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。     

Nash-optimization distributed model predictive control for multi mobile robots formation

This paper investigates the distributed model predictive control (DMPC) problem for multi mobile robots. The distributed system model is obtained by the kinematic model of single mobile robot. By including the coupling terms in the cost function, cooperation between subsystems can be incorporated in the distributed control problem. Then, each robot has its own optimal control problem, and neighboring subsystems can exchange information with one another by using wireless communication. The distributed model predictive control problem is formulated by the local cost function and solved by using Nash-optimization algorithm. The convergence condition of the proposed algorithm is presented. Finally, an illustrative example is given to demonstrate the effectiveness of the proposed method.     

VCS-based motion planning for distributed mobile robots: collision avoidance and formation

This paper addresses decentralized motion planning among a homogeneous set of feedback-controlled mobile robots. It introduces the velocity obstacle, which describes the collision between robot and obstacle, and the hybrid interactive velocity obstacles are designed for collision checking between interacting robots. The (sub)goal selection algorithm is also studied for formation control, then the preferred velocity is designed for robot tracking its desired (sub)goal. Furthermore, the rules for the size regulation of obstacle are presented to avoid conservative motion planning and enhance the safety. Then, we establish a novel Velocity Change Space (VCS), map the velocity obstacles, the desired (sub)goal and the reachable velocity change window before collision in this space, and directly get the new velocity by a multi-objective optimization method. We apply VCS-based motion planning methods to distributed robots, and simulation is used to illustrate the good performances with respect to the un-conservative, foresighted and multi-objective optimal motion planning, especially the successful application in the formation control of the multi-robot system.     

Vision-based formation control of mobile robots

1Introduction Formation control of multiple vehicles,such ascooperative control of a group of mobile robots[1~4]and multiple spacecraft[5,6],has beenrecognized as a keytechnologyfor the future and studied by many researchersin recent years.The various control approaches to multiplevehicle formation reported in the literature can becategorized into three groups:leader following schemes;behavior_based methods;and virtual structure techniques.In the leader following approach[1,2,7],one of thevehi…     

Vision-based formation control of mobile robots

In this paper,a formatio n control algorithm and an obstacle avoidance control algorithm for mobile robots are developed based on a relative motion sensory system such as a pan/tilt camera vision system,without the need for global sensing and communication between robots.This is achieved by e mploying the velocity variation,instead of actual ve locities,as the control inputs.Simulation and experi mental results have demonstrated the effectiveness of the proposed control methods.     

Nonlinear formation control of unicycle-type mobile robots

We investigate formation control of a group of unicycle-type mobile robots at the dynamics level with a little amount of inter-robot communication. A combination of the virtual structure and path-tracking approaches is used to derive the formation architecture. Each individual robot has only position and orientation available for feedback. For each robot, a coordinate transformation is first derived to cancel the velocity quadratic terms. An observer is then designed to globally exponentially/asymptotically estimate the unmeasured velocities. An output feedback controller is designed for each robot. The controller is designed in such a way that the path derivative is left as a free input to synchronize the robots’ motion. Simulations illustrate the soundness of the proposed controller.     

非完整移动机器人的复合编队控制

主要研究了非完整自主机器人之间的队形保持和避障问题,提出了一种新的复合编队控制方法,该方法根据机器人的期望位置在其运动约束区域内外的不同,分别以一种灵活的反馈线性化算法和最优近似目标算法来建立控制规则,并提出了编队环境中存在静态障碍物时的队形控制策略,从而实现多机器人的稳定编队控制．该方法降低了传统线性反馈控制对编队初始误差范围的要求,并且解决了非完整机器人编队的避障问题．实验结果表明了该编队控制方法的可行性和有效性．     

Formations of minimalist mobile robots using local-templates and spatially distributed interactions

In this paper we address the problem of synthesizing simple rules and local interactions at the individual level so that pre-specified complex behavior emerges at the group level of a collection of autonomous mobile agents. Usually, the emergent collective behavior is used to perform certain spatial group-tasks. Specifically, we consider self-assembling of a group of mobile robots into grid, line, and wedge patterns. We introduce the notion of local-templates in which each mobile agent – capable of simple forward/backward movements and a clock-wise/counter clock-wise spin – actively encodes distinctive information into multiple non-overlapping sectorial regions of the surrounding environment in order to form pose-specific virtual links with similar minimalist agents in a local neighborhood. The resulting local patterns around each agent lead to the desired global formation. In order to take mobile robots closer to their biological counterparts, there is a need to further simplify the manner in which they currently perceive their surroundings, communicate with their neighbors, and compute their actions. We have built a robotic platform consisting of four wheeled-mobile robots that are christened as Kinbots. They are similar in principle to Braitenberg Vehicles and use simple perception/interaction/actuation techniques to achieve individual vehicle complexity and produce effective group behavior through cooperation. To validate the proposed approach, we demonstrate a column-formation task in computer simulations and physical experiments. We illustrate an experiment which is representative of various prominent stages in a group-formation task such as formation-achievement, maintenance, and response of formation movement to the presence of obstacles.     

