Swarm robotic network using Lévy flight in target detection problem

One approach in swarm robotics is homogeneous system which is embedded with sensing, computing, mobile and communication components. In this study, a target detection problem, which is one of navigation problems, was employed. Once a robot detects a target, robots immediately communicate with a base station via intermediate relay robots due to the multi-hop transmission of wireless communication. Therefore, this control task is completed with connectivity of the network. In a target detection problem, we must improve the performance of exploration as well as connectivity of the network. This study investigates the performances of the two types of random walk algorithm in navigation while loosely ensuring connectivity of the robotic network based on our previous study.     

基于WIFI+GPRS的无线传感器网络监控系统

传感器网络是一个将传感器技术、嵌入式系统、通信网络技术相结合的网络,实现数据采集、无线定位、远程监控、设备管理等功能,结合ZigBee、WIFI、GPRS等无线网络的优点,构建一个异构无线传感器网络,实现无线网络和移动通讯刚络的远程数据采集、定位与控制、异常事件报警,系统通过无线传感器终端节点进行数据采集,利用具有接收、转发数据助能的无线网络接收,实现异构网络终端设备间的数据交互与共享,达到无线定位,短信报警、上位机软件监控的目的．     

基于惯性传感器的集群移动机器人定位系统设计

为了对集群机器人的定位技术做进一步研究,本文对群体移动机器人的整体框架进行了设计,主要包括控制单元、通信模块和传感器单元等,重点对基于MPU9250惯性传感器的定位技术进行了研究,定位系统以ZigBee模块组成无线传感网络,用Arduino对MPU9250进行姿态数据获取并进行处理,利用ZigBee网络将位置信息传输到上位机.本文提出的机器人惯导定位技术对于解决机器人的定位问题具有一定的指导意义.     

Guide robot intelligent navigation in urban environments

This paper presents an intelligent robotic system to guide visually impaired people in urban environments. The robot is equipped with two laser range finders, global positioning system (GPS), camera, and compass sensors. All the sensors data are processed by a single laptop computer. We have implemented different navigation algorithms enabling the robot to move autonomously in different urban environments. In pedestrian walkways, we utilize the distance to the edge (left, right, or both) to determine the robot steering command. In difference from pedestrian walkways, in open squares where there is no edge information, artificial neural networks map the GPS and compass sensor data to robot steering command guiding the visually impaired to the goal location. The neural controller is designed such as to be employed even in environments different from those in which they have been evolved. Another important advantage is that a single neural network controls the robot to reach multiple goal locations inside the open square. The proposed algorithms are verified experimentally in a navigation task inside the University of Toyama Campus, where the robot moves from the initial to goal location.     

Path planning of fire-escaping system for intelligent building

We present the path-planning techniques of the fire-escaping system for intelligent building, and use multiple mobile robots to present the experimental scenario. The fire-escaping system contains a supervised computer, an experimental platform, some fire-detection robots and some navigation robots. The mobile robot has the shape of a cylinder, and its diameter, height and weight are 10?cm, 15?cm and 1.5?kg, respectively. The mobile robot contains a controller module, two DC servomotors (including drivers), three IR sensor modules, a voice module and a wireless RF module. The controller of the mobile robot acquires the detection signals from reflective IR sensors through I/O pins and receives the command from the supervised computer via wireless RF interface. The fire-detection robot carries the flame sensor to detect fire sources moving on the grid-based experiment platform, and calculates the more safety escaping path using piecewise cubic Bezier curve on all probability escaping motion paths. Then the user interface uses A* searching algorithm to program escaping motion path to approach the Bezier curve on the grid-based platform. The navigation robot guides people moving to the safety area or exit door using the programmed escaping motion path. In the experimental results, the supervised computer programs the escaping paths using the proposed algorithms and presents movement scenario using the multiple smart mobile robots on the experimental platform. In the experimental scenario, the user interface transmits the motion command to the mobile robots moving on the grid-based platform, and locates the positions of fire sources by the fire-detection robots. The navigation robot guides people leaving the fire sources using the low-risk escaping motion path and moves to the exit door.     

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.     

