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1.
张津华  田峰 《微机发展》2013,(6):109-112,121
针对放大转发无线协作中继网络,文中提出了一种改进的基于拍卖理论的分布式功率分配算法。该算法中用户以最大化自身的效用为目标,通过向中继节点发送投标量的方式购买中继功率,中继节点根据价格更新策略指定合理的中继价格,并根据用户的投标量进行功率分配。改进算法重新定义了用户节点的效用函数,降低了算法的复杂度。文中分析了单中继无线协作网络中继功率的分配过程以及用户的最佳投标量。仿真结果表明,该改进算法收敛速度快,中继节点覆盖范围大,有效提高了网络的传输速率。  相似文献   

2.
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  相似文献   

3.
多机器人协作是当前机器人学和人工智能的研究热点之一。针对多机器人系统中的任务分配问题,提出一种基于集中式和分布式的混合式控制结构,在机器人得到传感器信息后,使用合同网协议来完成任务分配,最终实现多机器人协作。在player/stage仿真平台进行的实验表明:多机器人系统能够有效地进行任务分配与协作,提出的解决方案是行之有效的。  相似文献   

4.
随着通信技术、传感技术和控制技术的发展,多机器人系统因其良好的鲁棒性,灵活性和可扩展性,在理论研究和工程应用中展现出广阔的前景.区域覆盖是多机器人系统典型应用之一,目前多采用维诺图分割覆盖区域并使用Lloyd算法控制机器人前往维诺图细胞中心.然而传统Lloyd算法存在不平衡问题,即机器人覆盖区域面积大小不一,这降低了多机器人协作效率.针对平均区域覆盖问题,本文提出了一种改进的Lloyd算法,将维诺图中各细胞面积方差引入Lloyd算法,相应地设计了基于梯度下降法的分布式控制器.本文方法降低了维诺图中各细胞面积的方差,改善了Lloyd算法的平衡性,能够实现整个区域面积更为平均的划分与机器人对该区域的覆盖.数值仿真与无人机实物实验均验证了改进算法的有效性.  相似文献   

5.
研究了一种在动态环境下的新型协作多机器人路径规划算法。采用集中式与分布式相结合的多机器人系统体系结构,弥补了在分布式环境下的全局性较差和在集中式环境下的实时性较差等不足。在此基础上,通过融合免疫协同进化算法与人工势场法解决全局路径规划与局部路径规划问题,以有效提高机器人的全局协调能力及自适应水平。仿真实验证明了所提算法在动态环境下实现的可行性与有效性。  相似文献   

6.
多机器人系统在联合搜救、智慧车间、智能交通等领域得到了日益广泛的应用。目前,多个机器人之间、机器人与动态环境之间的路径规划和导航避障仍需依赖精确的环境地图,给多机器人系统在非结构环境下的协调与协作带来了挑战。针对上述问题,本文提出了不依赖精确地图的分布式异构多机器人导航避障方法,建立了基于深度强化学习的多特征策略梯度优化算法,并考虑了人机协同环境下的社会范式,使分布式机器人能够通过与环境的试错交互,学习最优的导航避障策略;并在Gazebo仿真环境下进行了最优策略的训练学习,同时将模型移植到多个异构实体机器人上,将机器人控制信号解码,进行真实环境测试。实验结果表明:本文提出的多特征策略梯度优化算法能够通过自学习获得最优的导航避障策略,为分布式异构多机器人在动态环境下的应用提供了一种技术参考。  相似文献   

7.
一种多机器人任务规划算法及其系统实现   总被引:1,自引:0,他引:1  
针对多机器人任务规划问题,提出了一种蚁群集中式规划方法,建立了任务分配和路由规划的蚁群算法描述模型,并利用局部搜索策略改进了蚁群算法分配效果,实现了多机器人集中任务规划系统.利用该系统平台,进行了大量的实验分析.结果表明,蚁群算法能有效解决多机器人任务规划问题,为多机器人协作机制提供了新思路.  相似文献   

8.
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,比现有控制处法的收敛速度快,队形收敛所需的时间仅为现有算法的10%左右。  相似文献   

9.
多智能体协作完成特定任务是多智能体领域的一个基本问题 .本文结合多智能体理论和基于队形向量的队形控制算法 ,提出了一种改进的基于队形向量的控制机器人部队形成任意形状的队形的分布式队形控制算法 DFC.仿真的实验结果证明 ,该算法比现有算法功能完备 ,控制简单  相似文献   

