一种多非完整移动机器人分布式编队控制方法

本文研究了多非完整移动机器人编队控制算法。在该算法中,参考轨迹被视为虚拟领导者,只有部分机器人可以接收到领导者信息,机器人之间只能进行局部信息交互。利用坐标变换将机器人系统的编队问题转化为变换后系统的一致性问题,在持续激励的条件下,设计了一种分布式控制算法,通过图论与Lyapunov 理论证明了该分布式控制算法可以使移动机器人队伍指数收敛于期望队形,并使队形的几何中心指数收敛到参考轨迹。最后,数值仿真验证了该控制算法的有效性。     

Control of leader–follower formation and path planning of mobile robots using Asexual Reproduction Optimization (ARO)

This paper presents the optimal path of nonholonomic multi robots with coherent formation in a leader–follower structure in the presence of obstacles using Asexual Reproduction Optimization (ARO). The robots path planning based on potential field method are accomplished and a novel formation controller for mobile robots based on potential field method is proposed. The efficiency of the proposed method is verified through simulation and experimental studies by applying them to control the formation of four e-Pucks robots (low-cost mobile robot platform). Also the proposed method is compared with Simulated Annealing, Improved Harmony Search and Cuckoo Optimization Algorithm methods and the experimental results, higher performance and fast convergence time to the best solution of the ARO demonstrated that this optimization method is appropriate for real time control application.     

Distributed Constraint Force Approach for Coordination of Multiple Mobile Robots

A new approach to coordination of multiple mobile robots is presented in this paper. The approach relies on the notion of constraint forces which are used in the development of the dynamics of a system of constrained particles with inertia. A familiar class of dynamic, nonholonomic robots are considered. The goal is to design a distributed coordination control algorithm for each robot in the group to achieve, and maintain, a particular formation while ensuring navigation of the group. The theory of constraint forces is used to generate a stable control algorithm for each mobile robot that will achieve, and maintain, a given formation. The advantage of the proposed method is that the formation keeping forces (constraint forces) cancel only those applied forces which act against the constraints. Another feature of the proposed distributed control algorithm is that it allows to add/remove other mobile robots into/from the formation gracefully with simple modifications of the control input. Further, the algorithm is scalable. To corroborate the theoretical approach, simulation results on a group of six robots are shown and discussed.     

Formation path following control of unicycle-type mobile robots

This paper presents a control strategy for the coordination of multiple mobile robots. A combination of the virtual structure and path following approaches is used to derive the formation architecture. A formation controller is proposed for the kinematic model of two-degree-of-freedom unicycle-type mobile robots. The approach is then extended to consider the formation controller by taking into account the physical dimensions and dynamics of the robots. The controller is designed in such a way that the path derivative is left as a free input to synchronize the robot’s motion. Simulation results with three robots are included to show the performance of our control system. Finally, the theoretical results are experimentally validated on a multi-robot platform.     

一种编队控制的动态调整与规划方法

This article is concerned with cooperative control problems in formation of mobile robots under the nonholonomic constraints that certain geometrical constraints are imposed on multiple mobile robots throughout their travel. For this purpose, a new method of motion control for formation is presented, which is based on the dynamic regulation and scheduling scheme. It is attractive for its adaptability to the formation structure and desired trajectory. The quality of formation keeping can be evaluated by the instantaneous errors of formation offset and spacing distance. Some kinematics laws are developed to regulate and maintain the formation shape. Simulation results and data analysis show the validity of the proposed approach for a group of robots.     

Robust formation control of electrically driven nonholonomic mobile robots via sliding mode technique

This paper proposes a sliding mode formation control method for electrically driven nonholonomic mobile robots in the presence of model uncertainties and disturbances. We use the kinematic model based on the leader-following approach for the formation control of multiple robots. Unlike many researches considering only the kinematic model, we also consider the dynamic model including actuator dynamics to obtain the voltage input because it is more realistic to use the voltage as input than the velocity. Then, the sliding mode control method is used to deal with model uncertainties and disturbances acting on the mobile robots. The stability of the proposed control system is proven using Lyapunov stability theory. Finally, we perform computer simulations to demonstrate the performance of the proposed control system.     

