A New Low Cost System for Autonomous Robot Heading and Position Localization in a Closed Area

A low cost system for the localization of mobile indoor robots is presented. The system is composed of an emitter located on a wall and a receptor on top of the robot. The emitter is a laser pointer acting like a beacon, and the receptor is a cylinder made out of 32 independent photovoltaic cells. The robot's position and orientation are obtained from the moments when the laser crosses each cell.     

移动机器人同步定位与地图构建研究进展

同步定位与地图构建（Simultaneous localization and mapping, SLAM）作为能使移动机器人实现全自主导航的工具近来倍受关注.本文对该领域的最新进展进行综述,特别侧重于一些旨在降低计算复杂度的简化算法的分析上,同时对它们进行分类,并指出其优点和不足.本文首先建立了SLAM问题的一般模型,指出了解决SLAM问题的难点;然后详细分析了基于EKF的一些简化算法和基于其他估计思想的方法;最后,对于多机器人SLAM和主动SLAM等前沿课题进行了讨论,并指出了今后的研究方向.     

车底检查机器人导航控制研究

针对采用履带式行驶机构的车底检查机器人,提出了一种基于模糊控制的航向纠偏算法,算法在实时嵌入式多任务控制系统中得到了具体实现,解决了机器人在行走过程中偏离航向以及误差累积的问题。通过试验验证了该算法的有效性,保障了航向纠偏的实时性。文中给出了模糊控制器的详细设计过程,并且给出了在不同行驶速度时,应用航向纠偏算法的机器人与无航向纠偏算法的机器人之间的航向数据对比曲线。     

基于移动机器人的室内火灾预警点探测与定位的方法研究

火灾探测技术已成为对火灾进行预防的重要手段之一,目前常用的固定式火灾探测装置不能自主的探测和定位到火警点,对火灾发生初期的预防和灭火有一定的局限性。论文针对该问题,在分析火灾探测技术的基础上,提出一种多位姿仿人鼻的火灾探测装置,并制备出样机,同时尝试将其与可移动机器人结合来实现对室内火警点的探测和定位。基于不同的烟雾情况制定出不同的探测准则,根据该准则进行路径轨迹仿真,经过仿真结果可以看到移动机器人最终定位到火警点的位置。可移动的火灾探测装置在探测和定位到火警点的过程中,若所在空间中由拐角或家具死角导致烟雾扩散有聚集死角的情况存在,会对探测和定位过程造成很大的影响,仿真实验中的移动机器人在探测和定位火警点中的轨迹可以看出死角的存在虽然影响了对火警点的探测,但最终还是能够探测和定位到火警点,其路径轨迹表现出很好的一致性和连续性。     

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.     

Active visual localization for multiple inspection robots

In the routine inspection of industrial or other areas, teams of robots with various sensors could operate together to great effect, but require reliable, accurate and flexible localization capabilities to be able to move around safely. We demonstrate accurate localization for an inspection team consisting of a robot with stereo active vision and its blind companion with an active lighting system, and show that in this case a single sensor can be used for measuring the position of known or unknown scene features, measuring the relative location of the two robots and actually carrying out an inspection task.     

PIRF-Nav 2.0: Fast and online incremental appearance-based loop-closure detection in an indoor environment

This paper presents a fast and online incremental solution for an appearance-based loop-closure detection problem in a dynamic indoor environment. Closing the loop in a dynamic environment has been an important topic in robotics for decades. Recently, PIRF-Nav has been reported as being successful in achieving high recall rate at precision 1. However, PIRF-Nav has three main disadvantages: (i) the computational expense of PIRF-Nav is beyond real-time, (ii) it utilizes a large amount of memory in the redundant process of keeping signatures of places, and (iii) it is ill-suited to an indoor environment. These factors hinder the use of PIRF-Nav in a general environment for long-term, high-speed mobile robotic applications. Therefore, this paper proposes two techniques: (i) new modified PIRF extraction that makes the system more suitable for an indoor environment and (ii) new dictionary management that can eliminate redundant searching and conserve memory consumption. The results show that our proposed method can complete tasks up to 12 times faster than PIRF-Nav with only a slight percentage decline in recall. In addition, we collected additional data from a university canteen crowded during lunch time. Even in this crowded indoor environment, our proposed method has better real-time processing performance compared with other methods.     

A speeded-up online incremental vision-based loop-closure detection for long-term SLAM

An online incremental method of vision-only loop-closure detection for long-term robot navigation is proposed. The method is based on the scheme of direct feature matching which has recently become more efficient than the Bag-of-Words scheme in many challenging environments. The contributions of the paper are the application of hierarchical k-means to speed-up feature matching time and the improvement of the score calculation technique used to determine the loop-closing location. As a result, the presented method runs quickly in long term while retaining high accuracy. The searching cost has been markedly reduced. The proposed method requires no any off-line dictionary generation processes. It can start anywhere at any times. The evaluation has been done on standard well-known datasets being challenging in perceptual aliasing and dynamic changes. The results show that the proposed method offers high precision-recall in large-scale different environments with real-time computation comparing to other vision-only loop-closure detection methods.     