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.     

A distributed multi-agent production planning and scheduling framework for mobile robots

Inspired by the new achievements in mobile robotics having as a result mobile robots able to execute different production tasks, we consider a factory producing a set of distinct products via or with the additional help of mobile robots. This particularly flexible layout requires the definition and the solution of a complex planning and scheduling problem. In order to minimize production costs, dynamic determination of the number of robots for each production task and the individual robot allocation are needed. We propose a solution in terms of a two-level decentralized Multi-Agent System (MAS) framework: at the first, production planning level, agents are tasks which compete for robots (resources at this level); at the second, scheduling level, agents are robots which reallocate themselves among different tasks to satisfy the requests coming from the first level. An iterative auction based negotiation protocol is used at the first level while the second level solves a Multi-Robot Task Allocation (MRTA) problem through a distributed version of the Hungarian Method. A comparison of the results with a centralized approach is presented.     

Cooperative hunting by distributed mobile robots based on local interaction

This paper proposes a distributed control approach called local interactions with local coordinate systems (LILCS)to multirobot hunting tasks in unknown environments, where a team of mobile robots hunts a target called evader, which will actively try to escape with a safety strategy. This robust approach can cope with accumulative errors of wheels and imperfect communication networks. Computer simulations show the validity of the proposed approach.     

CBBR: enabling distributed shared memory-based coordination among mobile robots

Coordinating mobile robots are widely used in commercial and industrial settings to fulfill various tasks. However, to program the coordination among mobile robots is challenging. A coordination framework is needed to shield the programmer from handling low-level details of robot control and communication, while supporting flexible and cost-effective coordination at the same time. The coordination framework should also be able to well coexist with the underlying robot control. To this end, we propose the Coordination-enabled Behavior-Based Robotics (CBBR) framework. CBBR employs Distributed Shared Memory (DSM) to support coordination. The shared memory illusion built by the DSM greatly simplifies the coordination logic. Moreover, the flexible access patterns of the DSM and the rich consistency semantics of the DSM reads and writes enable flexible and cost-effective coordination. With the coordination support from the DSM, CBBR naturally extends the classical Behavior-Based Robotics (BBR) for robot control. From the perspective of robot control using BBR, the shared variables in the DSM act as the logical sensors capturing the status of coordination. The coordination algorithms are encapsulated into coordination behaviors. Thus, the physical environment status and the coordination status may trigger the physical and the coordination behaviors. The scheduling of both types of behaviors integrates coordination into robot control. We conduct a case study to demonstrate the use of CBBR. The performance measurements show the cost-effectiveness of coordinating mobile robots based on CBBR, in terms of time, space, and energy consumption.     

多移动机器人的领航-跟随编队避障控制

针对多移动机器人的编队控制问题,提出了一种结合Polar Histogram避障法的领航-跟随协调编队控制算法。该算法在领航-跟随l-φ编队控制结构的基础上引入虚拟跟随机器人,将编队控制转化为跟随机器人对虚拟跟随机器人的轨迹跟踪控制。结合移动机器人自身传感器技术,在简单甚至复杂的环境下为机器人提供相应的路径运动策略,实现实时导航的目的。以两轮差动Qbot移动机器人为研究对象,搭建半实物仿真平台,进行仿真实验。仿真结果表明:该方法可以有效地实现多移动机器人协调编队和避障控制。     

Teleoperation of a platoon of distributed wheeled mobile robots with predictive display

We propose a novel teleoperation framework for multiple distributed non-holonomic mobile robots (WMR), each equipped with onboard sensing and computing using peer-to-peer communication. One of the WMRs is designated as the leader with the first-person view camera and SLAM, while the other WMRs maintain a certain desired formation relative to their respective fore-running WMR in a distributed manner. For this, we first utilize nonholonomic passive decomposition to split the platoon kinematics into that of the formation-keeping aspect and the collective tele-driving aspect. We then design the controls for these two aspects individually and distribute them into each WMR while incorporating their nonholonomic constraint and distribution requirement. We also propose a novel predictive display, which, by providing the user with the estimated current and predicted future pose of the platoon and future possibility of collision while incorporating the uncertainty inherent to the distribution, can significantly enhance the tele-driving performance. Experiments and user study are also performed.     

