平行机器人与平行无人系统:框架、结构、过程、平台及其应用

本文将基于ACP（Artificial societies,computational experiments,parallel execution）的平行系统思想与机器人领域相结合,形成一种软硬件相结合的框架,为无人机、无人车、无人船在复杂环境中实验、学习与实际工作提供便捷、安全的平台,即平行无人系统.本文从平行机器人的基本概念出发,提出平行无人系统的基本框架,并介绍了各模块的基本功能与实现方法,探讨了其中的关键技术.然后本文围绕无人机、无人车、无人船三个方面展望了无人平行系统在实际中的应用和所面临的挑战,提出了平行无人系统的未来发展方向.     

A Multi-Point Distance-Bounding Protocol for Securing Automatic Dependent Surveillance-Broadcast in Unmanned Aerial Vehicle Applications

The Automatic Dependent Surveillance-Broadcast (ADS-B) protocol is being adopted for use in unmanned aerial vehicles (UAVs) as the primary source of information for emerging multi-UAV collision avoidance algorithms. The lack of security features in ADS-B leaves any processes dependent upon the information vulnerable to a variety of threats from compromised and dishonest UAVs. This could result in substantial losses or damage to properties. This research proposes a new distance-bounding scheme for verifying the distance and flight trajectory in the ADS-B broadcast data from surrounding UAVs. The proposed scheme enables UAVs or ground stations to identify fraudulent UAVs and avoid collisions. The scheme was implemented and tested in the ArduPilot SITL (Software In The Loop) simulator to verify its ability to detect fraudulent UAVs. The experiments showed that the scheme achieved the desired accuracy in both flight trajectory measurement and attack detection.

     

面向目标跟踪的多机协同通信保持控制

由于无人机存在通信和测量约束的情况,远程无人机执行持续目标跟踪任务时无法直接与地面站保持通信,需要其他无人机作为通信中继方可与地面站建立可靠的通信连接.基于Dubins曲线,采用最小转弯半径和航向调整相结合的方法对具有初始和终止航向角约束的多无人机进行协同航路规划,确保所有无人机同时到达指定位置,形成多机协同通信保持的初始构型.针对随机移动目标,在多机协同通信保持的动态过程中,考虑平台性能、通信约束、碰撞规避等约束条件,采用非线性模型预测控制(NMPC)实现无人机协同分布式在线优化.在确保无人机通信中继保持的前提下,有效提高了算法的实时性.仿真结果表明了该算法的有效性.     

A modified consensus algorithm for multi-UAV formations based on pigeon-inspired optimization with a slow diving strategy

This paper considers the formation control problem for a group of unmanned aerial vehicles（UAVs） employing consensus with different optimizers.A group of UAVs can never accomplish difficult tasks without formation because if disordered they do not work any better than a single vehicle,and a single vehicle is limited by its undeveloped intelligence and insufficient load.Among the many formation methods,consensus has attracted much attention because of its effectiveness and simplicity.However,at the beginning of convergence,overshoot and oscillation are universal because of the limitation of communication and a lack of forecasting,which are inborn shortcomings of consensus.It is natural to modify this method with lots of optimizers.In order to reduce overshoot and smooth trajectories,this paper first adopted particle swarm optimization（PSO）,then pigeon-inspired optimization（PIO） to modify the consensus.PSO is a very popular optimizer,while PIO is a new method,both work but still retain disadvantages such as residual oscillation.As a result,it was necessary to modify PIO,and a pigeon-inspired optimization with a slow diving strategy（SD-PIO） is proposed.Convergence analysis was performed on the SD-PIO based on the Banach fixed-point theorem and conditions sufficient for stability were achieved.Finally,a series of comparative simulations were conducted to verify the feasibility and effectiveness of the proposed approach.     

Multiple UAVs/UGVs heterogeneous coordinated technique based on Receding Horizon Control (RHC) and velocity vector control

Multiple unmanned air vehicles(UAVs)/unmanned ground vehicles(UGVs) heterogeneous cooperation provides a new breakthrough for the effective application of UAV and UGV.On the basis of introduction of UAV/UGV mathematical model,the characteristics of heterogeneous flocking is analyzed in detail.Two key issues are considered in multi-UGV subgroups,which are Reynolds Rule and Virtual Leader(VL).Receding Horizon Control(RHC) with Particle Swarm Optimization(PSO) is proposed for multiple UGVs flocking,and velocit...     

Distributed hierarchical control for multiple vertical takeoff and landing UAVs with a distance‐based network topology

A distributed formation control algorithm is proposed for multiple vertical takeoff and landing (VTOL) unmanned aerial vehicles (UAVs) in this paper. The neighboring information is obtained by active measurements rather than by nonactive communications as done in the current literatures. By properly expanding the distance‐based network topology structure between each pair of UAVs, a distributed algorithm is proposed such that the switching topology remains connected along the time. Since a VTOL UAV system is typically underactuated, a hierarchical idea is introduced to derive the control design procedure. More specifically, the studied formation control problem of multiple VTOL UAVs is first transformed into the consensus problem of their corresponding error systems. Then, a command force and an applied torque are synthesized for each VTOL UAV such that the error systems reach a consensus. It is demonstrated in terms of Lyapunov theory that the proposed distributed hierarchical control algorithm guarantees the formation realization of multiple VTOL UAVs while maintaining the network connectivity. Finally, simulations are performed to validate the theoretical results.     

