一个面向复杂任务的多机器人分布式协调系统

基于多智能体系统理论, 研究在非结构、不确定环境下面向复杂任务的多机器人分布式协调系统的实现原理、方法和技术. 提出的递阶混合式协调结构、基于网络的通讯模式和基于有限状态机的规划与控制集成方法, 充分考虑了复杂任务和真实自然环境的特点. 通过构建一个全实物的多移动机器人实验平台, 对规划、控制、传感、通讯、协调与合作的各关键技术进行了开发和集成, 使多机器人分布式协调技术的研究直接面向实际应用, 编队和物料搬运的演示实验结果展示了多机器人协调技术的广阔应用前景.     

面向多机器人遥操作的分布式预测图形仿真系统

在遥操作机器人系统中,由于存在通信传输时延,可能导致控制系统不稳定,从而降 低遥操作的效率和安全性．目前多采用预测仿真的方法来克服．在多机器人遥操作系统不但 要克服时延的影响,还要能控制机器人协调地完成遥操作任务．我们开发了一个面向多操作 者 多机器人遥操作的分布式预测图形仿真系统,实现了对多机器人遥操作系统的预测仿真 ,多个操作者可以通过人机交互接口遥控各自的机器人,相互协调完成遥操作的任务．初步 的实验表明该系统能够克服时延的影响,并能实现多操作者 多机器人的协调遥操作．这对 空间站机器人科学实验、多航行器对接等方面的研究有理论参考价值．     

旋翼飞行机器人研究进展

旋翼飞行机器人是面向空中自主作业需求,将旋翼飞行器与多自由度机械臂相结合所提出的新型机器人.该机器人作业过程中旋翼飞行器、机械臂与作业目标之间的动态相对运动以及与作业目标接触过程中未建模外力、力矩扰动使自主控制受到极大挑战.本文将针对旋翼飞行机器人的结构演变及关键技术、作业机构集成技术进行综述.从动力学建模及动力学特性分析、动态运动约束/力约束下的协调规划、非结构环境下的运动和作业控制、面向任务动态操作的环境感知、面向任务的实验系统构建与实验验证五个方面初步构建了旋翼飞行机器人自主作业理论体系.     

基于多模式交互的多移动机器人分布式合作系统

本文研究合作型多移动机器人系统的分布式控制方法.为了保证多机器人间合作的实 时性和高效率,采用了一种分组策略,并提出了将局部感知和组内通信相集成的多模式机器人 间交互方法.考虑到任务的复杂性和真实环境的非结构化特点,构建了将递阶规划技术与基于 行为的反应式控制相结合的递阶混合式协调结构,并采用有限状态机模型实现了规划层与行为 层的协调机制.合作垃圾清运的实验结果证明了上述方法的有效性.     

基于开放式多智能体结构的分布式自主机器人系统

针对多机器人系统的分布式自主控制,本文首先提出了一种开放式的多智能体结构,给出了 设计原则和技术特点．然后面向真实世界的多机器人实时协作任务,采用多台自主移动机器 人构造了一个多机器人系统, 该系统集成了包括机器人视觉、传感器融合、无线通讯网络 以及基于行为控制等多项技术．最后采用基于行为融合的加权方法,实现了多机器人的编队 控制,实验结果表明了上述体系结构与方案的有效性．     

基于网络的多操作者多机器人协作研究

研究基于网络的多操作者多机器人的协作方案,分别提出了针对机器人约束和非约束体协作条件下的协调策略,并在局域网内建立一个仿真实验系统对机器人协作进行仿真.在约束情况下以机器人协同搬运为研究点,提出采用"主、从"机器人控制方法,确定工件运动轨迹后采用位置反解算法确定机器人运动.在非约束情况下提出采用"时间戳"、"回滚"方法协调操作.在整个仿真系统中采用基于AABB的碰撞检测算法确保机器人操作的安全性.仿真实验的结果验证了协调策略的可行性和正确性.     

机器人点焊工作站在汽车制造中的应用

机器人焊接系统属于多智能体系统（Multi—Agent systems，MAS），机器人点焊系统集成的关键是如何处理好MAS的通信和工作协调。本文介绍汽车车身机器人点焊的工作流程，重点介绍了机器人点焊工作站的控制原理及工作站集成技术。     

面向VAL语言的机器人仿真和离线编程

本文介绍一个面向VAL语言的机器人仿真和离线编程系统ROSOP(Robot Simnlation and off-linepzogzamming system).该系统是中科院沈阳自动化研究所结合国家“863”高技术课题(“智能机器人系统仿真”和双机器人协调工作实验系统”),为两个PUMA机器人双手协调工作的研究而开发研制的.     