未知死区输入非线性系统的双观测器动态面控制

针对一类含死区输入的严格反馈非线性系统,提出基于双观测器的自适应鲁棒控制算法.动态面的每一步设计中,第1观测器即跟踪信号观测器对指令信号进行观测,并得到指令信号的差分信号,消除传统动态面控制中计算复杂问题.第二观测器即扰动观测器在线估计高阶动态面控制系统中每一步的不确定模型,与跟踪信号观测器实现双反馈控制,提高控制效果...     

非完整轮式机器人的鲁棒同步编队跟踪及镇定控制

本文研究了受到建模不确定性影响和输入限制的非完整轮式机器人的同步编队跟踪和编队镇定问题.首先,基于领航–跟随策略,确定了编队构型的数学表达形式.其次,通过定义含有辅助控制量的跟踪误差,设计了一种具有统一结构的分布式运动学控制器,可使跟随者实现对复杂期望轨迹的跟踪,包括时变轨迹和固定点等.然后,针对建模不确定性影响和输入限制,基于反步法、模糊控制方法和Lyapunov控制理论,设计了一种饱和动力学控制器,使得系统的闭环跟踪误差全局收敛至零点附近有界领域内.最后,通过对比仿真实验,验证了本文控制方法的有效性.     

Model predictive control for trajectory-tracking and formation of wheeled mobile robots

Neural Computing and Applications - Model predictive control (MPC) naturally guarantees optimal transient process and constraints satisfaction. Most mature MPC theories concern with linear...     

Formation control of multiple mecanum-wheeled mobile robots with physical constraints and uncertainties

Aiming at the formation control of multiple Mecanum-wheeled mobile robots (MWMRs) with physical constraints and model uncertainties, a novel robust control scheme that combines model predictive control (MPC) and extended state observer-based adaptive sliding mode control (ESO-ASMC) is proposed in this paper. First, a linear MPC strategy is proposed to address the motion constraints of MWMRs, which can transform the robot formation model based on leader-follower into a constrained quadratic programming (QP) problem. The QP problem can be solved iteratively online by a delay neural network (DNN) to obtain the optimal control velocity of the follower robot. Then, to address the input saturation constraints, model uncertainties and unknown disturbances in the dynamic model, an improved ESO-ASMC is proposed and compared with the robust adaptive terminal sliding mode control (RATSMC) and the conventional sliding mode control (SMC) to prove the effectiveness. The proposed scheme, considering the optimal control velocity obtained by the kinematics controller as the given desired velocity of the dynamics controller, can implement precise formation control, while solving various physical constraints of the robot, and eliminating the effects of model uncertainties and disturbances. Finally, through a comparative simulation case, the effectiveness and robustness of the proposed method are verified.

     

Linear estimation of the physical odometric parameters for differential-drive mobile robots

In this paper a calibration technique aimed at identifying the odometric parameters of differential-drive mobile robots is proposed. The algorithm is based on two successive least-squares estimations based on the continuous-time kinematic equations of motion; the time-discretization error, thus, is avoided. The use of the least-squares technique is made possible by working on a linear mapping between the unknowns and the measurements and is not the result of a linearization. Another advantage of the proposed technique is that no specific path is required. The basic technique makes use of video-camera measurements and absolute position readings of the wheels’ encoders; the use of different sensors and measurements of the wheels velocities is also discussed. Experimental results with a mobile robot Khepera II confirm the effectiveness of the proposed technique.

Navigation strategies for multiple autonomous mobile robots moving in formation

The problem of deriving navigation strategies for a fleet of autonomous mobile robots moving in formation is considered. Here each robot is represented by a particle with a spherical effective spatial domain and a specified cone of visibility. The global motion of each robot in the world space is described by the equations of motion of the robot's center of mass. First, methods for formation generation are discussed. Then, simple navigation strategies for robots moving in formation are derived. A sufficient condition for the stability of a desired formation pattern for a fleet of robots each equipped with the navigation strategy based on nearest neighbor tracking is developed. The dynamic behavior of robot fleets consisting of three or more robots moving in formation in a plane is studied by means of computer simulation.