群机器人学

介绍了群机器人学的含义、特点和发展现状,分析了研究群机器人系统的相关理论和方法,总结了群机器人学研究的主要内容,并指出其发展趋势。     

Cooperative Mobile Robotics: Antecedents and Directions

There has been increased research interest in systems composed of multiple autonomous mobile robots exhibiting cooperative behavior. Groups of mobile robots are constructed, with an aim to studying such issues as group architecture, resource conflict, origin of cooperation, learning, and geometric problems. As yet, few applications of cooperative robotics have been reported, and supporting theory is still in its formative stages. In this paper, we give a critical survey of existing works and discuss open problems in this field, emphasizing the various theoretical issues that arise in the study of cooperative robotics. We describe the intellectual heritages that have guided early research, as well as possible additions to the set of existing motivations.     

On the potential contributions of hybrid intelligent approaches to Multicomponent Robotic System development

The area of cognitive or intelligent robotics is moving from the single monolithic robot control and behavior problem to that of controlling robots with multiple components or multiple robots operating together, and even collaborating, in dynamic and unstructured environments. This paper introduces the topic and provides a general overview of the current state of the field of Multicomponent Robotic Systems focusing on providing some insights into where Hybrid Intelligent Systems could provide key contributions to its advancement. Thus, the aim is to identify prospective research areas and to try to delimit the field from the point of view of the following essential problem: how to coordinate multiple robotic elements in order to perform useful tasks.     

Aspects of non-cartesian robotics

Non-Cartesian robotics, which began with the introduction of subsumption architecture by Rodney Brooks, now encompasses a wide range of robotics that do not follow traditional cartesian principles in the running of a robot. The new field is sometimes called biorobotics as it draws its guiding principles from biology, physiology, behavioural sciences, genetics and theories of evolution, brain sciences, genetics and theories of evolution, brain sciences, ethology, psychology, and other related non-engineering disciplines. The difference in principles of operation, however, has roots deeper in the philosophical underpinnings of the way we view controlling artifacts and the concept of control itself when it is contrasted against the concept of autonomy. Realization of increasingly higher levels of autonomy is routinely demanded today not only in industry where most robotic applications occur, but also in areas closer to our daily life where a gradual but steady increase in service applications of robotics is observed. This paper introduces the concept of non-Cartesian robotics as an antithesis to conventional (Cartesian) robotics and describes various aspects of this new way of running a robotic system. This work was presented, in part, at the International symposium on Artificial Life and Robotics, Oita, Japan, February 18–20, 1996     

生物交哺行为启发的群体机器人搜集行为研究

为了提高群体机器人系统的整体性能,受生物系统中普遍存在的交哺现象的启发,在原来多机器人系统的基本行为的基础上,提出了一种引入交哺行为的多机器人协作机制。机器人依靠有限的感知能力和局部交互功能,以自组织方式执行目标搜集任务。机器人的内部状态变量反映其执行任务的情况以及对环境和其他机器人的评价。比较机器人的内部状态变量,可以判断是否需要交哺和交哺的方向性。主要目的是减少机器人之间的冲突,降低系统能量消耗的同时,提高机器人搜集目标的效率。最后通过计算机仿真实验以及与其他多机器人协作方法比较,分析该方法对提高系统性能的有效性。     

High Precision Formation Control of Mobile Robots Using Virtual Structures

A key problem in cooperative robotics is the maintenance of ageometric configuration during movement. To address this problem, theconcept of a Virtual Structure isintroduced. Using this idea, a general control strategy is developedto force an ensemble of robots to behave as if they were particlesembedded in a rigid structure. The method was instantiated and testedusing both simulation and experimentation with a set of 3differential drive mobile robots. Results are presented thatdemonstrate that this approach is capable of achieving high precisionmovement that is fault tolerant and exhibits graceful degradation ofperformance. In addition, this algorithm does not require leaderselection as in other cooperative robotic strategies. Finally, themethod is inherently highly flexible in the kinds of geometricformations that can be maintained.     

切换拓扑下群系统保性能编队形成问题优化控制方法

针对群系统编队形成问题,提出一种切换拓扑下保性能的优化控制方法.首先,建立保性能编队形成问题的数学描述,设计编队控制协议;其次,通过变量代换,给出群系统实现时变编队的充分条件,借助李雅普诺夫方法分析系统的稳定性;再次,通过求解线性矩阵不等式,设计编队控制器,给出群系统性能上界值的数学表达形式.最后,通过仿真实验验证了所提控制方法的有效性.     