基于虚拟样机的复杂产品协同设计与仿真关键技术研究*

主要研究并行工程环境下复杂产品虚拟样机协同设计与仿真的体系结构及其关键技术。提出虚拟样机协同设计与仿真系统的体系结构与整体解决方案,研究面向虚拟样机的数字化多领域集成建模理论与方法,建立面向虚拟样机开发全生命周期的集成过程管理与冲突协调模型,提出面向复杂产品虚拟样机开发的多学科协同设计、协同仿真和智能决策支持的理论与方法,建立复杂产品虚拟样机协同支持环境,有效提高企业创新能力和核心竞争力。     

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。     

Petri Net Plans

Programming the behavior of multi-robot systems is a challenging task which has a key role in developing effective systems in many application domains. In this paper, we present Petri Net Plans (PNPs), a language based on Petri Nets (PNs), which allows for intuitive and effective robot and multi-robot behavior design. PNPs are very expressive and support a rich set of features that are critical to develop robotic applications, including sensing, interrupts and concurrency. As a central feature, PNPs allow for a formal analysis of plans based on standard PN tools. Moreover, PNPs are suitable for modeling multi-robot systems and the developed behaviors can be executed in a distributed setting, while preserving the properties of the modeled system. PNPs have been deployed in several robotic platforms in different application domains. In this paper, we report three case studies, which address complex single robot plans, coordination and collaboration.     

RoboNetSim: An integrated framework for multi-robot and network simulation

In networked multi-robot systems, communication plays a major role defining system’s dynamics and performance. Unfortunately, existing multi-robot simulators do not provide advanced communication models. Therefore, given the intrinsic unreliability of wireless communications, significant differences might be observed between simulation and real-world results.Addressing these issues, we present RoboNetSim, an integrated simulation framework for communication-realistic simulation of networked multi-robot systems. RoboNetSim integrates multi-robot simulators with network simulators. We present two model implementations based on ARGoS at the robotic side, and NS-2 and NS-3 as network simulators. We evaluate the framework in terms of accuracy and computational performance, showing that it can efficiently simulate systems consisting of hundreds of robots.Using the Stage simulator as an example, we also show the integration of a robotic simulator with RoboNetSim by only adapting robot controllers, without the need to adapt the general code of the simulator.Finally, we demonstrate the effects of communication on mobile multi-robot systems. We consider two different case studies: a distributed coordination and task assignment scenario, and a coordinated mobility scenario. We compare realistic network simulation with simplified communication models and algorithms, and we study the resulting behavior and performance of the multi-robot system and the impact of different parameters.     

Distributed Coordination in Heterogeneous Multi-Robot Systems

Coordination in multi-robot systems is a very active research field in Artificial Intelligence and Robotics, since through coordination one can achieve a more effective execution of the robots' tasks. In this paper we present an approach to distributed coordination of a multi-robot system that is based on dynamic role assignment. The approach relies on the broadcast communication of utility functions that define the capability for every robot to perform a task and on the execution of a coordination protocol for dynamic role assignment. The presented method is robust to communication failures and suitable for application in dynamic environments. In addition to experimental results showing the effectiveness of our approach, the method has been successfully implemented within the team of heterogeneous robots Azzurra Robot Team in a very dynamic hostile environment provided by the RoboCup robotic soccer competitions.     

异构多机器人编队相互通信时延精确控制

编队控制是多机器人协同控制领域研究的重点问题。考虑实际复杂环境,对异构多机器人系统的编队控制研究更具工程意义。再者,当异构多机器人编队系统存在通信时延时,同时对系统中不同阶机器人进行一致性分析的难度增大。针对以上问题,提出一种基于一致性理论的异构系统编队控制算法。考虑零时延与固定时延两种情况,首先,利用一致性思想将领航跟随者模式下的异构多机器人系统编队控制问题转换为稳定性问题。然后,根据矩阵分析与Routh-Hurwitz定理,推导出零时延系统实现编队控制的充要条件。进一步构造Lyapunov-Razumikhin函数,利用Newton-Leibniz公式与Lyapunov定理,推导出固定时延系统实现编队控制的充分条件。仿真结果表明：基于一致性算法的异构多机器人系统能够实现相互通信时延条件下的编队精确控制。     

