A hierarchical cyclic pursuit scheme for vehicle networks

The agreement problem is studied whereby a group of mobile agents achieves convergence to a common point. A hierarchical cyclic pursuit scheme is introduced, and it is shown that this scheme yields a very significant increase in the rate of convergence to a common point when compared to traditional cyclic pursuit. A second scheme is introduced in which there are more communication links between vehicles. It is shown that this scheme produces a rate of convergence greater than the traditional scheme but significantly less than the hierarchical scheme.     

Cooperative control for target-capturing task based on a cyclic pursuit strategy

This paper studies a methodology for group coordination and cooperative control of n agents to achieve a target-capturing task in 3D space. The proposed approach is based on a cyclic pursuit strategy, where agent i simply pursues agent i+1 modulo n. The distinctive features of the proposed method are as follows. First, no communication mechanism between agents is necessary and thus it is inherently a distributed control strategy. Also, it is a simple robust memoryless control scheme which has self-stability property. Finally, it guarantees a global convergence of all agents to the desired formation. Further, it is also guaranteed that no collision occurs. Simulation examples are given to illustrate the efficacy of the proposed method and the achievement of a desired pursuit pattern in 3D space.     

Generalization of nonlinear cyclic pursuit

In this paper, some generalizations of the problem of formation of a group of autonomous mobile agents under nonlinear cyclic pursuit is studied. Cyclic pursuit is a simple distributed control law, in which the agent i pursues agent i+1 modulo n. Each agent is subjected to a nonholonomic constraint. A necessary condition for equilibrium formation to occur among a group of agents with different speeds and different controller gains is obtained. These results generalize equal speed and equal controller gain results available in the literature.     

Cooperative path planning with priority target assignment and collision avoidance guidance for rescue unmanned surface vehicles in a complex ocean environment

In this paper, a novel cooperative path planning scheme of unmanned surface vehicles (USVs) for rescuing targets in a complex ocean environment is proposed. The primary objective of the rescue USVs is to bring all targets back safely on the premise of first rescuing priority targets, while optimizing the path length, the navigation time and the angular energy. The main contributions of this paper are as follows: (1) The proposed K-means-division (KMD) algorithm is able to identify a complex ocean environment with collision-free zone and static-obstacles zone; (2) The proposed path planning method with fast-marching-method-based ellipse guidance range (E-FMM) is able to optimize the angular energy while ensuring safety; (3) The proposed cooperative management system (including priority-target-assignment (PTA) with reward-mechanism genetic-optimization (RM-GO) and collision-avoidance (CA) guidance law with Tangent-based surge-varying wave-disturbances-observer (Tangent-SV-WDO)) can accomplish the mission of the rescue USVs. Comparative studies with the state-of-the-art methods demonstrate that the proposed cooperative path planning scheme is superior in terms of priority-target-assignment (PTA) and collision-avoidance (CA) of the actual rescue work.     

Min–max time consensus tracking on a multi-quadrotor testbed

In this work, min–max time consensus tracking is implemented on a multi-quadrotor testbed. The trajectory of a leader quadrotor is generated manually. The remaining quadrotors converge onto this reference trajectory in min–max time using a local feedback control strategy which is known to be globally optimal. Further, the effect of finite communication/measurement rate on consensus tracking is analysed. The bounds on the deviations of the trajectories due to finite communication/measurement rate are characterized. The theoretical claims made are verified through experiments.     

A bio-inspired pursuit strategy for optimal control with partially constrained final state

We discuss a biologically inspired cooperative control strategy which allows a group of autonomous systems to solve optimal control problems with free final time and partially constrained final state. The proposed strategy, termed “generalized sampled local pursuit” (GSLP), mimics the way in which ants optimize their foraging trails, and guides the group toward an optimal solution, starting from an initial feasible trajectory. Under GSLP, an optimal control problem is solved in many “short” segments, which are constructed by group members interacting locally with lower information, communication and storage requirements compared to when the problem is solved all at once. We include a series of simulations that illustrate our approach.     

