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1.
针对动态多目标围捕,提出了一种复杂环境下协同自组织多目标围捕方法.首先设计了多目标在复杂环境下的运动模型,然后通过对生物群体围捕行为的研究,构建了多目标简化虚拟受力模型.基于此受力模型和提出的动态多目标自组织任务分配算法,提出了群机器人协同自组织动态多目标围捕算法,这两个算法只需多目标和个体两最近邻位置信息以及个体面向多目标中心方向的两最近邻任务信息,计算简单高效,易于实现.接着获得了系统稳定时参数的设置范围.由仿真可知,所提的方法具有较好的灵活性、可扩展性和鲁棒性.最后给出了所提方法相较于其它方法的优势.  相似文献   

2.
针对未知动态障碍物环境下非完整移动群机器人围捕,提出了一种基于简化虚拟受力模型的自组织方法.首先给出了个体机器人的运动方程,然后给出了未知动态环境下目标和动态障碍物的运动模型.通过对复杂环境下围捕行为的分解,抽象出简化虚拟受力模型,基于此受力模型,设计了个体运动控制方法,接着证明了系统的稳定性并给出了参数设置范围.不同情况下的仿真结果表明,本文给出的围捕方法可以使群机器人在未知动态障碍物环境下保持较好的围捕队形,并具有良好的避障性能和灵活性.最后分析了本文与基于松散偏好规则的围捕方法相比的优势.  相似文献   

3.
In this paper we present role-based control which is a general bottom-up approach to the control of locomotion in self-reconfigurable robots. We use role-based control to implement a caterpillar, a sidewinder, and a rolling track gait in the CONRO self-reconfigurable robot consisting of eight modules. Based on our experiments and discussion we conclude that control systems based on role-based control are minimal, robust to communication errors, and robust to reconfiguration.  相似文献   

4.
We demonstrate how multiagent systems provide useful control techniques for modular self-reconfigurable (metamorphic) robots. Such robots consist of many modules that can move relative to each other, thereby changing the overall shape of the robot to suit different tasks. Multiagent control is particularly well-suited for tasks involving uncertain and changing environments. We illustrate this approach through simulation experiments of Proteo, a metamorphic robot system currently under development.  相似文献   

5.
Self-reconfigurable modular robots consist of many identical modules. By changing the connections among modules, the configuration of the robot can be transformed into other configurations. For the self-reconfigurable modular robot, one of its main functions is its self-repairing ability. First, the module of the lattice-type self-reconfigurable robot is presented. It is composed of a central cube and six rotary arms. On each rotary arm the docking mechanism is designed to show the self-repairing ability. Second, the basic motion of the self-reconfigurable robot is described to change the positions of the module. The state matrix and the location matrix are proposed to describe the connection states. Third, a self-repairing algorithm based on the positions of the faulty modules is presented. The algorithm applies the Breadth-First-Search method and the Depth-First-Search method to find a locomotion path by which the faulty module is ejected and replaced by a spare module. At last, a simulation on the fourth-order lattice-type self-reconfigurable robot consisting of 729 modules shows the feasibility and effectiveness of this self-repairing algorithm in three dimensions.  相似文献   

6.
自重构机器人的自组织变形   总被引:3,自引:0,他引:3  
本文深入研究了自重构机器人实现自组织变形的基本方法.首先根据自重构机器人 系统结构的基本特征提出一种描述模型,可以对各类模块化自重构机器人的拓扑结构进行统 一描述.然后提出一种建立在全离散的局部智能基础上的自重构机器人的自组织变形策略, 通过建立适当的模块运动规则和规则进化使机器人由局部自主运动产生全局系统自组织的结 果.  相似文献   

7.
在自重构多机器人系统中,机器人控制需要解决的关键问题是系统的任务规划和多机器人的协调控制。其中,任务规划是高层的组织与决策机制问题,指如何组织多个机器人共同完成任务,实现机器人系统资源的优化配置。本文通过建立一种多机器人系统的模型,结合集中规划的决策方法,实现自重构机器人系统任务规划的优化问题。仿真结果表明,该方法是可行的。  相似文献   

8.
Modular robots may become candidates for search and rescue operations or even for future space missions, as they can change their structure to adapt to terrain conditions and to better fulfill a given task. A core problem in such missions is the ability to visit distant places in rough terrain. Traditionally, the motion of modular robots is modeled using locomotion generators that can provide various gaits, e.g. crawling or walking. However, pure locomotion generation cannot ensure that desired places in a complex environment with obstacles will in fact be reached. These cases require several locomotion generators providing motion primitives that are switched using a planning process that takes the obstacles into account. In this paper, we present a novel motion planning method for modular robots equipped with elementary motion primitives. The utilization of primitives significantly reduces the complexity of the motion planning which enables plans to be created for robots of arbitrary shapes. The primitives used here do not need to cope with environmental changes, which can therefore be realized using simple locomotion generators that are scalable, i.e., the primitives can provide motion for robots with many modules. As the motion primitives are realized using locomotion generators, no reconfiguration is required and the proposed approach can thus be used even for modular robots without self-reconfiguration capabilities. The performance of the proposed algorithm has been experimentally verified in various environments, in physical simulations and also in hardware experiments.  相似文献   

9.
Self-reconfigurable robots are robots that can change their shape in order to better suit their given task in their immediate environment. Related work on around fifteen such robots is presented, compared and discussed. Based on this survey, design considerations leading to a novel design for a self-reconfigurable robot, called “ATRON”, is described. The ATRON robot is a lattice-based self-reconfigurable robot with modules composed of two hemispheres joined by a single revolute joint. Mechanical design and resulting system properties are described and discussed, based on FEM analyses as well as real-world experiments. It is concluded that the ATRON design is both competent and novel. Even though the ATRON modules are minimalistic, in the sense that they have only one actuated degree of freedom, the collective of modules is capable of self-reconfiguring in three dimensions. Also, a question is raised on how to compare and evaluate designs for self-reconfigurable robots, with a focus on lattice-based systems.  相似文献   

10.
This paper is devoted to the problem of automatically designing feasible and manufacturable robots made up of heterogeneous modules. Specifically, the coevolution of morphology and control in robots is analyzed and a particular strategy to address this problem is contemplated. To this end, the main issues of this approach such as encoding, evaluation or transfer to reality are studied through the use of heterogeneous modular structures with distributed control. We also propose a constructive evolutionary algorithm based on tree-like representations of the morphology that can intrinsically provide for a type of generative evolutionary approach. The algorithm introduces some new elements to smooth the search space and make finding solutions much easier. The evaluation of the individuals is carried out in simulations and then transferred to real robots assembled from the modules considered. To this end, the extension of the principles proposed by classical authors in traditional evolutionary robotics to brain–body evolution regarding how simulations should be set up so that robust behaviors that can be transferred to reality are obtained is considered here. All these issues are analyzed by means of an evolutionary design system called EDHMoR (Evolutionary Designer of Heterogeneous Modular Robots) that contains all the elements involved in this process. To show practical evidences of the conclusions that have been extracted with this work, two benchmark problems in modular robotics are considered and EDHMoR is tested over them. The first one is focused on solving a linear robot motion mission and the second one on a static task of the robot that does not require displacements.  相似文献   

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