移动机器人多传感器信息融合技术述评

多传感器信息融合技术是目前移动机器人领域的研究热点。详细阐述了多传感器信息融合技术在移动机器人领域中的应用与研究进展,尤其对多传感器信息融合实现方法进行了深入的探讨。指明了移动机器人领域中多传感器信息融合技术未来的发展方向。     

多移动机器人协作任务的分布式控制系统

本文以多移动机器人协作执行围捕任务为背景，探讨了多机器人系统行为层规划及任务层中的任务分解和分配问题，提出了一种能有效降低计算量的编队中子任务的分配方法．为多移动机器人提供了一种在不确定环境中，动态变化的协作任务下进行基于传感器信息和通信信息的在线路径规划的方法．     

自主微小型移动机器人的协作学习

自主微小型移动机器人的协作学习研究是多智能体机器人系统理论的主要研究方向。因为单个微小型移动机器人能力有限，所以机器人之间的协作在某些重要的基础工业和生物医学领域方面显得非常重要。该文介绍了几种用于协作学习的方法并且比较了它们之间的优点和缺点。最后，简要介绍了一些研究工作。     

移动机器人技术研究现状与未来

本文综述了智能移动机器人技术的历史、研究现状及未来展望．对移动机器人的导 航和定位、多传感器融合等技术进行了较为详细的分析，指出了优点与不足．同时对仿生机 器人、多机器人系统与机器人足球等移动机器人技术，做了进一步的分析．     

多移动机器人的智能协作与导航

论文将从应用角度设计机器人智能协作和导航系统。主要技术包括:利用多MobileAgent模型实现多移动机器人的智能协作;设计KQML(知识查询和操作语言)来实现移动机器人的交流;利用GSM(移动通信系统)网解决多移动机器人的通讯问题;基于GPS(全球定位系统)、GIS(地理信息系统)系统实现导航。该研究结果适用于广域的DAI(分布式人工智能)领域和AIS(自主式智能系统)。     

室外智能移动机器人的发展及其关键技术研究

室外智能移动机器人有着广泛的应用前景,是机器人研究中的热点之一．本文分析 了在室外移动机器人发展中有着代表意义的几个典型系统,进而论述了室外移动机器人研究 中的若干关键技术的研究现状及发展水平．这些关键技术包括移动机器人的控制体系结构、 机器人视觉信息的实时处理技术、车体的定位系统、多传感器信息的集成与融合技术以及路 径规划技术与车体控制技术等．     

智能算法在机器人路径规划中的应用研究

移动机器人技术研究中的一个重要领域是路径规划技术。综述了智能算法在移动机器人路径规划技术中的发展现状,指出了各种方法的优点与不足。最后对移动机器人路径规划技术的发展趋势进行了展望。     

多移动机器人系统个体控制体系结构

本文面向多移动机器人系统,提出了一种适合于移动机器人个体的分层式体系结构, 包括系统监控层、协作规划层和行为控制层三个层次．其中系统监控层主要实现人对系统的 实时监控功能;协作规划层在与其它机器人相应层的交互过程中建立系统的分层式组织形式 ,合理快速地完成任务的分解和分配,实现了机器人之间的任务级协作;行为控制层主要采 用基于行为的方法实现具体的运动控制．该结构满足了移动机器人渐趋复杂的应用环境和日 益增大的系统规模的要求．     

基于粒子滤波器的移动机器人定位和地图创建研究进展

首先，对粒子滤波器的原理和研究进展进行了综述．然后，介绍了基于粒子滤波器的移动机器人定位研究进展．其次，给出了粒子滤波器在移动机器人地图创建领域的最新成果．最后，对粒子滤波器在移动机器人研究领域的未来发展方向进行了展望．     

移动机器人路径规划技术的现状与发展

移动机器人技术是近年来的研究热点，路径规划技术是移动机器人技术研究中的一个重要领域。路径规划分为基于模型的环境已知的全局路径规划和基于传感器的环境未知的局部路径规划。该文详细地叙述了移动机器人路径规划技术的分类和发展现状，全局路径规划和局部路径规划中的各种方法，具体地分析了各种方法的算法过程，并指出了各种方法的优缺点，以及各种方法的改进的办法，最后对移动机器人路径规划技术的未来的发展趋势进行了展望。     

Distributed Consensus of Multiple Nonholonomic Mobile Robots

Consensus problems of multiple nonholonomic mobile robots are considered in this paper. These problems are simplified into consensus problems of two subsystems based on structure of nonholonomic mobile robots. Linear distributed controllers are constructed respectively for these two subsystems thanks to the theory of nonautonomous cascaded systems. Consensus of multiple nonholonomic mobile robots has been realized using the methodology proposed in this paper no matter whether the group reference signal is persistent excitation or not. Different from previous research on cooperative control of nonholonomic mobile robots where the consensus problem under persistent exciting reference has received a lot of attention, this paper reports the first consensus result for multiple nonholonomic mobile robots whose group reference converges to zero. Simulation results using Matlab illustrate the effectiveness of the proposed controllers in this paper.      

