基于初等运动的多机器人避碰及死锁预防

该文以一实际应用为背景提出了多移动机器人避碰及死锁预防算法,该算法将机器人的运行环境形式化地描述为初等运动集、冲突图、总任务集及机器人作业集,利用集合论、图论的有关方法及技术实现了多机器人间的避碰与死锁预防。当机器人的运行环境改变时,只需要对相应的集合描述文件进行修改,而不用对程序做任何屐改动。算法的另一个特点是利用避碰算法巧妙地完成了死锁预防。仿真和实际运行证明了该算法高效可靠。     

融合图特征的多机器人栅格地图拼接方法

现有的栅格地图拼接方法在地图重叠区域较小、地图特征较少、地图存在自相似性和非刚性形变的情况下匹配精度往往会大幅度下降甚至失配,提出了一种融合图特征的多机器人栅格地图拼接方法。提取待匹配栅格地图的ORB特征点并粗匹配,接下来建立ORB特征点之间的中值[K]近邻图;建立最优传输目标函数并融合ORB特征和图特征构建传输代价矩阵,同时建立增广节点筛选通过Sinkhorn算法求解最优匹配,RANSAC算法求解两张栅格地图之间的刚体变换,实现多机器人栅格地图的配准和拼接。通过实验验证了该方法具备较高的拼接精度,可应对重叠率低、特征不太明显的场景,展现出了较快的计算速度,并分析了相关参数对算法表现的影响。     

基于混合DSm模型的多机器人地图构建

针对多移动机器人探测静态未知环境,提出了多机器人的一类新的体系结构和机器人内部控制结构,采用分布式融合框架,引入了最近提出的一种在贝叶斯和DST扩展而来的信息融合理论DSmT,结合限制传播算法,建立了不精确传感器(声纳)的混合DSm模型.构造了基本信度赋值函数,计算每个栅格的基本信度值(gbba),有效地融合了多个移动机器人使用声纳获取到的不精确、不确定和高冲突环境信息.最后,以Pioneer 2-DXe机器人作为实验平台,将由混合DSm模型构建出的静态环境地图与实际环境布局做比较,并利用openGL绘制出三维置信度分布图,充分验证了所提出的算法和基于通信的多机器人系统的有效性.     

A Differential Game Theoretic Approach for Two-Agent Collision Avoidance with Travel Limitations

This work presents a collision avoidance control strategy that solves the Hamilton-Jacobi-Isaacs (HJI) equation for an agent to quickly take action assuming a worst-case scenario. By doing so, the agent can develop a control strategy that is robust to the strategies of other agents with whom collision is possible. Consequently, if the governing dynamics of the agent are sufficient, then a collision can be avoided. We build on the idea of finding control solutions by using a differential game theoretic approach (Mettenheim and Breitner, 2009). This is beneficial because the opposing agent’s strategy is incorporated into the control by assuming it plays the worst-case actions. The approach in this work solves the zero-sum aspects of the control on-line using a fast solution method that operates over partitions in the state space (Goode et al., ASME J Dyn Syst Meas Control, 2011). We form the solution to the Homicidal Chauffeur game which is used to provide the control for an evader attempting to avoid a pursuer, an agent that deviates from its normal path and into that of the evader. Furthermore, the evader is constrained to remain within defined boundaries of its assigned travel area, such as a road lane, water channel, etc. The control strategy consists of three parts: (1) a zero-sum approximation of collision avoidance, (2) high-level path planning, and (3) low-level vehicle control. Each component is explained, and an example is given using a real robotic vehicle control system. Here, we show how the control can be implemented using a simple processor located on a vehicle that seeks to avoid a collision with another oncoming vehicle, making a left turn.     

一种考虑机器人尺寸约束的动态窗避障方法

针对太部分反应式避障算法未考虑机器人尺寸的束导致机器人无法通过障碍物间可行通道的问题,提出了一种复杂环境下考虑机器人尺寸约束的动态窗避障方法.利用激光雷达提供的精确测距信息,通过探索机器人运动前方的可通行区域,避免陷入“U”型等局部最小区域;以障碍物间可行通道的宽度与机器人自身尺寸间的关系作为新的引导,构造目标函数,提...     