Adaptive configuration control of multiple UAVs

Several missions including surveillance, exploration, search-and-track, and lifting of heavy loads are best accomplished by multiple unmanned aerial vehicles (UAVs). Another important advantage to utilizing multiple vehicles is a reduction in the risk to successful completion of a mission due to the loss of a single vehicle. This increased robustness can lead to a commensurate decrease in vehicle specifications and cost, further improving the argument for swarm operations. This paper describes the development of an adaptive configuration controller for multiple vehicles executing a cooperative task in the presence of parametric uncertainty. A novel adaptive outer-loop controller that uses both local and global information is presented.     

Outdoor cooperative flight using decentralized consensus algorithm and a guaranteed real-time communication protocol

This paper describes the implementation of a decentralized consensus law with theoretically provable convergence properties on a multi-agent testbed comprising of quadrotors. It is shown that for small roll and pitch angles and well-tuned control loops, the quadrotor dynamics can be approximated as a pair of double integrators. Several experiments are carried out in an outdoor environment for validation of the consensus law which is based on double integrator dynamics. For any arbitrary initial positions of the quadrotors, the consensus law is able to drive them to an autonomously decided common point, given that the communication graph is connected at each instant of time. The resulting experimental trajectories and the consensus point matches with theoretical predictions. For guaranteeing real-time reliability required for such coordinated motion, a novel synchronized, time-slotted, scalable and fully airborne communication protocol is proposed. The protocol avoids data collisions and ensures real-time, reliable communication between agents. It can also address changing communication graph topologies, temporary link-breaks and additions. Using this underlying protocol, the quadrotors attain consensus for static and dynamic communication graphs. Experiments to observe the effect of communication rate on consensus performance are also conducted.     

多无人机航迹融合算法及性能评估

航迹融合是多无人机系统进行协同侦察, 巡逻和目标跟踪领域中的一个重要问题. 本文根据不同信息反馈配置 给出了局部航迹之间的协方差的精确计算, 并据此提出一种精确、具有可扩展性并且适用于任意通信频率的航迹融合 算法. 此外, 本文通过求解对应的离散代数Riccati方程求取融合估计的稳态误差协方差, 并以此进行融合性能分析. 最 后, 本文利用Monte Carlo仿真比较理论和实际结果, 实验结果验证了该融合算法的有效性.     

Cooperative control of multiple neural networks for an indoor blimp robot

We report on the cooperative control of multiple neural networks for an indoor blimp robot. In our research group, the indoor blimp robot has been studied to achieve various flying robot applications. The objective of this article is to propose a robust controller that can adapt to mechanical accidents such as the breakdown of propellers. In our proposed method, each propeller thrust is independently calculated by a small neural network. We confirm the advantage of the proposed method against the control by a single large neural network. This work was presented in part at the 13th International Symposium on Artificial Life and Robotics, Oita, Japan, January 31–February 2, 2008     

复杂多约束UAVs协同目标分配的一种统一建模方法

多无人机协同目标分配(Multi-UAVs cooperative target assignment problem, MUCTAP)是一个条件复杂的多模型、多约束组合优化问题, 很难用一致的方法获得可行的解. 为解决该问题, 本文对各种目标分配模型统一建模, 设计了一致的模型处理方法; 针对三维环境特点, 提出利用空间垂直切面计算无人机估计航程代价的方法, 并利用航程代价矩阵优化目标分配算法; 同时加入协同约束关系计算, 提高分配算法的准确性. 仿真实验验证了该方法能够处理多种情况的目标分配问题, 具有较高的通用性和准确性, 能够有效完成多机协同目标分配任务.     

Extremum seeking for moderately unstable systems and for autonomous vehicle target tracking without position measurements

We remove the long standing restriction that plant dynamics in extremum seeking control must be stable and provide an extension that allows single integrators, double integrators, and moderately unstable single poles. An application of the result for single and double integrators is in control of autonomous vehicles. Extremum seeking is used for finding a source of a signal (chemical, electromagnetic, etc.) whose strength decays with the distance. This is achieved without the measurement of the position vector and using only the measurement of the scalar signal.     