Robotic data mules for collecting data over sparse sensor fields

We present a robotic system for collecting data from wireless devices dispersed across a large environment. In such applications, deploying a network of stationary wireless sensors may be infeasible because many relay nodes must be deployed to ensure connectivity. Instead, our system utilizes robots that act as data mules and gather the data from wireless sensor network nodes. We address the problem of planning paths of multiple robots so as to collect the data from all sensors in the shortest time. In this new routing problem, which we call the data gathering problem (DGP), the total download time depends on not only the robots' travel time but also the time to download data from a sensor and the number of sensors assigned to the robot. We start with a special case of DGP in which the robots' motion is restricted to a curve that contains the base station at one end. For this version, we present an optimal algorithm. Next, we study the two‐dimensional version and present a constant factor approximation algorithm for DGP on the plane. Finally, we present field experiments in which an autonomous robotic data mule collects data from the nodes of a wireless sensor network deployed over a large field. © 2011 Wiley Periodicals, Inc.     

无线传感器网络疑误数据节点自动诊断方法

为了提高无线传感器网络疑误数据检测能力,提出基于轮换调度的无线传感器网络疑误数据节点自动诊断方法.通过采用分块区域特征匹配的方法,得到无线传感器网络疑误数据传输的梯度模型,采用资源优化分配方案,进行数据传输信道的均衡调度,得到节点部署分布模型.通过传感信息跟踪采样方法,得到采样信息分布,建立无线传感器网络疑误数据信息特...     

无线传感网中混合业务下的触发式流控制算法

无线传感器网络中,节点所具有的能量和通信能力等都十分有限,如何设计有效的协议及算法,利用有限的资源高效地完成诸多任务,成为无线传感器网络设计所面临的一大挑战.考虑接收容量模型,研究了无线传感器网络在节点接收容量和能量联合受限情况下,面向混合业务时的效用公平流控制问题,并针对传统对偶分解算法存在着收敛速度慢、步长不易调节、通信负荷大等缺陷,进一步提出了基于事件触发的分布式求解算法.理论分析与仿真验证均表明:使用事件触发算法时,传感节点的平均广播周期比使用对偶分解算法时大很多,大幅度降低了无线传感器网络节点间的通信量,减少了网络的通信开销.仿真结果显示:与对偶分解算法相比,分布式事件触发算法具有收敛速度快、对网络规模扩展的适应性强等优势;与传统的速率公平流控制机制相比,所提的效用公平流控制模型能够更加适应弹性与非弹性业务共存的网络场景.     

A geometric approach to deploying robot swarms

We discuss the fundamental problems and practical issues underlying the deployment of a swarm of autonomous mobile robots that can potentially be used to build mobile robotic sensor networks. For the purpose, a geometric approach is proposed that allows robots to configure themselves into a two-dimensional plane with uniform spatial density. Particular emphasis is paid to the hole repair capability for dynamic network reconfiguration. Specifically, each robot interacts selectively with two neighboring robots so that three robots can converge onto each vertex of the equilateral triangle configuration. Based on the local interaction, the self-configuration algorithm is presented to enable a swarm of robots to form a communication network arranged in equilateral triangular lattices by shuffling the neighbors. Convergence of the algorithms is mathematically proved using Lyapunov theory. Moreover, it is verified that the self-reparation algorithm enables robot swarms to reconfigure themselves when holes exist in the network or new robots are added to the network. Through extensive simulations, we validate the feasibility of applying the proposed algorithms to self-configuring a network of mobile robotic sensors. We describe in detail the features of the algorithm, including self-organization, self-stabilization, and robustness, with the results of the simulation.     

矿井宽带无线传输技术研究

提出了矿井宽带无线传输技术是解决采掘工作面移动监控、监视和语音通信需求的关键技术。提出了矿井宽带无线传输应满足传输带宽宽、便于接入有线宽带网络、中继设备少、体积小、发射功率小、电磁兼容性好、安全性好、传输协议标准化、电源电压波动适应能力强等要求。提出了漏泄通信不能用作矿井宽带无线传输技术,但可用于煤矿井下局部通信等;感应通信不能用作矿井宽带无线传输技术,但可用于煤矿井下救灾通信等;透地通信不能用作矿井宽带无线传输技术,但可用于煤矿井下避难硐室等应急通信;小灵通、CDMA、GSM、Bluetooth不能用作矿井宽带无线传输技术;RFID不能用作矿井宽带无线传输技术,但可用于煤矿物联网、矿用设备管理和防碰撞等;ZigBee不能用作矿井宽带无线传输技术,但可用于煤矿井下人员、胶轮车、电机车等动目标精确定位和矿用传感器无线传输等;UWB不能用作矿井宽带无线传输技术,但可用于煤矿井下生命探测、防碰撞、煤矿井下人员和胶轮车等动目标精确定位等;WCDMA、CDMA2000、TD-SCDMA等3G不能用作矿井宽带无线传输技术,但可用于煤矿井下语音移动通信等。提出了矿井宽带无线传输技术宜采用WiFi,4G有可能成为未来矿井宽带无线传输技术。     