A Decentralized Architecture for Multi-Robot Systems Based on the Null-Space-Behavioral Control with Application to Multi-Robot Border Patrolling

This paper presents a control architecture for multi-robot systems. The proposed architecture has been developed in the framework of the Null-Space-based-Behavioral (NSB) control, a competitive-collaborative behavior-based control approach. The standard NSB statically determines a set of suitably defined elementary tasks (behaviors) and their priorities, i.e., they cannot be dynamically changed according to mission requirements and environmental constraints. In this paper, a three layer architecture has been designed in order to avoid such a drawback. The single robotic unit (agent) performing the mission is placed on the lower layer. In the middle layer, suitably defined elementary behaviors are defined; these elementary behaviors are then combined, via the NSB approach, in more complex actions. The upper layer is a Supervisor in charge of dynamically selecting the proper action to be executed. As further contribution, the architecture has been applied to the multi-robot border patrolling mission to generate a decentralized, deterministic and non-communicative solution that is robust to faults, and prevents collisions, even in the case of high robot density. Finally, the simulations on a team composed by a large number of robots, and experiments on a real setup, composed by three Pioneer-3DX robots, are provided.     

A Probabilistic Approach to Collaborative Multi-Robot Localization

This paper presents a statistical algorithm for collaborative mobile robot localization. Our approach uses a sample-based version of Markov localization, capable of localizing mobile robots in an any-time fashion. When teams of robots localize themselves in the same environment, probabilistic methods are employed to synchronize each robot's belief whenever one robot detects another. As a result, the robots localize themselves faster, maintain higher accuracy, and high-cost sensors are amortized across multiple robot platforms. The technique has been implemented and tested using two mobile robots equipped with cameras and laser range-finders for detecting other robots. The results, obtained with the real robots and in series of simulation runs, illustrate drastic improvements in localization speed and accuracy when compared to conventional single-robot localization. A further experiment demonstrates that under certain conditions, successful localization is only possible if teams of heterogeneous robots collaborate during localization.     

A Situation-Aware Collision Avoidance Strategy for Car-Following

In this paper, we discuss how to develop an appropriate collision avoidance strategy for car-following. This strategy aims to keep a good balance between traffic safety and efficiency while also taking into consideration the unavoidable uncertainty of position/speed perception/measurement of vehicles and other drivers. Both theoretical analysis and numerical testing results are provided to show the effectiveness of the proposed strategy.      

一种具有小世界特征和冲突避免的DSR协议

提出一种DSR的改进协议M-DSR.M-DSR协议首先把路由请求范围限制在一定区域内,然后根据实际情况逐步扩大请求范围,进一步根据节点的性能值来避免局部网络冲突.仿真实验表明,M-DSR协议能够提高路由发现速度、降低网络冗余信息、避免局部网络冲突,在路由负荷较大的情况下的表现尤其突出.     

自治水下机器人避碰算法及其仿真研究

为了提高水下机器人(AUV)在复杂海洋环境下的自适应性,文章对传统的避碰方法进行了改进.对AUV的禁入区和潜在碰撞区进行了安全性分析.建立了前视声纳模型以及三维水下规划空间模型.提出了基于强化学习、BP神经网络及人工势场相结合的避碰算法.在AUV与环境的试错交互中,借助于来自成功和失败经验的奖励和惩罚值,不断改进水下机器人的自治能力.设计了AUV深度行为模糊协调器, 对潜深行为和距底高度行为进行协调融合.开发了AUV运动规划与仿真的半实物软件系统,仿真试验证明了算法的合理性与可行性.研究对于提高AUV的自主性和安全性具有重要的应用价值.     