敌对攻击环境下基于移动目标防御的算法稳健性增强方法

传统的机器学习模型工作在良性环境中,通常假设训练数据和测试数据是同分布的,但在恶意文档检测等领域该假设被打破。敌人通过修改测试样本对分类算法展开攻击,使精巧构造的恶意样本能够逃过机器学习算法的检测。为了提高机器学习算法的安全性,提出了基于移动目标防御技术的算法稳健性增强方法。实验证明,该方法通过在算法模型、特征选择、结果输出等阶段的动态变换,能够有效抵御攻击者对检测算法的逃逸攻击。     

Autonomous navigation of an automated guided vehicle in industrial environments

The research presented in this paper approaches the issue of navigation using an automated guided vehicle (AGV) in industrial environments. The work describes the navigation system of a flexible AGV intended for operation in partially structured warehouses and with frequent changes in the floor plant layout. This is achieved by incorporating a high degree of on-board autonomy and by decreasing the amount of manual work required by the operator when establishing the a priori knowledge of the environment. The AGV's autonomy consists of the set of automatic tasks, such as planner, perception, path planning and path tracking, that the industrial vehicle must perform to accomplish the task required by the operator. The integration of these techniques has been tested in a real AGV working on an industrial warehouse environment.     

移动USBL测距辅助的UUV协同导航定位方法

针对无人水下航行器(UUV) 导航精度受惯性导航(INS) 影响较大的问题, 本文提出一种基于无人水面船 (USV)携带超短基线(USBL)对UUV进行移动式辅助导航定位的方法. 文中以USV上高精度INS和全球导航卫星系 统(GNSS)组合后的导航结果作为基准, 利用USBL测量得到的USV和UUV相对位置和姿态信息, 结合UUV的INS误 差方程, 建立了UUV协同导航系统的状态方程和观测方程, 并基于自适应卡尔曼滤波方法对UUV状态进行滤波估 计. 仿真和湖上实验结果表明, 文中所提方法可有效提升UUV导航精度.     

Basic navigation,guidance and control of an Unmanned Surface Vehicle

This paper discusses the navigation, guidance and control (NGC) system of an Unmanned Surface Vehicle (USV) through extended at sea trials carried out with the prototype autonomous catamaran Charlie. In particular, experiments demonstrate the effectiveness, both for precision and power consumption, of extended Kalman filter and simple PID guidance and control laws to perform basic control tasks such as auto-heading, auto-speed and straight line following with a USV equipped only with GPS and compass.

RoboCup仿真比赛中的Multi-Agent层次协作模型

本文针对RoboCup仿真比赛的多智能体协作问题，分析了目前在RoboCup中的几个典型多智能体协作模型，提出一种三层的Multi—Agent层次协作模型，它包括全局层、局部层和个体层。实战证明该模型是合理的、有效的。     

多无人水面艇协同海上溢油羽流监测

本文讨论多无人水面艇协同海上溢油污染羽流监测问题,其中羽流扩张过程是由二维空间对流–扩散方程描述.本文的主要目标是为水面无人艇构建基于领导–跟随–锚的协同控制算法,实现其对羽流边界的动态合围与实时跟踪,其中羽流边界是一个预先设定阈值的水平集合.为此,选择两艘无人水面艇分别将其设定为边界领导艇和边界锚艇,并将其余艇设定为...     

Navigation of an AUV for investigation of underwater structures

There is a great demand for autonomous underwater vehicles (AUVs) to investigate artificial underwater structures such as piles and caissons in harbours, and risers and jackets of deep-sea oilfields. This paper proposes an autonomous investigation method of underwater structures using AUVs that is implemented by initially detecting the target objects, localizing them, then approaching them by taking video images while closely tracing their shape. A laser ranging system and a navigation method based on the relative position with respect to the target objects are introduced to realize this behaviour.