An algorithm for safe navigation of mobile robots by a sensor network in dynamic cluttered industrial environments

Mobile robots have been widely implemented in industrial automation and smart factories. Different types of mobile robots work cooperatively in the workspace to complete some complicated tasks. Therefore, the main requirement for multi-robot systems is collision-free navigation in dynamic environments. In this paper, we propose a sensor network based navigation system for ground mobile robots in dynamic industrial cluttered environments. A range finder sensor network is deployed on factory floor to detect any obstacles in the field of view and perform a global navigation for any robots simultaneously travelling in the factory. The obstacle detection and robot navigation are integrated into the sensor network and the robot is only required for a low-level path tracker. The novelty of this paper is to propose a sensor network based navigation system with a novel artificial potential field (APF) based navigation algorithm. Computer simulations and experiments confirm the performance of the proposed method.     

Autonomous robot navigation using optimal control of probabilistic regular languages

This paper addresses autonomous intelligent navigation of mobile robotic platforms based on the recently reported algorithms of language-measure-theoretic optimal control. Real-time sensor data and model-based information on the robot's motion dynamics are fused to construct a probabilistic finite state automaton model that dynamically computes a time-dependent discrete-event supervisory control policy. The paper also addresses detection and avoidance of livelocks that might occur during execution of the robot navigation algorithm. Performance and robustness of autonomous intelligent navigation under the proposed algorithm have been experimentally validated on Segway RMP robotic platforms in a laboratory environment.     

基于遗传算法的机械设备故障检测机器人设计

当前故障检测机器人受到超声波影响故障检测存在精准度低的问题,据此提出了基于遗传算法的机械设备故障检测机器人设计。采用AD500-1A型号传感器采集机械设备内外部数据信息,使用等效转换电路使机器人实时感知周围环境变化信息,并利用灵敏度高电子仪器实现机器人传感工作;使用2路200万数字网络高清摄像头,监视整个机械设备,获取机器人结构通信、管理和运动信息;将proGee0813型号芯片作为导航设备定位芯片,根据实际需求获取信号指令,并选定机器人行驶路径;通过Unity与UE4引擎虚拟现实硬件交互设备进行故障定位追踪;利用关节装置连接车轮前臂和上臂,实现不同磁铁吸附与脱离,依据机器人结构,完成机器人硬件结构设计。采用遗传算法确定导航适应度函数,通过机器人视频采集信息,设计预警功能,并利用机器人即时生成设备故障图像,依据实现流程,在超声避障功能支持下,完成机械设备故障检测。由实验结果可知,该机器人检测精准度最高可达到0.96,提高了机器人检测鲁棒性。     

A Vision for Supporting Autonomous Navigation in Urban Environments

The autonomous navigation systems (ANS), such as autonomous ground vehicles (AGVs), unmanned aerial vehicles (UAVs), and unmanned submersible vehicles (USVs), and modern vehicles with actuators, sensors, and computer control perform three basic functions: context gathering using sensors, processing, and action. Most researchers have put all three functions into the ANS or the robot itself to overcome occlusions and handle the environment's dynamics. However, this causes the ANS and robotic systems to be bulky and expensive. It also impedes the introduction of vehicles with ANS in urban environments, where they must coexist with existing cars and highways. The approach presented distributes the context-gathering and processing functions using sensor networks and wireless communications technologies to reduce costs and make ANS widespread. The system uses sensors mounted on moving vehicles and stationary objects such as lampposts, traffic lights, toll plazas, and buildings to gather information at different levels     

Adaptive clustering in wireless sensor networks by mining sensor energy data

Clustering has been well received as one of the effective solutions to enhance energy efficiency and scalability of large-scale wireless sensor networks. The goal of clustering is to identify a subset of nodes in a wireless sensor network, then all the other nodes communicate with the network sink via these selected nodes. However, many current clustering algorithms are tightly coupled with exact sensor locations derived through either triangulation methods or extra hardware such as GPS equipment. However, in practice, it is very difficult to know sensor location coordinates accurately due to various factors such as random deployment and low-power, low-cost sensing devices. Therefore, how to develop an adaptive clustering algorithm without relying on exact sensor location information is a very important yet challenging problem. In this paper, we try to address this problem by proposing a new adaptive clustering algorithm for energy efficiency of wireless sensor networks. Compared with other work having been done in this area, our proposed adaptive clustering algorithm is original because of its capability to infer the location information by mining wireless sensor energy data. Furthermore, based on the inferred location information and the remaining (residual) energy level of each node, the proposed clustering algorithm will dynamically change cluster heads for energy efficacy. Simulation results show that the proposed adaptive clustering algorithm is efficient and effective for energy saving in wireless sensor networks.     

