一类非完整移动机器人编队控制方法

针对大部分两轮非完整移动机器人轮轴中心与几何中心不重合的特点, 提出一种多机器人协调编队控制算法. 构造队形参数矩阵确定编队形状, 根据领航机器人和相关队形参数生成虚拟机器人, 把编队控制分解为跟随机器人对虚拟机器人的轨迹跟踪. 建立虚拟机器人与跟随机器人之间误差系统模型, 利用Lyapunov 理论设计相应控制器, 从而实现队形保持和变换. 应用microsoft robotics developer studio 4(MRDS4) 搭建3D 仿真平台, 设计3 组实验, 结果进一步验证了所提出方法的有效性.

     

基于单应性矩阵的移动机器人编队跟随控制

本文针对以领航跟随模型为代表的移动机器人编队系统提出了一种基于单应性的编队跟随控制方案,在给定理想队形间隔距离和理想期望图像的前提下,利用单应性矩阵构造可反映理想队形中跟随机器人实时位姿的虚拟机器人,将原先的编队问题转化为对虚拟机器人的轨迹跟踪问题.编队跟随过程中,领航机器人的速度采用估计的方式,利用单应性与速度之间的关系模型以及跟随机器人的实时速度能较为准确的估计领航速度,从而避免采用局部通信的方式,节省了编队实验成本.最后本文进行的半实物仿真以及实物实验均可验证所提出的编队跟随算法包括速度估计方法的实际有效性.     

动态环境下的多机器人编队控制方法的研究

多机器人编队控制是研究机器人协调合作问题的基础.在诸多的编队方法中,传统人工势场法以其算法简单,易于实现等特点被广泛应用于机器人避障.但上述方法无法适应动态未知环境,并且存在着局部极小问题,为解决上述问题,提出一种改进的人工协调场方法,即在排斥力的垂直方向增加一个协调力,从而消除零势能点,克服局部极小.同时与领航—跟随法结合,将编队信息预先存储在领航机器人中,通过队伍行进中领航者所发出的位置信息,跟随者保持队形,不仅可以达到灵活躲避动态障碍物,同时可以保持队形稳定.最终在TEAMBOTS平台上进行了仿真,结果证明了改进方法的有效性,实现了动态环境中的多机器人编队的灵活控制.     

多机器人队形保持与变换仿真研究

针对多机器人的队形保持与变换任务,采用基于行为的控制方法,设计了五种子行为,即奔向目标、躲避障碍物、围绕障碍物、随机扰动和保持队形.对有障碍物环境下的队形保持进行了仿真,并针对机器人队伍无法保持队形通过的地形,采用邻居参照点法与领航参照点法相结合的策略,改进了控制方法.仿真结果表明,使用改进的控制方法,机器人队伍可以安全地通过大直径障碍物,并且提高了队形稳定性.     

基于模糊人工势场法的多智能体编队控制及避障方法

针对动态环境中多智能体编队控制及避障问题,提出了一种基于模糊人工势场法的编队方法。首先,在领航跟随法的框架下控制编队队形,在动态队形变换策略的异构模式下,使用人工势场法为多智能体编队中每个智能体规划避障路径;其次,利用模糊控制器控制跟随智能体追踪领航智能体,同时保持跟随智能体之间与领航智能体的相对距离,遇到未知障碍物时,及时保持多智能体编队之间的队形并避免碰撞障碍物。针对人工势场法在引力增量系数和斥力增量系数设置的局限性,利用模糊控制器选择出适应环境的增量系数。Matlab仿真实验结果表明,该方法能够有效地解决复杂环境下多智能体编队控制及避障问题,使用效率函数对实验数据进行分析,验证了所优化方法的合理性和有效性。     

双参考点切换的多移动机器人队形运动控制方法

为描述机器人队列的运动过程,从相对位姿的角度定义了多移动机器人的队形模型.在传统leader-following队形控制的基础上,引入切换控制思想,每对领路机器人与跟随机器人之间设计3个控制器,对应跟随机器人中轴线上两参考点分别设计两个运动子控制器,控制领路机器人与跟随机器人之间的相对位姿;切换控制器根据系统处于平衡状态时,跟随机器人线速度的符号切换运动控制器,从而保证队列收敛到目标队形.仿真实验结果表明,机器人队列表现出良好的整体一致性,队列运动更加平稳.     

基于全向移动平台的多机器人编队控制研究

针对多机器人编队控制中的队形控制和协同避障问题,提出了基于麦克纳姆轮的全向移动多机器人编队的基于领航-跟随型编队控制算法.首先建立多机器人运动学模型,得到车体运动控制参数,并针对传统领航跟随法进行改进,设计一种虚拟结构领航-跟随法,并将改进的人工势场法引入领航机器人的在线局部路径规划中,通过添加虚拟斥力旋转势场,解决了局部极小值问题,实现了多机器人编队在静态障碍环境中无碰撞路径规划.最后通过Python仿真验证了该算法结合的有效性.     