The leader-follower formation control of nonholonomic mobile robots

In this paper, the leader-waypoint-follower formation is constructed based on relative motion states of nonholonomic mobile robots. Since the robots’ velocities are constrained, we proposed a geometrical waypoint in cone method so that the follower robots move to their desired waypoints effectively. In order to form and maintain the formation of multi-robots, we combine stable tracking control method with receding horizon (RH) tracking control method. The stable tracking control method aims to make the robot’s state errors stable and the RH tracking control method guarantees that the convergence of the state errors tends toward zero efficiently. Based on the methods mentioned above, the mobile robots formation can be maintained in any trajectory such as a straight line, a circle or a sinusoid. The simulation results based on the proposed approaches show each follower robot can move to its waypoint efficiently. To validate the proposed methods, we do the experiments with nonholonomic robots using only limited on-board sensor information.     

一类有序化多移动机器人群集运动控制系统

群集运动控制(flocking control)是一种新型的多移动机器人运动协调控制, 目前的研究多集中于无leader模式下群集运动控制器的设计. 为此, 本文阐述了一类多移动机器人有序化群集运动系统控制方案及其性能评价方法. 首先, 在前人的研究基础上, 本文介绍了基于Agent的有序化编队控制机制; 然后, 运用非完整约束下移动机器人的动力学原理, 设计了由Agent到移动机器人的控制转化方法; 并进一步提出了基于“最小稳定时间”的群集运动分析法, 可对有序化群集运动系统进行分析; 最后, 运用仿真实例, 描述了多移动机器人有序化群集运动的控制及分析过程. 实验结果验证了此控制方案的有效性.     

Leader–follower formation control of nonholonomic mobile robots based on a bioinspired neurodynamic based approach

This paper investigates the leader–follower formation control problem for nonholonomic mobile robots based on a bioinspired neurodynamics based approach. The trajectory tracking control for a single nonholonomic mobile robot is extended to the formation control for multiple nonholonomic mobile robots based on the backstepping technique, in which the follower can track its real-time leader by the proposed kinematic controller. An auxiliary angular velocity control law is proposed to guarantee the global asymptotic stability of the followers and to further guarantee the local asymptotic stability of the entire formation. Also a bioinspired neurodynamics based approach is further developed to solve the impractical velocity jumps problem. The rigorous proofs are given by using Lyapunov theory. Simulations are also given to verify the effectiveness of the theoretical results.     

含驱动器动力学的移动机器人编队自适应控制

针对含有驱动器及编队动力学的多非完整移动机器人编队控制问题,基于领航者-跟随者[l-ψ]控制结构,通过反步法设计了一种将运动学控制器与驱动器输入电压控制器相结合的新型控制策略。采用径向基神经网络（RBFNN）对跟随者及领航者动力学非线性不确定部分进行在线估计,并通过自适应鲁棒控制器对神经网络建模误差进行补偿。该方法不但解决了移动机器人编队控制的参数与非参数不确定性问题,同时也确保了机器人编队在期望队形下对指定轨迹的跟踪;基于Lyapunov方法的设计过程,保证了控制系统的稳定与收敛;仿真结果表明了该方法的有效性。     

A finite-time approach to formation control of multiple mobile robots with terminal sliding mode

In this study, a new finite-time synchronised approach is developed for multiple mobile robots formation control based on terminal sliding mode control principle and system synchronisation theory. Associated stability analysis is presented to lay a foundation for analytical understanding in generic theoretical aspects and safe operation for real systems. An illustrative example of multiple mobile robots formation control is bench tested to validate the effectiveness of the proposed approach.     

基于双移动信标的多机器人编队控制算法

针对多机器人在未知环境下的编队控制问题,提出了一种基于双移动信标的多机器人编队算法.该方法在以两个移动信标机器人为领航机器人的基础之上,设计了基于超宽带测距技术的多机器人定位模型,通过摔制从机器人的位姿状态,实现多机器人编队控制,并且设计了多传感器数据融合算法,有效提高多机器人编队的精度.该方法解决了多机器人在未知环境中的编队控制问题,提高了多机器人编队控制的精度.仿真结果表明了该方法的可行性和有效性.     

多移动机器人组成任意队形的控制研究

本文将多移动机器人组成队形的整体行为分解为机器人个体分别向对应目标点运动的子行为加以研究．提出了基于两层监控模式的分布式控制框架,监控模块作为统一的指挥协调中枢,确定各机器人合理的对应目标点,避免机器人在目标区域内绕路,使得多移动机器人能够快速流畅地组成任意队形．实验证明了控制方法的有效性．     

移动机器人编队自修复的切换拓扑控制

针对机器人缺失后的移动机器人编队自修复问题, 构建了结合切换拓扑和交互动力模型的移动机器人编队模型, 通过分析机器人缺失后的拓扑变化情况, 提出了网络切换拓扑控制, 该算法利用递归实现自修复, 并且是收敛的. 通过设计相应的分布式算法, 本文将拓扑控制转化为基于局部交互的递归自修复个体控制, 证明了编队自修复个体控制的稳定性. 最后针对编队任务, 通过仿真验证了切换拓扑控制的有效性, 和其他方法比较具有低恢复时间和低功率消耗的优点.     