Multi-robot coalition formation

As the community strives towards autonomous multi-robot systems, there is a need for these systems to autonomously form coalitions to complete assigned missions. Numerous coalition formation algorithms have been proposed in the software agent literature. Algorithms exist that form agent coalitions in both super additive and non-super additive environments. The algorithmic techniques vary from negotiation-based protocols in multi-agent system (MAS) environments to those based on computation in distributed problem solving (DPS) environments. Coalition formation behaviors have also been discussed in relation to game theory. Despite the plethora of MAS coalition formation literature, to the best of our knowledge none of the proposed algorithms have been demonstrated with an actual multi-robot system. There exists a discrepancy between the multi-agent algorithms and their applicability to the multi-robot domain. This paper aims to bridge that discrepancy by unearthing the issues that arise while attempting to tailor these algorithms to the multi-robot domain. A well-known multi-agent coalition formation algorithm has been studied in order to identify the necessary modifications to facilitate its application to the multi-robot domain. This paper reports multi-robot coalition formation results based upon simulation and actual robot experiments. A multi-agent coalition formation algorithm has been demonstrated on an actual robot system.     

考虑通信状况的多机器人CSLAM问题综述

多机器人系统的通信状况能够直接影响协作同时定位与地图创建(Cooperative simultaneous localization and mapping, CSLAM)算法的设计和实现.根据对多机器人通信状况所作出假设的侧重点不同, 对多机器人CSLAM算法研究现状和进展进行综述.首先,简要介绍了基于完全连通通信条件的集中式CSLAM算法的特点和缺陷; 其次,结合多机器人系统初始相对位姿关系未知的情况,从地图配准、数据关联和地图融合等三个方面, 对基于通信范围或者带宽受限条件的分布式CSLAM算法的地图合并问题进行了分析和阐述; 进而重点对考虑稀疏动态通信状况的分布式CSLAM算法的最新研究成果进行了归纳总结. 最后指出多机器人CSLAM研究领域今后的研究方向.     

Model Continuity to Support Software Development for Distributed Robotic Systems: A Team Formation Example

Modeling, design and testing of the software underlying distributed robotic systems is a challenging task, especially when a large number of mobile robots and task coordination are involved. Model continuity, the ability to use the same model of a system throughout its design phases, provides an effective way to manage this development complexity and maintain consistency of the software. In this paper, we describe the design and implementation of a team-formation multi-robot system. This is used as an example to demonstrate how a modeling and simulation environment, based on the DEVS formalism, can support model continuity in the design of distributed robotic systems. This example shows how the intelligent control models of the robots are first designed and tested via simulation and, when verified mapped to physical robots with DEVS-on-a-chip brains for execution.     

基于事件的设计与控制技术及其在机器人系统中的应用

基于事件的设计与控制技术已经引起人们的广泛关注,其基本思想就是引入与系统输出相关的运动参考变量(action reference),在任意时刻使系统给定量的输入以及系统的设计都转化为这个参考变量的函数,使系统的设计部分与控制器一样成为系统的决策部件,从而使系统具备处理突发性、不确定性事件的能力,可以根据系统的实际输出来实时、自动地调整系统的输入,实现对系统的实时控制．机器人系统是一个智能控制系统．机器人间的协调协作是其智能性的主要表现．本文首先对基于事件的控制理论及其发展做了回顾,然后介绍了基于事件的控制技术在机器人队形保持、机器制造、多机器人协作等系统智能控制中的应用,实验证明该方法可以取得很好的智能控制效果,提高系统的控制性能．最后探讨了这一研究领域的发展方向．     

Adaptive Force-Motion Control of Coordinated Robots Interacting With Geometrically Unknown Environments

Most studies on adaptive coordination of multi-robot systems assume exact knowledge of system kinematics and deal only with dynamic uncertainties. However, many industrial applications involve tasks in which a multi-robot system interacts with geometrically unknown environments. In this paper, we consider a multi-robot system grasping a rigid object in contact with a geometrically unknown surface. The proposed adaptive hybrid force-motion controller guarantees asymptotic tracking of desired motion and force trajectories while ensuring exact identification of constraint Jacobian matrix without persistency of excitation condition. The control signal is smooth and does not depend on contact force derivative. The proposed adaptive controller is robustified against environmental friction and nonparametric uncertainty in environment geometry. Simulation examples are presented to illustrate the results.