基于博弈论的多移动机器人聚集任务路径规划

针对多移动机器人聚集任务的路径规划,建立系统多目标优化数学模型,研究基于博弈论的求解方法。将n个机器人视为博弈的n方,建立Nash均衡博弈模型和共谋合作博弈模型,结合进化策略,对多移动机器人的运动协调进行研究。仿真实验结果表明,博弈分析方法可有效解决多机器人的协调路径规划问题。     

Interaction dynamics of multiple mobile robots with simple navigation strategies

The global dynamic behavior of multiple interacting autonomous mobile robots with simple navigation strategies is studied. Here, the effective spatial domain of each robot is taken to be a closed ball about its mass center. It is assumed that each robot has a specified cone of visibility such that interaction with other robots takes place only when they enter its visibility cone. Based on a particle model for the robots, various simple homing and collision-avoidance navigation strategies are derived first. Then, an analysis of the dynamical behavior of the interacting robots in unbounded spatial domains is made. The article concludes with the results of computer simulation studies of two or more interacting robots.     

Finite-time tracking control for multiple non-holonomic mobile robots based on visual servoing

This paper investigates finite-time tracking control problem of multiple non-holonomic mobile robots via visual servoing. It is assumed that the pinhole camera is fixed to the ceiling, and camera parameters are unknown. The desired reference trajectory is represented by a virtual leader whose states are available to only a subset of the followers, and the followers have only interaction. First, the camera-objective visual kinematic model is introduced by utilising the pinhole camera model for each mobile robot. Second, a unified tracking error system between camera-objective visual servoing model and desired reference trajectory is introduced. Third, based on the neighbour rule and by using finite-time control method, continuous distributed cooperative finite-time tracking control laws are designed for each mobile robot with unknown camera parameters, where the communication topology among the multiple mobile robots is assumed to be a directed graph. Rigorous proof shows that the group of mobile robots converges to the desired reference trajectory in finite time. Simulation example illustrates the effectiveness of our method.     

Optimal path planning of mobile robots for sample collection

In this paper, the problem of path planning for sample collection using single or multiple mobile robots such as Mars rovers is formulated as a mathematical optimization problem involving a performance metric based on the scientific values of the collected rock and soil samples. The posed optimization problem is NP‐hard and more complex than the well‐known Traveling Salesman Problem. Algorithms are proposed for obtaining near‐optimal solutions for both single and multiple robots. Their application is illustrated using real Mars surface data. The dependence of the optimal performance on the number of mobile robots is studied numerically. © 2004 Wiley Periodicals, Inc.     

Concurrent localization of multiple robots

A concurrent localization method for multiple robots using ultrasonic beacons is proposed. This method provides a high-accuracy solution using only low-price sensors. To measure the distance of a mobile robot from a beacon at a known position, the mobile robot alerts one beacon to send out an ultrasonic signal to measure the traveling time from the beacon to the mobile robot. When multiple robots requiring localization are moving in the same block, it is necessary to have a schedule to choose the measuring sequence in order to overcome constant ultrasonic signal interference among robots. However, the increased time delay needed to estimate the positions of multiple robots degrades the localization accuracy. To solve this problem, we propose an efficient localization algorithm for multiple robots, where the robots are in groups of one master robot and several slave robots. In this method, when a master robot calls a beacon, all the group robots simultaneously receive an identical ultrasonic signal to estimate their positions. The effectiveness of the proposed algorithm has been verified through experiments.     

A* search algorithm applied to a Chinese chess game

This article presents an A* search algorithm to be applied to path planning in a Chinese chess game, and uses multiple mobile robots to present the scenario. The mobile robots have a cylindrical shape, and their diameter, height, and weight are 8 cm, 15 cm, and 1.5 kg, respectively. The controller of the mobile robots is a MCS-51 chip. We play the Chinese chess game using multiple mobile robots according to the evaluation algorithm of the game, and calculate the displacement by the encoder of a DC servomotor. The A* search algorithm can solve the shortest-path problem for the mobile robots from the starting point to the target point on the chess board. The simulated results found the shortest path for the mobile robots (chess pieces) moving to target points from their starting points in a collision-free environment. Finally, we implemented the experimental results on a Chinese chess board using mobile robots. Users can play the Chinese chess game using the supervising computer via a wireless RF interface. The scenario of the feedback of the Chinese chess game to the user interface uses an image system.     

Motion-based identification of multiple mobile robots using trajectory analysis in a well-configured environment with distributed vision sensors

Networked mobile robots are able to determine their poses (i.e., position and orientation) with the help of a well-configured environment with distributed sensors. Before localizing the mobile robots using distributed sensors, the environment has to have information on each of the robots?? prior knowledge. Consequently, if the environment does not have information on the prior knowledge of a certain mobile robot then it will not determine its current pose. To solve this restriction, as a preprocessing step for indoor localization, we propose a motion-based identification of multiple mobile robots using trajectory analysis. The proposed system identifies the robots by establishing the relation between their identities and their positions, which are estimated from their trajectories related to each of the paths generated as designated signs. The primary feature of the proposed system is the fact that networked mobile robots are quickly and simultaneously able to determine their poses in well-configured environments. Experimental results show that our proposed system simultaneously identifies multiple mobile robots, and approximately estimates each of their poses as an initial state for autonomous localization.     

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.     

Coordination of multiple mobile robots with limited communication range in pursuit of single mobile target in cluttered environment

This paper addresses the problem of coordinating multiple mobile robots in searching for and capturing a mobile target, with the aim of reducing the capture time. Compared with the previous algorithms, we assume that the target can be detected by any robot and captured successfully by two or more robots. In this paper, we assume that each robot has a limited communication range. We maintain the robots within a mobile network to guarantee the successful capture. In addition, the motion of the target is modeled and incorporated into directing the motion of the robots to reduce the capture time. A coordination algorithm considering both aspects is proposed. This algorithm can greatly reduce the expected time of capturing the mobile target. Finally, we validate the algorithm by the simulations and experiments.