10.
基于蚁群算法的多机器人协作策略   总被引:24,自引:2,他引:24  
丁滢颍  何衍  蒋静坪 《机器人》2003,25(5):414-418
蚁群算法是一种通过对蚂蚁社会长期观察得来的优化算法.它建立在蚁群的一种叫“外激励”的联系方式上,对解决一些分布式控制问题和复杂的优化问题十分有效.将“外激励”这一概念引入多机器人系统中,设计了一种基于蚁群算法的多机器人协作策略.这一策略可以解决多机器人系统在未知环境工作时所面临的一项艰巨的任务:自主协作规划.定义了多机器人系统在未知环境中可能存在的一个问题:任务死锁;将衰减因子引入协作算法,以防止任务死锁的发生;通过仿真验证了算法的性能.  相似文献   

11.
This paper proposes a reliable and efficient multi-robot coordination algorithm to accomplish an area exploration task given that the communication range of each robot is limited. This algorithm is based on a distributed bidding model to coordinate the movement of multiple robots. Two measures are developed to accommodate the limited-range communications. First, the distances between robots are considered in the bidding algorithm so that the robots tend to stay close to each other. Second, a map synchronization mechanism, based on a novel sequence number-based map representation and an effective robot map update tracking, is proposed to reduce the exchanged data volume when robot subnetworks merge. Simulation results show the effectiveness of the use of nearness measure, as well as the map synchronization mechanism. By handling the limited communication range we can make the coordination algorithms more realistic in multi-robot applications.  相似文献   

12.
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.  相似文献   

13.
基于行为的多机器人任意队形的控制   总被引:4,自引:0,他引:4  
张磊  秦元庆  孙德宝  肖俊 《控制工程》2005,12(2):174-176
针对多机器人队形优化控制任务,提出一种快速收敛的机器人任意队形的控制算法。各机器人在奔向目标的过程中以队形的几何中心为参考点,自主地确定队形向量。在保持队形的过程中,采用动态死区法,通过对各个区域大小的控制达到对机器人速度的控制,维持规定队形。采用反向避碰、切线避障,根据各机器人间的位置,引入整体队形向量约束机器人的方向,达到机器人整体队形的方向与机器人运动方向一致。实验结果表明该算法可以快速、有效地完成各种编队任务。  相似文献   

14.
李静  席裕庚 《控制工程》2007,14(5):540-543
针对多移动机器人全局静态环境未知的路径规划问题,采用了一个全局性能指标,在保证路径较优的情况下,最小化机器人的停顿时间,提出机器人之间以修正局部路径为主的协调策略。根据多机器人滚动路径算法的原理,设计了改进的多机器人分布式滚动路径规划算法。在已有仿真系统上进行测试,比较了所提出的协调策略与改变机器人移动速度协调策略对性能指标的影响。仿真结果表明,静态环境未知情况下,机器人可以并行规划各自的协调路径。  相似文献   

15.
在拥挤环境中,由于障碍物的边界形状比较复杂,需要使用广义Voronoi图表示空间环境。且在多移动机器人的运动规划过程中,需要协调多个机器人的运动,必须得到Voronoi图通道的宽度。为此提出了一种计算拥挤障碍物环境中生成的广义Voronoi图及其通道宽度的算法。并在生成的Voronoi图上利用A*算法对多个机器人进行路径规划,并利用分布式方法协调多个机器人运动。对协调两个机器人运动的过程进行了仿真,仿真结果表明利用提出的算法生成的具有通道宽度信息的Voronoi图能够满足多移动机器人运动规划的需要。  相似文献   

16.
This paper studies connectivity maintenance of robotic networks that communicate at discrete times and move in continuous space. We propose a distributed coordination algorithm that allows the robots to decide whether a desired collective motion breaks connectivity. We build on this procedure to design a second coordination algorithm that allows the robots to modify a desired collective motion to guarantee that connectivity is preserved. These algorithms work under imperfect information caused by delays in communication and the robots’ mobility. Under very outdated information, the proposed algorithms might prevent some or all of the robots from moving. We analyze the correctness of our algorithms by formulating them as games against a hypothetical adversary who chooses system states consistent with observed information. The technical approach combines tools from algebraic graph theory, linear algebra, and nonsmooth analysis.  相似文献   

