been solved by a Genetic Algorithm (GA) with the proposal of novel evolutionary operators. The initial populations have been generated from a seed-path for each UAV. The seed-paths have been obtained both by utilizing the Pattern Search method and solving the multiple-Traveling Salesman Problem (mTSP). Utilizing the mTSP solves both the visiting sequences of DRs and the assignment problem of “which DR should be visited by which UAV”. It should be emphasized that all of the paths in population in any generation of the GA have been constructed using the dynamical mathematical model of an UAV equipped with the autopilot and guidance algorithms. Simulations are realized in the MATLAB/Simulink environment. The path planning algorithm has been tested with different scenarios, and the results are presented in Section 6. Although there are previous studies in this field, this paper focuses on maximizing the collected information instead of minimizing the total mission time. Even though, a direct comparison of our results with those in the literature is not possible, it has been observed that the proposed methodology generates satisfactory and intuitively expected solutions.     

一种持续侦察无人机集群规模自适应调控方法

无人机集群(unmanned aerial vehicles, UAVs)持续侦察是多无人机协同控制中一个重要的研究方向.随着任务环境和使命需求越来越复杂,对无人机集群可重构性和柔性的要求也越来越高.其中,对于自适应可重构无人机集群,无人机的规模数量是最基本的控制要素之一.然而,目前大部分无人机集群的研究都侧重于特定任务背景下的路径规划,而集群规模的动态调整则未被考虑.针对传统无人机集群侦察设计中,集群的数量难以自适应调整以匹配不同侦察环境、不同侦察态势的问题,提出了基于区域信息熵的“数字草皮”及其植物量变化模型,模仿草皮-食草动物生态系统中的动态平衡机制,设计了目标区域-无人机集群持续侦察体系中的规模控制方法.在此基础上,研究了侦察体系达到稳定时群落矩阵和平衡点的情况,探讨了在不同任务环境中、不同效能约束限制下,无人机集群规模的自适应调控方法,并利用仿真和可视化手段对平衡点的存在性和系统的收敛性进行了验证.