基于多智能体强化学习的无人机群室内辅助救援

本文主要研究了在室内场景中使用多台无人机设备对受害者进行合作搜索的问题.在室内场景中,依赖全球定位系统获取受害者位置信息可能是不可靠的.为此,本文提出一种基于多智能体强化学习(MARL)方案,该方案着重对无人机团队辅助救援时的路径规划问题进行研究.相比于传统方案,所提方案在大型室内救援场景中更具优势,例如部署多台救援无...     

Unmanned Aerial Vehicles Formation Using Learning Based Model Predictive Control

This paper presents a solution for the formation flight problem for multiple unmanned aerial vehicles (UAVs) cooperating to execute a required mission. Learning Based Model Predictive Control (LBMPC) is implemented on the team of UAVs in order to accomplish the required formation. All flight simulations respect Reynold's rules of flocking to avoid UAV collisions with nearby flockmates, match the team members velocity and stay close to each other during the formation. The main contribution of this paper lies in the application of LBMPC to solve the problem of formation for an autonomous team of UAVs. The proposed solution is theoretically, by the application of analysis to the problem, demonstrated to be stable. Moreover, simulations support the findings of the paper. The main contributions of this paper are the proposed LBMPC formulation for formation of vehicles with uncertainty in their models, and the theoretical analysis of the solution.     

Joint optimization of UAV position and user grouping for UAV-assisted hybrid NOMA systems

This article investigates the use of unmanned aerial vehicles (UAVs) in assisting hybrid non-orthogonal multiple access (NOMA) systems to enhance spectrum efficiency and communication connectivity. A joint optimization problem is formulated for UAV positioning and user grouping to maximize the sum rate. The formulated problem exhibits non-convexity, calling for an effective solution. To address this issue, a two-stage approach is proposed. In the first stage, a particle swarm optimization algorithm is employed to optimize the UAV positions without considering user grouping. With the UAV positions optimized, a game theory-based approach is utilized in the second stage to optimize user grouping and improve the sum rate of the hybrid NOMA system. Simulation results demonstrate that the proposed two-stage method achieves solutions close to the global optimum of the original problem. By optimizing the positions of UAVs and user groups, the sum rate can be effectively improved. Additionally, optimizing the deployment of UAVs ensures better fairness in providing communication services to multiple users.     

Output feedback observation and control for visual servoing of VTOL UAVs

This paper considers the question of stabilizing vertical take‐off and landing (VTOL) unmanned aerial vehicles (UAVs) using a minimal and an inexpensive sensor suite. The sensor suite considered consists of rate gyros and a single embedded video camera system. The approach taken is based on the principles of dynamic image‐based visual servo control and extends the authors' earlier work by removing dependence on additional sensors, such as accelerometers and magnetometers. The technique presented has potential for mini‐UAVs evolving in urban areas where global positioning system signals may not be available. The control algorithms and coupled state observers are presented in details. The main result of the paper is synthesized in a theorem along with a rigorous stability analysis of the closed‐loop system. An estimate of the basin of attraction for the closed‐loop system is provided. Simulation results are performed to illustrate the performance of the proposed control. Copyright © 2010 John Wiley & Sons, Ltd.     

Formation stability analysis of unmanned multi-vehicles under interconnection topologies

In this paper, the overall formation stability of an unmanned multi-vehicle is mathematically presented under interconnection topologies. A novel definition of formation error is first given and followed by the proposed formation stability hypothesis. Based on this hypothesis, a unique extension–decomposition–aggregation scheme is then employed to support the stability analysis for the overall multi-vehicle formation under a mesh topology. It is proved that the overall formation control system consisting of N number of nonlinear vehicles is not only asymptotically stable, but also exponentially stable in the sense of Lyapunov within a neighbourhood of the desired formation. This technique is shown to be applicable for a mesh topology but is equally applicable for other topologies. A simulation study of the formation manoeuvre of multiple Aerosonde UAVs (unmanned aerial vehicles), in 3-D space, is finally carried out verifying the achieved formation stability result.     

Trajectory Planning for Communication Relay Unmanned Aerial Vehicles in Urban Dynamic Environments

This paper proposes an optimal positioning and trajectory planning algorithm for unmanned aerial vehicles (UAVs) to improve a communication quality of a team of ground mobile nodes (vehicles) in a complex urban environment. In particular, a nonlinear model predictive control (NMPC)-based approach is proposed to find an efficient trajectory for UAVs with a discrete genetic algorithm while considering the dynamic constraints of fixed-wing UAVs. The advantages of using the proposed NMPC approach and the communication performance metrics are investigated through a number of scenarios with different horizon steps in the NMPC framework, the number of UAVs used, heading rates and speeds.     