基于姿态测量模块和闭环检测算法的仿生SLAM研究

基于传感器模型的SLAM导航策略精度较高,但由于摩擦等因素误差长时间累计会造成里程计的漂移现象.依靠视觉里程计进行导航的RatSLAM系统,通过在局部场景细胞中引入闭环检测策略实现累计误差的校正,在静态环境下具有一定的鲁棒性,但在复杂场景里,如移动障碍物的出现,视觉里程计会提取到错误的速度等姿态信息,导致航迹出现较大偏移,有时无法通过场景重定位进行闭环校正.结合两种模型的优势提出一种带姿态测量模块和闭环检测算法的仿生SLAM模型.实验表明,相较于仅带带闭环检测的RatSLAM系统或仅由姿态测量模块构成的导航系统,本文提出的新系统更能适应长期复杂场景下的导航,且鲁棒性更强.     

A taxonomy for multi-agent robotics

A key difficulty in the design of multi-agent robotic systems is the size and complexity of the space of possible designs. In order to make principled design decisions, an understanding of the many possible system configurations is essential. To this end, we present a taxonomy that classifies multi-agent systems according to communication, computational and other capabilities. We survey existing efforts involving multi-agent systems according to their positions in the taxonomy. We also present additional results concerning multi-agent systems, with the dual purposes of illustrating the usefulness of the taxonomy in simplifying discourse about robot collective properties, and also demonstrating that a collective can be demonstrably more powerful than a single unit of the collective.The support of NSERC Canada is greatfully acknowledged.     

移动机器人同时定位与地图创建研究进展

对移动机器人的同时定位与地图创建􀁫(Simultaneous Localization and Mapping)的最新研究进行了综述.指出SLAM 面临的问题,介绍了SLAM的基本实现方法.通过对各种改进的SLAM实现方法的性能对比,详尽地分析了如何降低SLAM的复杂度、提高SLAM的鲁棒性等关键技术问题,同时对多机器人协作的SLAM也进行了论述.探讨了SLAM的研究与发展方向.􀁱     

一种改进的超高压输电线路巡检机器人越障方法

介绍了一种新型的超高压输电线路巡检机器人,阐述了分阶段的控制策略．主要针对越障的工程实际问题,从理论上分析了越障阶段的难点：质心调节,输电线的辨识与定位问题．进行了仿真和试验,验证了控制策略和理论分析的正确性．     

High-level mobility controller for a remotely operated unmanned land vehicle

The U.S. Army Laboratory Command, as part of the Department of Defense Robotics Testbed Program, is developing a testbed for cooperative, real-time control of unmanned land vehicles. The program entails the development and integration of many elements which allow the vehicles to perform both autonomous and teleoperated functions. The National Institute of Standards and Technology (NIST) is supporting this program by developing the vehicle control system using the Real-time Control System (RCS) architecture. RCS is a hierarchical, sensory-based control system, initially developed for the control of industrial robots and automated manufacturing systems. NIST is developing the portions of RCS that control all vehicle mobility functions, coordinate the operations of the other subsystems on the vehicle, and communicate between the vehicle and the remote operator control station. This paper reviews the overall control system architecture, the design and implementation of the mobility and communication functions, and results from recent testing.This work is funded by the U.S. Army Laboratory Command. This paper was prepared by U.S. Government employees and is not subject to copyright. Equipment listings do not imply a recommendation by NIST.     

基于物联网技术的管网巡检系统

本文系统介绍了基于物联网技术的管网巡检系统的系统架构、技术路线及功能设计,并对系统综合利用当前最先进的物联网、移动互联网、移动GIS、智能终端以及首创的图文导航等创新技术应用进行了详细介绍,最后对系统应用效果作了客观的评价。     

Optimizing the Scalability of Network Intrusion Detection Systems Using Mobile Agents

Modern Intrusion Detection Systems (IDSs) are distributed real-time systems that detect unauthorized use or attacks upon an organization's network and/or hosts. The components of most distributed IDSs are arranged in a hierarchical tree structure, where the sensor nodes pass information to the analyzer nodes. Optimal placement of the analyzer nodes results in an improved response time for the IDS, and isolation of attacks within the IDS network. Since the network topology and workload are constantly changing, we are able to maintain near-optimal placement of the analyzer nodes by instantiating them as mobile agents. The analyzer nodes may then relocate, reproduce or be deleted as necessary. Such flexibility improves the response times and the stability of an IDS. The movement of the analyzer nodes also offers some protection against denial-of-service attacks, since secure analyzer nodes will be relocated to take over some of the functionality of the host under attack.     

基于移动代理和免疫原理的IDS模型研究

目前的入侵检测系统大多是等级结构的,容易出现单点失效和网络拥塞问题,把移动代理技术和人工免疫原理应用到入侵检测系统(IDS)中,充分结合二者的优点,使IDS具有更高的容错性和健壮性。     

不同跟随策略下RMFS调度问题研究

随着电商行业的快速发展,移动机器人仓储系统(robotic mobile fulfillment systems,RMFS)在现代化物流中心被广泛应用.在RMFS中,机器人在一次分拣搬运任务中,可以采用完全跟随或不跟随两种策略,即机器人可以全程跟随拣选货架直至该任务完成;或者当货架在工作站排队时机器人离开货架去执行其他任务.针对两种跟随策略下的机器人调度问题,以机器人完成批次任务的总时间最短为目标,建立了两种跟随策略下的机器人调度模型,并基于遗传算法设计了两种跟随策略下的仿真实验平台,通过仿真实验对完全跟随与不跟随两种策略下的系统性能进行了比较,得出了基于完工时间最短的跟随策略决策决策曲线,证明结合具体工况选择合适的跟随策略能够有效提高拣货系统作业效率,利用跟随策略曲线可以帮助企业进行机器人跟随策略的选择.