Multi-robot-based intelligent security system

This article describes a multiple security module-based intelligent security system that has multiple communication interfaces which can be applied in home automation. The interfaces of the intelligent security system contain wired RS485, wireless RF, and Internet. The detection modules of the system have both active and passive security modules. The passive security modules contain wired security modules and wireless security modules. The control unit of all security modules is a HOLTEK microchip. Each security module has two different interfaces. They use voice modules to alarm users of an event, and to transmit real-time event signals to the supervising computer via the wired RS485 or wireless RF interface. If an event occurs, the supervising computer calculates its belief values using Dempster-Shafter evidence theory according to the passive wired and wireless security modules. If the belief value is over a set threshold, the supervising computer commands the mobile robot to move to the event location, and receives a signal from the mobile robot via the wireless RF interface. The supervising computer recognizes the final decision output using Dempster-Shafter evidence theory, and displays the detection and decision output values on the monitor of the user interface. Finally, we present some experimental results using wired passive security modules, wireless passive security modules, and active security modules for fire detection and gas leakage detection using the experimental platform of the intelligent security system.     

Design and implementing wireless multimedia sensor network for movement detection using FPGA local co-processing

In recent years, many researches have been conducted on designing wireless multimedia sensor networks. But, implementing these networks faces several challenges. One of these challenges is the bulky nature of the multimedia data which needs powerful radios with high data rates for transmission and requires much more energy. So, in some applications it is more efficient to process the data locally and send the results to the base station which allows WMSNs to be implemented using simple and cheap network nodes. In this paper a wireless multimedia sensor network has been designed which processes the images locally using small FPGA processors in order to detect possible motions and the time and location of the detected movements will be sent to the base station. The network is implemented to perform two motion detection algorithms separately using Spartan 6 FPGAs and the local results of motion detection and global result of the network are presented.

     

一类新的分布式随机验证无线传感网络节点克隆攻击检测

由于无线传感器网络节点的无人值守性,攻击者很容易捕获并复制节点,利用节点的安全证书把复制节点发布到无线传感器网络的各个角落,进而秘密发动各种攻击。提出一类新的分布式节点复制攻击检测协议,协议采用随机区域单元映射和域内随机线选验证相结合的方法进行攻击检测。仿真结果显示,协议的随机验证特性使网络能量消耗均匀,延长网络的生存周期。域内线选验证使协议的通信开销和储存开销较低并具有较高的检测率。     

Unmanned Ground Vehicle Navigation in Coordinate-Free and Localization-Free Wireless Sensor and Actuator Networks

We present a set of algorithms for the navigation of Unmanned Ground Vehicles (UGVs) towards a set of pre-identified target nodes in coordinate-free and localization-free wireless sensor and actuator networks. The UGVs are equipped with a set of wireless listeners that provide sensing information about the potential field generated by the network of actuators. Two main navigation scenarios are considered: single-UGV, single-destination navigation and multi-UGV, multi-destination navigation. For the single-UGV, single-destination case, we present both centralized and distributed navigation algorithms. Both algorithms share a similar two-phase concept. In the first phase, the system assigns level numbers to individual nodes based on their hop distance from the target nodes. In the second phase, the UGV uses the potential field created by the network of actuators to move towards the target nodes, requiring cooperation between triplets of actuator nodes and the UGV. The hop distance to the target nodes is used to control the main moving direction while the potential field, which can be measured by listeners on the UGV, is used to determine the UGV’s movement. For the multi-UGV, multi-destination case, we present a decentralized allocation algorithm such that multiple UGVs avoid converging to the same destination. After each UGV determines its destination, the proposed navigation scheme is applied. The presented algorithms do not attempt to localize UGVs or sensor nodes and are therefore suitable for operating in GPS-free/denied environments. We also present a study of the communication complexity of the algorithms as well as simulation examples that verify the proposed algorithms and compare their performances.