17.
Many collaborative multi-robot application domains have limited areas of operation that cause spatial conflicts between robotic teammates. These spatial conflicts can cause the team's productivity to drop with the addition of robots. This phenomenon is impacted by the coordination methods used by the team-members, as different coordination methods yield radically different productivity results. However, selecting the best coordination method to be used by teammates is a formidable task. This paper presents techniques for creating adaptive coordination methods to address this challenge. We first present a combined coordination cost measure, CCC, to quantify the cost of group interactions. Our measure is useful for facilitating comparison between coordination methods, even when multiple cost factors are considered. We consistently find that as CCC values grow, group productivity falls. Using the CCC, we create adaptive coordination techniques that are able to dynamically adjust the efforts spent on coordination to match the number of perceived coordination conflicts in a group. We present two adaptation heuristics that are completely distributed and require no communication between robots. Using these heuristics, robots independently estimate their combined coordination cost (CCC), adjust their coordination methods to minimize it, and increase group productivity. We use simulated robots to perform thousands of experiment trials to demonstrate the efficacy of our approach. We show that using adaptive coordination methods create a statistically significant improvement in productivity over static methods, regardless of the group size.  相似文献   

18.
《Advanced Robotics》2013,27(1-2):1-23
This paper presents a system for the coordination of aerial and ground robots for applications such as surveillance and intervention in emergency management. The overall system architecture is described. An important part for the coordination between robots is the task allocation strategy. A distributed market-based algorithm, called S + T, has been developed to solve the multi-robot task allocation problem in applications that require cooperation among the robots to accomplish all the tasks. Using this algorithm, robots can provide transport and communication relay services dynamically to other robots during the missions. Moreover, the paper presents a demonstration with a team of heterogeneous robots (aerial and ground) cooperating in a mission of fire detection and extinguishing.  相似文献   

19.
In this paper, a practically viable approach for conflict free, coordinated motion planning of multiple robots is proposed. The presented approach is a two phase decoupled method that can provide the desired coordination among the participating robots in offline mode. In the first phase, the collision free path with respect to stationary obstacles for each robot is obtained by employing an A* algorithm. In the second phase, the coordination among multiple robots is achieved by resolving conflicts based on a path modification approach. The paths of conflicting robots are modified based on their position in a dynamically computed path modification sequence (PMS). To assess the effectiveness of the developed methodology, the coordination among robots is also achieved by different strategies such as fixed priority sequence allotment for motion of each robot, reduction in the velocities of joints of the robot, and introduction of delay in starting of each robot. The performance is assessed in terms of the length of path traversed by each robot, time taken by the robot to realize the task and computational time. The effectiveness of the proposed approach for multi-robot motion planning is demonstrated with two case studies that considered the tasks with three and four robots. The results obtained from realistic simulation of multi-robot environment demonstrate that the proposed approach assures rapid, concurrent and conflict free coordinated path planning for multiple robots.  相似文献   

20.
The current trends in the robotics field have led to the development of large-scale multiple robot systems, and they are deployed for complex missions. The robots in the system can communicate and interact with each other for resource sharing and task processing. Many of such systems fail despite the availability of necessary resources. The major reason for this is their poor coordination mechanism. Task planning, which involves task decomposition and task allocation, is paramount in the design of coordination and cooperation strategies of multiple robot systems. Task allocation mechanism allocates the task in a mission to the robots by maximizing the overall expected performance, and thereby reducing the total allocation cost for the team. In this paper, we formulate a heuristic search-based task allocation algorithm for the task processing in heterogeneous multiple robot system, by maximizing the efficiency in terms of both communication and processing cost. We assume a set of decomposed tasks of a mission, which needs to be allocated to the robots. The near-optimal allocation schemes are found using the proposed peer structure algorithm for the given problem, where the number of the tasks is more than the robots present in the system. The cost function is the summation of static overhead cost of robots, assignment cost, and the communication cost between the dependent tasks, if they are assigned to different robots. Experiments are performed to verify the effectiveness of the algorithm by comparing it with the existing methods in terms of computational time and quality of solution. The experimental results show that the proposed algorithm performs the best under different problem scales. This proves that the algorithm can be scaled for larger system and it can work for dynamic multiple robot system.  相似文献   

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