存在视觉盲区的小型无人机群自主控制

小型无人机自身负载小,所能携带的通信设备比较有限,可以安装鱼眼镜头作为相互之间的视觉通信设备以扩大无人机的可视范围,但鱼眼镜头仍然存在视觉盲区.为了解决这一问题,论文提出了存在视觉盲区的小型无人机群自主控制算法.论文的主要思想是,首先,对无人机的飞行时的运动状态进行分析,进而建立其飞行时的运动学方程;其次,针对无人机飞...     

Fault‐tolerant formation control of multiple UAVs in the presence of actuator faults

In order to counteract actuator faults in formation flight of multiple unmanned aerial vehicles (UAVs), this paper presents a fault‐tolerant formation control (FTFC) design methodology, in which the reference generator and the finite‐time convergence of FTFC gains are explicitly considered. Feasible references in response to actuator faults can be generated by considering the health and mission conditions of an overall team of UAVs. Moreover, by applying an auxiliary integrated regressor matrix and vector method, FTFC gains can converge within a finite amount of time to facilitate the fault accommodation process. Thus, the negative effects resulting from failed actuators can be compensated by the healthy/redundant actuators in UAVs. Simulation studies of UAV formation flight are carried out to exemplify the effectiveness of this design approach. Copyright © 2015 John Wiley & Sons, Ltd.     

仿欧椋鸟大规模超机动行为的无人机集群转弯控制

为了在动态不确定环境下实现大规模无人机集群转弯的快速性和一致性,提出了一种仿欧椋鸟大规模超机动行为的无人机集群转弯控制方法．通过分析欧椋鸟大规模超机动行为,分别建立邻居选择、局部交互和信息传递机制,并将其映射到无人机集群转弯控制中．在这些机制的基础上,利用改进社会力模型进行无人机转弯控制,使无人机集群在没有外界刺激的情况下实现快速聚集和速度极化;而在有外界刺激的情况下,无人机切换模式,整个集群快速完成超机动转弯动作以避开危险．仿真实验结果表明,在该模型作用下无人机集群既能满足转弯曲率的要求,又能保持群集运动的一致性．     

面向搜索跟踪任务的小型无人机云台补偿控制

在地面目标搜索任务中,无人机与传感器设备的安装交联和无人机的六自由度运动会使得无人机探测路径与飞行路径之间产生差异．因此,针对耦合作用给搜索任务带来的消极影响,将无人机本体的姿态测量信息引入到对云台的控制中,保证飞行路径与探测路径的协调．同时,针对目标跟踪任务,对因为无人机与目标的相对位置变化对实时捕捉目标造成的不良影响进行补偿,使摄像机对目标的凝视更稳定、更准确．最后,通过仿真实验验证该云台控制方法的有效性．     

Asynchronous double-precision windows based unmanned aerial vehicle real-time path planning

A real-time path planning approach based on asynchronous double-precision windows is proposed for unmanned aerial vehicles (UAVs). In this proposed method, cursory paths and elaborate paths are planned respectively in the global and local windows. Specifically, global cursory path planner and local elaborate path planner are integrated by rolling two windows on different frequencies with different modes. Simulation results demonstrate that the proposed approach is effective for realizing a balance between t...     

下一代海洋机器人——写在人类创造下潜深度世界记录10912 米50 周年之际

人类探索、认识和利用海洋的活动历史很漫长，最近50 年，各种海洋机器人及相关装备的助推，使这 种活动达到了前所未有的高峰阶段，未来社会进步的需求和科学技术发展的牵引将会使这种活动达到新的高度．本 文简要回顾了世界和我国海洋机器人的发展历史，分析了各种类型海洋机器人的现状，并对其未来作了展望．     

Unmanned Aerial Vehicles: Control Methods and Future Challenges

With the rapid development of computer technology,automatic control technology and communication technology,research on unmanned aerial vehicles(UAVs)has attracted extensive attention from all over the world during the last decades.Particularly due to the demand of various civil applications,the conceptual design of UAV and autonomous flight control technology have been promoted and developed mutually.This paper is devoted to providing a brief review of the UAV control issues,including motion equations,various classical and advanced control approaches.The basic ideas,applicable conditions,advantages and disadvantages of these control approaches are illustrated and discussed.Some challenging topics and future research directions are raised.     

Formation control of unmanned aerial vehicle swarms: A comprehensive review

The unmanned aerial vehicle formation plays a crucial role in numerous applications, such as reconnaissance, agricultural plant protection, and electric power inspection. This paper provides a comprehensive review and analysis of the unmanned aerial vehicle swarm communication networks and formation control strategies. First, the most commonly used unmanned aerial vehicles are introduced and compared. Next, the entire process of the formation task, from the formation assignment to the formation transformation, is detailed described. At last, the widely adopted communication networks are analyzed, and the existing formation control strategies of the UAV swarm are compared, which shows that the distributed formation control is superior to the centralized method and is the future development trend.