移动机器人的队形控制及其主动避障

在这篇论文中, 我们利用一个统一的算法框架来解决移动机器人的队形控制和主动避障问题, 使得编队中的从机器人在避开障碍物的同时, 能够与被跟踪的主机器人保持期望的相对距离或相对方位. 在现有的关于主—从跟踪编队控制的文献中, 为了实现对主机器人快速准确的跟踪, 从机器人在跟踪控制时需要主机器人在惯性坐标系下的绝对运动速度作为队形跟踪控制器的输入. 然而, 在一些环境中, 主机器人的绝对运动状态很难获得. 这里, 我们将利用主—从机器人之间的相对速度来建立机器人编队系统的运动学模型. 基于这个模型的编队控制方法将不再需要测量主机器人的绝对运动速度. 进一步地, 上述的建模和控制方法被扩展为一个移动机器人的动态避障方法, 该方法利用机器人与障碍物之间相对运动状态作为避障控制器的信息输入. 利用由三个非完整移动机器人组成的多机器人系统, 验证了所提出编队控制方法的有效性.     

全向移动机器人编队分布式控制研究

简单介绍了NuBot机器人的两个主要组成部分：全向视觉和全向运动系统，并给出了运动学分析．基于该机器人平台，提出了D-A和D-D控制两种跟踪算法．通过机器人之间的相对定位和局部通信，实现了多机器人编队的分布式控制，同时，该算法可对机器人朝向进行独立控制．针对不同情况下的编队避障问题，提出了编队变形和编队变换两种方法．仿真和实际机器人实验表明，D-A控制方法能够实现平滑的编队变换；编队变形方法能够在尽量保持原始队形的情况下保证编队顺利避障．     

基于一致性理论的多机器人系统队形控制

首先回顾了多机器人系统队形控制方面的成果；然后提出一个多机器人队形控制的模型．该模型可描述多机器人之间相互作用固定和动态切换两种通信拓朴结构，也能描述多机器人系统队形的分布式控制方法和基于leader的控制方法，还能表示多机器人系统奔向目标点的行为，在此基础上，利用一致性理论，对系统的稳定性条件进行分析．最后通过仿真证明了该方法的有效性．     

A Synchronization Approach to Trajectory Tracking of Multiple Mobile Robots While Maintaining Time-Varying Formations

In this paper, we present a synchronization approach to trajectory tracking of multiple mobile robots while maintaining time-varying formations. The main idea is to control each robot to track its desired trajectory while synchronizing its motion with those of other robots to keep relative kinematics relationships, as required by the formation. First, we pose the formation-control problem as a synchronization control problem and identify the synchronization control goal according to the formation requirement. The formation error is measured by the position synchronization error, which is defined based on the established robot network. Second, we develop a synchronous controller for each robot's translation to guarantee that both position and synchronization errors approach zero asymptotically. The rotary controller is also designed to ensure that the robot is always oriented toward its desired position. Both translational and rotary controls are supported by a centralized high-level planer for task monitoring and robot global localization. Finally, we perform simulations and experiments to demonstrate the effectiveness of the proposed synchronization control approach in the formation control tasks.     

Formation control of underactuated bio-inspired snake robots

This paper considers formation control of snake robots. In particular, based on a simplified locomotion model, and using the method of virtual holonomic constraints, we control the body shape of the robot to a desired gait pattern defined by some pre-specified constraint functions. These functions are dynamic in that they depend on the state variables of two compensators which are used to control the orientation and planar position of the robot, making this a dynamic maneuvering control strategy. Furthermore, using a formation control strategy we make the multi-agent system converge to and keep a desired geometric formation, and enforce the formation follow a desired straight line path with a given speed profile. Specifically, we use the proposed maneuvering controller to solve the formation control problem for a group of snake robots by synchronizing the commanded velocities of the robots. Simulation results are presented which illustrate the successful performance of the theoretical approach.     

A switched-system approach to formation control and heading consensus for multi-robot systems

This paper proposes a novel, hybrid and decentralized, switched-system approach for formation and heading consensus control of mobile robots under switching communication topology, including collision avoidance capability. The set of robots consists of nonholonomic wheeled mobile robots and can include a teleoperated UAV. The key feature of this approach is a virtual graph, which is derived by adding a set of relative translation vectors to the real graph of the multiple robots. Our approach results in the robots in the real graph moving to the desired formation and achieving heading consensus while the virtual robots on the virtual graph reach pose consensus. If any robot detects a nearby obstacle or other robot, the robot will temporarily move along an avoidance vector, which is perpendicular and positively projected onto the attractive vector, such that collision is avoided while minimally deviating from its formation control path. Experimental results are provided by two different research groups to demonstrate the effectiveness of our approach. These experiments extend the theoretical development by introducing a teleoperated quadrotor as a leader robot of the multi-robot systems. The same control law works for the extended system, with no modifications.     