团队CGA行进中的动态避障方法

提出一个团队CGA行进中的动态障碍规避方法,利用非零和2人对策来讨论两个CGA之间的碰撞问题,通过对每个CGA的特征分析得到对策的解,使CGA成员获得期望的效用。该方法很容易地实现了团队队形依据环境的动态改变及处理掉队问题。     

密集型WSN冲突避免的MAC协议

无线传感器网络媒体接触控制层存在2种冲突。提出基于概率的时隙选择算法,使不同节点在相同时隙发送概率不同,从而降低域内冲突。实验结果显示,该算法的有效能量和损失能量相比Sift协议节省了17.6%和43.9%,能量有效率提高了14.3%。提出染色预防算法,通过提前确定节点活动时序解决域间冲突问题。实验结果显示,该算法的节点平均睡眠时间在87%以上,空闲侦听导致的能量消耗仅占总能量的7%。     

密集型WSN冲突避免的MAC协议

无线传感器网络媒体接触控制层存在2种冲突。提出基于概率的时隙选择算法,使不同节点在相同时隙发送概率不同,从而降低域内冲突。实验结果显示,该算法的有效能量和损失能量相比Sift协议节省了17.6%和43.9%,能量有效率提高了14.3%。提出染色预防算法,通过提前确定节点活动时序解决域间冲突问题。实验结果显示,该算法的节点平均睡眠时间在87%以上,空闲侦听导致的能量消耗仅占总能量的7%。     

A Novel Multi-agent Formation Control Law With Collision Avoidance

In this paper a stable formation control law that simultaneously ensures collision avoidance has been proposed. It is assumed that the communication graph is undirected and connected. The proposed formation control law is a combination of the consensus term and the collision avoidance term (CAT). The first order consensus term is derived for the proposed model, while ensuring the Lyapunov stability. The consensus term creates and maintains the desired formation shape, while the CAT avoids the collision. During the collision avoidance, the potential function based CAT makes the agents repel from each other. This unrestricted repelling magnitude cannot ensure the graph connectivity at the time of collision avoidance. Hence we have proposed a formation control law, which ensures this connectivity even during the collision avoidance. This is achieved by the proposed novel adaptive potential function. The potential function adapts itself, with the online tuning of the critical variable associated with it. The tuning has been done based on the lower bound of the critical variable, which is derived from the proposed connectivity property. The efficacy of the proposed scheme has been validated using simulations done based on formations of six and thirty-two agents respectively.      

地图构建中动态障碍干扰滤除的一种方法

在移动机器人环境建图中,动态障碍物的存在直接影响传感器的读数,导致产生不一致的环境地图,因此,移动机器人构建地图必须滤除动态障碍物干扰。采用直线插补的方法在先前的局部图上搜寻机器人与目标点之间是否存在障碍物,若存在障碍,则可判定该障碍物已移走(即为动态障碍),应该予以滤除。实验结果证明,该方法能在建图过程中有效地滤除动态障碍,并能有效减少静态障碍物探测的误差累积,算法复杂度小。     

A Nonlinear Set Membership Approach for the Localization and Map Building of Underwater Robots

This paper proposes a set membership method based on interval analysis to solve the simultaneous localization and map building (SLAM) problem. The principle of the approach is to cast the SLAM problem into a constraint satisfaction problem for which interval propagation algorithms are particularly powerful. The resulting propagation method is illustrated on the localization and map building of an actual underwater robot.      

汽车防撞预警系统的研究与发展

随着汽车工业的发展,汽车行驶速度越来越快,道路交通事故已成为世界性的社会问题。其中,碰撞事故占的比例约80％,所以对汽车防撞研究也成为世界性课题。先对汽车防撞预警系统的原理进行分析,再结合国内外现有的汽车防撞预警系统,如超声波防撞预警系统、雷达防撞预警系统、激光防撞预警系统、机器视觉防撞预警系统、红外线防撞预警系统以及交互式智能化防撞预警系统等,对它们的原理、特点、缺陷等方面进行分析,最后总结出现有技术的固有缺陷,提出了汽车防撞预警系统的发展方向。