Artificial moment method for swarm robot formation control

The purpose of this paper is to develop a general control method for swarm robot formation control. Firstly, an attraction-segment leader-follower formation graph is presented for formation representations. The model of swarm robot systems is described. According to the results and two kinds of artificial moments defined as leader-attraction moment and follower-attraction moment, a novel artificial moment method is proposed for swarm robot formation control. The principle of the method is introduced and the motion controller of robots is designed. Finally, the stability of the formation control system is proved. The simulations show that both the formation representation graph and the formation control method are valid and feasible.     

Simulation and control of distributed robot search teams

This article describes the simulation of distributed autonomous robots for search and rescue operations. The simulation system is utilized to perform experiments with various control strategies for the robot team and team organizations, evaluating the comparative performance of the strategies and organizations. The objective of the robot team is to, once deployed in an environment (floor-plan) with multiple rooms, cover as many rooms as possible. The simulated robots are capable of navigation through the environment, and can communicate using simple messages. The simulator maintains the world, provides each robot with sensory information, and carries out the actions of the robots. The simulator keeps track of the rooms visited by robots and the elapsed time, in order to evaluate the performance of the robot teams. The robot teams are composed of homogenous robots, i.e., identical control strategies are used to generate the behavior of each robot in the team. The ability to deploy autonomous robots, as opposed to humans, in hazardous search and rescue missions could provide immeasurable benefits.     

Particle swarm-based olfactory guided search

This article presents a new algorithm for searching odour sources across large search spaces with groups of mobile robots. The proposed algorithm is inspired in the particle swarm optimization (PSO) method. In this method, the search space is sampled by dynamic particles that use their knowledge about the previous sampled space and share this knowledge with other neighbour searching particles allowing the emergence of efficient local searching behaviours. In this case, chemical searching cues about the potential existence of upwind odour sources are exchanged. By default, the agents tend to avoid each other, leading to the emergence of exploration behaviours when no chemical cue exists in the neighbourhood. This behaviour improves the global searching performance. The article explains the relevance of searching odour sources with autonomous agents and identifies the main difficulties for solving this problem. A major difficulty is related with the chaotic nature of the odour transport in the atmosphere due to turbulent phenomena. The characteristics of this problem are described in detail and a simulation framework for testing and analysing different odour searching algorithms was constructed. The proposed PSO-based searching algorithm and modified versions of gradient-based searching and biased random walk-based searching strategies were tested in different environmental conditions and the results, showing the effectiveness of the proposed strategy, were analysed and discussed. Lino Marques is an auxiliary professor in the Department of Electrical Engineering, University of Coimbra, and he is a researcher in the Institute for Systems and Robotics (ISR-UC). He received his Licenciatura, MSc. and Ph.D. degrees in Electrical Engineering from the University of Coimbra, Portugal. His main research interests include embedded systems, mechatronics, robotics for risky environments, optical range sensors, artificial olfaction systems and mobile robot olfaction. Urbano Nunes is an associate professor of the University of Coimbra and a researcher of the Institute for Systems and Robotics (ISR-UC), where he has been involved in research and teaching since 1983. He received his Licenciatura and Ph.D. degrees in Electrical Engineering from the University of Coimbra, Portugal, in 1983 and 1995, respectively. He is the coordinator of the Mechatronics Laboratory of ISR-UC, and had been responsible for several funded projects in the areas of mobile robotics and intelligent vehicles. His research interests include mobile robotics, intelligent vehicles, and mechatronics. Professor Urbano Nunes serves on the Editorial Board of the Journal on Machine Intelligence and Robotic Control, and currently he is co-chair of the IEEE RAS TC on Intelligent Transportation Systems. Currently he is the Program Chair of the IEEE ITSC2006. He has served as General Co-Chair of ICAR 2003 and as member of several program committees of international conferences. Aníbal T. De Almeida graduated in Electrical Engineering, University of Porto, 1972, and received a Ph.D. in Electrical Engineering, from Imperial College, University of London, 1977. Currently he is a Professor in the Department of Electrical Engineering, University of Coimbra, and he is the Director of the Institute of Systems and Robotics since 1993. Professor De Almeida is a consultant of the European Commission Framework Programmes. He is the co-author of five books and more than one hundred papers in international journals, meetings and conferences. He has coordinated several European and national research projects.     