多机器人任意队形分布式控制研究

本文针对多智能体协作完成特定任务时难以在全自主控制的前提下协作形成任意队 形和队形向量不易确定的问题，通过由各智能体自主简单的确定自己的队形向量，从理论上 扩展基于队形向量的队形控制原理以生成任意队形，改进机器人的运动方式以提高收敛速度 ，提出一种快速收敛的机器人部队任意队形分布式控制算法．为了解决智能体机器人之间的 冲突问题，提出了一个通信协调模型．仿真实验和实际机器人实验均表明了算法的可行性和 有效性．     

考虑障碍环境下的多机器人编队控制研究

编队和避障控制是机器人路径规划设计中的典型问题,文中提出了将leader—following法和人工势场法相结合的方法,来更好地完成多机器人在未知环境下的编队和避障控制。之前的研究只将leader—following算法用于多机器人的编队控制,而文中提出此方法也可以用于多机器人系统的避障控制。基于leader—following法,多机器人能自动编队并保持队形;而结合人工势场法,多机器人可以保持队形行进,在遇到障碍物的情况下变换队形避障,在避障后恢复原队形,最终到达目标。通过仿真实验证明,该算法实现了多机器人在未知环境下的自动编队和避障,从而证明了leader—following算法可以用于机器人的避障控制。     

快速收敛的机器人部队任意队形分布式控制算法

针对多智能体协作完成特定任务时难以在全自主控制的前提下协作形成任意队形和队形向量不易确定的问题 ,通过由各智能体自主简单的确定自己的队形向量 ,从理论上扩展基于队形向量的队形控制原理以生成任意队形 ,改进机器人的运动方式以提高收敛速度 ,提出一种快速收敛的机器人部队任意队形分布式控制算法 .仿真结果表明 ,该算法可以形成任意队形 ,比现有控制算法的收敛速度快 ,队形收敛所需的时间仅为现有算法的 10 %左右     

A generalized framework of dynamic role assignment for robot formation control

A dynamic role assignment algorithm is proposed in the paper for formation control of multiple mobile robots. The goal of the algorithm is to reassign a role for each robot automatically during a formation is forming or switching. Many formation control systems have been successfully implemented and validated by supporting experimental results. Nevertheless, this research aims at providing an efficient algorithm of role assignment for a class of formation control systems employing the concept of combinational optimization problems. Specifically, by exploring spatial relationship between robots and information of obstacles surrounding the robots, a character cost function is found to represent the degree of difficulty for a robot been assigned a specified role in a formation. Instead of using complex cost minimization procedure, a solution is provided by calculating the largest value of character set fitness, and a new formation is selected for robots accordingly. The developed algorithm is applied to the formation control of a group omni-directional driven robots. Simulation and experimentation are performed with real platform to verify the proposed algorithm and the results show that the performance of the proposed dynamic role assignment algorithm is efficient for robot formation control.     

基于认知模型的室内移动服务机器人人机耦合协同作业机制

针对老年人和残疾人这类特殊用户群体与服务机器人构成的人机智能系统,提出了基于ACT-R(理性思维的适应性控制)认知架构模型的室内移动服务机器人人机耦合协同作业机制.基于ACT-R认知架构对人机一体化室内移动服务机器人人机协同作业系统进行了总体设计,利用简单自然的人机效应通道,设计了基于ACT-R认知架构的人机耦合界面;通过人-机-环境空间感知耦合,提出并建立了室内移动服务机器人人机一体化协同决策作业机制.最后在室内环境下进行移动服务机器人人机协同作业实验,系统安全高效地完成了作业任务,验证了该机制的有效性.     

Robust Formation Control of Multiple Wheeled Mobile Robots

This paper considers formation control of a group of wheeled mobile robots with uncertainty. Decentralized cooperative robust controllers are proposed in two steps. In the first step, cooperative control laws are proposed for multiple kinematic systems with the aid of results from graph theory such that a group of robots comes into a desired formation. In the second step, cooperative robust control laws for multiple uncertain dynamic systems are proposed with the aid of backstepping techniques and the passivity properties of the dynamic systems such that multiple robots comes into a desired formation. Since communication delay is inevitable in cooperative control, its effect on the proposed controllers is analyzed. Simulation results show the effectiveness of the proposed controllers.