多机器人主—从行星式编队控制

研究了二阶积分器描述的多机器人主—从行星式编队控制问题,提出了将多机器人编队分解为每个机器人对各自具有时变速度的虚拟机器人的跟踪控制,使得每个机器人相对于虚拟机器人的位置与速度跟踪误差收敛为零且彼此不相碰撞,此时编队系统收敛到理想队形.在统一的算法框架下,分别实现了跟随者以领航者为中心的公转运动编队(revolution formation,RF)模式和跟随者与领航者保持期望距离、期望速度的编队(desiredformation,DF)模式.公转运动编队(RF)模式适用于异构多机器人系统的环境探索任务;保持期望距离、期望速度的编队(DF)模式适用于自主水下机器人(AUV)、无人机(UAV)等合作与协调任务.应用李亚普诺夫稳定性理论对控制算法的稳定性进行了分析,并通过计算机仿真验证了该方法的有效性.     

Decentralised consensus-based formation tracking of multiple differential drive robots

This article investigates the control problem for formation tracking of multiple nonholonomic robots under distributed manner which means each robot only needs local information exchange. A class of general state and input transform is introduced to convert the formation-tracking issue of multi-robot systems into the consensus-like problem with time-varying reference. The distributed observer-based protocol with nonlinear dynamics is developed for each robot to achieve the consensus tracking of the new system, which namely means a group of nonholonomic mobile robots can form the desired formation configuration with its centroid moving along the predefined reference trajectory. The finite-time stability of observer and control law is analysed rigorously by using the Lyapunov direct method, algebraic graph theory and matrix analysis. Numerical examples are finally provided to illustrate the effectiveness of the theory results proposed in this paper.     

From Trajectory Tracking Control to Leader–Follower Formation Control

Abstract

This work investigates the leader–follower formation control of multiple nonholonomic mobile robots. First, the formation control problem is converted into a trajectory tracking problem and a tracking controller based on the dynamic feedback linearization technique drives each follower robot toward its corresponding reference trajectory in order to achieve the formation. The desired orientation for each follower is selected such that the nonholonomic constraint of the robot is respected, and thus the tracking of the reference trajectory for each follower is feasible. An adaptive dynamic controller that considers the actuators dynamics in the design procedure is proposed. The dynamic model of the robots includes the actuators dynamics in order to obtain the velocities as control inputs instead of torques or voltages. Using Lyapunov control theory, the tracking errors are proven to be asymptotically stable and the formation is achieved despite the uncertainty of the dynamic model parameters. In order to assess the proposed control laws, a ROS-framework is developed to conduct real experiments using four ROS-enabled mobile robots TURTLEBOTs. Moreover, the leader fault problem, which is considered as the main drawback of the leader–follower approach, is solved under ROS. An experiment is conducted where in order to overcome this problem, the desired formation and the leader role are modified dynamically during the experiment.     

Analyzing the Multiple-target-multiple-agent Scenario Using Optimal Assignment Algorithms

This work considers the problem of maximum utilization of a set of mobile robots with limited sensor-range capabilities and limited travel distances. The robots are initially in random positions. A set of robots properly guards or covers a region if every point within the region is within the effective sensor range of at least one vehicle. We wish to move the vehicles into surveillance positions so as to guard or cover a region, while minimizing the maximum distance traveled by any vehicle. This problem can be formulated as an assignment problem, in which we must optimally decide which robot to assign to which slot of a desired matrix of grid points. The cost function is the maximum distance traveled by any robot. Assignment problems can be solved very efficiently. Solution times for one hundred robots took only seconds on a Silicon Graphics Crimson workstation. The initial positions of all the robots can be sampled by a central base station and their newly assigned positions communicated back to the robots. Alternatively, the robots can establish their own coordinate system with the origin fixed at one of the robots and orientation determined by the compass bearing of another robot relative to this robot. This paper presents example solutions to the multiple-target-multiple-agent scenario using a matching algorithm. Two separate cases with one hundred agents in each were analyzed using this method. We have found these mobile robot problems to be a very interesting application of optimal assignment algorithms, and we expect this to be a fruitful area for future research.     

非完整机器人Leader-Follower编队控制器设计

编队控制是多机器人协作的最重要的研究领域,其目的是控制组中的机器人的相对位置和方向,让机器人移动作为一个整体。Le-ader-follower策略已经广泛地应用到多机器人系统编队控制中。文中涉及了非完整移动机器人leader-follower编队控制问题,然后描述了基于leader-follower策略的控制方法,最后采用输入/输出反馈线性化方法设计控制器,以确保编队的渐进稳定。在保持理想的相对距离和转向角时,该控制器能够有效地稳定编队。仿真结果表明了该编队控制方案的有效性。