Robust Path Planning for Non-Holonomic Robots

This paper deals with mobile robots path planning. We decompose the problem in three parts. In the first part, we describe a modeling method based on a configuration space discretization. Each model element is built following a particular structure which is easy to handle, as we will show. We describe the methodologies and the algorithms allowing to build the model. In the second part, we propose a path-planning application for a non-holonomic robot in configuration space. In the third part, we modify the path in order to be robust according to the control errors.     

Path planning for a manipulator with constraints on orientation

This paper discusses the work undertaken at the U.K. National Advanced Robotics Research Centre in the area of path planning. Experiments have been undertaken with the Best First Planner (BFP) and Random Path Planner (RPP) algorithms developed at Stanford University by Barraquand and Latombe. These look particularly suitable for solving a wide range of motion planning problems and for providing the basic mechanism for path planning in an advanced robotic architecture. From this basic mechanism higher level functional primitives have been developed to enable paths to be planned with a pre-defined orientation of the end effector at the goal location or maintaining an orientation throughout the whole path. These functions are achieved through placing additional constraints on the search through configuration space and modifying the workspace potential.     

大规模固定翼无人机集群编队控制方法

针对大规模固定翼无人机集群的编队控制问题,提出一种分层分组控制方案.首先,设计一种分布式的无人机集群分层分组控制架构,将集群内所有无人机分成若干独立且不相交的群组,并在群组内分别形成\"长机层\"和\"僚机层\";其次,对各群组内的长机设计协同路径跟随控制律,使长机收敛到各自期望路径上的虚拟目标点,并通过对各虚拟目标点的协调控...     

Current research in multirobot systems

As research progresses in distributed robotic systems, more and more aspects of multirobot systems are being explored. This article describes advances in multirobot systems, and surveys the current state of the art. The focus is principally on research that has been demonstrated in physical robot implementations. I have identified eight primary research topics within multirobot systems—biological inspirations, communication, architectures, localization/mapping/exploration, object transport and manipulation, motion coordination, reconfigurable robots, and learning—and discuss the current state of research in these areas. As I describe each research area, I identify some key open issues in multirobot team research, and conclude by identifying several additional open research issues in distributed mobile robotic systems. This work was presented, in part, at the Seventh International Symposium on Artificial Life and Robotics, Oita, Japan, January 16–18, 2002     

非合作群系统编队问题的纳什均衡优化控制方法

针对群系统编队控制问题,提出了一种分布式非合作优化控制方法。建立了群系统编队控制问题的数学模型和个体代价函数,采用一致性策略设计了分布式控制协议框架。基于纳什均衡理论设计了带参控制协议框架。给出了群系统形成时变编队的充要条件,并利用李雅普诺夫方法分析了系统的稳定性和参数选取方法。仿真实验验证了方法的有效性,以及在优化性能和收敛速度方面的改进效果。     

一种求解最少时间最小费用路问题的算法

针对同时带有弧费用和弧时间的运输网络中最少时间最小费用路的问题,本文提出了一种算法。该算法能高效地求出此类网络中从源节点到目的节点的双目标最短路（最少时间最小费用路）。实例计算表明,该算法是有效的。     

集群机器人研究综述

首先,给出了集群机器人的定义与基本特征,概括了相对于传统多机器人控制方法的优势.然后,总结了集群机器人的主要设计与分析方法.将集群机器人研究归纳为空间组织、集群导航、集群决策以及其他集群行为等4类,综述了各类别近十年的主要研究成果.最后,分析总结了当前集群机器人研究面临的挑战与关键科学问题,并对未来发展方向进行了展望.     

考虑容量和时延约束的网络端端可靠性研究

早期对网络可靠性的研究主要是以连通性为网络功能来研究的,并没有考虑网络完成用户需求的能力。综合考虑网络容量以及时延约束,在网络部件（节点或边）的容量约束下改变网络的拓扑结构,通过改进的节点遍历法,将满足用户时延约束的有效最小路集输出,通过BDD算法对有效路集进行不交化,得出网络端端可靠度的精确值。算法采用Matlab程序实现,为评估加权网络可靠性提供了一种新方法。