基于光斑室内移动机器人的定位导航技术

现代建筑室内结构日益复杂化,特别是伴随人口老龄化的加剧,家庭安全问题引起人们广泛关注。为了解决室内定位与导航的问题,提出基于光斑室内移动机器人的定位与导航技术,依靠机器人自带红外发射装置与外带摄像头相结合,实现室内情况下对机器人的精确定位与准确导航,并且可以广泛应用于扫地机器人、家庭监控机器人等家庭服务机器人,为实现机器人自动路径规划、自动充电、自动巡航、自动避障等功能提供保障。     

室内移动机器人新型视觉导航系统设计

视觉导航作为一种重要的机器人导航方式正日益受到人们的关注,为了解决目前采用视觉导航存在的算法设计复杂、导航性能差等问题,提出一种新的室内移动机器人视觉导航系统设计方案。首先阐述了该导航新方法的设计思想,然后介绍了采用该方法的导航系统的整体结构设计。利用放置在室内固定位置的摄像机采集室内环境的视频图像,设计了实时图像分析算法实现障碍物躲避、机器人位置跟踪等功能,为机器人的行走提供导航依据,同时通过无线通信的方式发送控制指令,实现对室内移动机器人的行走过程导航控制。     

基于激光SLAM的助老服务机器人建图导航技术研究

机器人的应用方向主要是自身定位、地图构建以及自主导航等,本设计的机器人从实际需求出发,针对老人行动不便的这一问题,自主设计了基于ROS和激光SLAM的助老服务机器人自主导航系统。该机器人主要是实现自主导航与实时建图,机器人通过自主路径规划可以实现在室内任意区域自主移动。老人可以通过语音呼唤让机器人到达指定的位置,从而实现助老的目的。该机器人利用gmapping、导航、语音等功能包实现建图导航及语音控制。利用温湿度传感器检测展厅内温湿度及二氧化碳情况,使用光电传感器检测室内光照度情况,使用电机驱动模块配合电机驱动机器人移动。结果表明该助老服务机器人可以实现自主导航及语音交互等功能。     

预测行人运动的服务机器人POMDP 导航

为提高室内动态环境下服务机器人对行人的自然避让能力,对人的运动轨迹模式进行建模,在此基础 上引入了将行人运动长、短期预测结合起来的方法．为适应传感器噪声及网络延迟等因素所造成的感知—控制回路 中的多源不确定性,将人与机器人的相对位置关系建模为部分可观的马尔可夫状态．采用部分可观的马尔可夫决策 过程（POMDP）进行多源不确定性下的概率决策,协调控制机器人全局路径规划、反应式运动及速度控制等行为模 块．实验结果验证,它能够实现提前避碰的安全导航,因避免反复的曲折与徘徊运动而提高了机器人导航效率．     

基于多传感器信息融合的机器人导航与定位技术研究

移动机器人已经服务于各个领域,作为室内移动机器人服务的前提是实现机器人精准定位。文章介绍了一种射频识别（Radio Frequency IDentification,RFID）和即时定位与地图构建（Simultaneous Localization and Mapping,SLAM）多传感器融合库存盘点机器人精准导航与定位的方法。通过读取布置在环境中的RFID标签,获取机器人的大概位置信息和准确运动状态,然后结合SLAM技术实现精准定位。实验结果表明,该方法可以使库存盘点机器人精准定位,且系统搭建简单、成本低,对室内机器人定位具有参考价值。     

服务机器人社会意识导航方法综述

为提升服务机器人的社会可接受性,与人共融的社会意识导航一直是服务机器人研究领域的热点之一。重点对服务机器人社会意识导航方法展开综述,概述了服务机器人社会意识导航总体框架及主要研究方法;详细总结了基于社会空间关系模型（包括社会力模型和高斯模型）、基于社会行为学习及基于行人轨迹预测的社会意识导航方法;对服务机器人社会意识导航未来的发展趋势进行了展望。     

双平面导航机器人系统在不同骨科适应症中的应用研究

从双平面定位算法和模块化导航机器人两方面阐述了双平面导航机器人系统．该系统通过对映射算法和导航机器人结构的调整，来适应不同的骨科适应症．本文从工作空间、投影模型、定位算法、临床实验及评价指标等方面介绍了双平面导航机器人系统在胫骨髓内钉、股骨髓内钉、股骨颈空心钉和骨盆骶髂关节螺钉这四种不同的骨科手术适应症中的应用研究情况．     

健康服务机器人室内导航视觉传感器研究与开发*

针对健康服务机器人室内导航的应用需求,设计出一种基于STM32F429的嵌入式导航视觉传感器,内嵌500万像素CMOS图像传感器和拥有高性能无线SOC的ESP8266,此次开发的视觉传感器,不是一般的CMOS图像传感器,而是综合了图像感知,图像处理,无线通信,节电唤醒等等功能于一体的智能化微型装置,即眼睛加大脑。经测试,本导航视觉传感器能够以每秒3次的速度向服务机器人发送位置,完全满足室内移动机器人的移动需求。     

智能空间助老助残服务机器人人机协作导航

针对具有基本认知行为能力的行动不便老人、肢残人士、运动和语言患者这类服务对象,构建了助老助残服务机器人人机一体化导航系统。用户与机器人之间进行交互,自由切换随机行走和自主导航2种运动模式,机器人根据现场环境和作业条件的不同,实时触发人机条件响应生成规则而产生相应的行走行为,作业时人机界面同步呈现虚实结合、实时交互的智能空间,实现人机一体化感知、决策与执行。以移动作业服务机器人为对象进行室内人机一体化导航作业,验证了该人机一体化导航系统的可行性。     

一处室内轮式自主移动机器人的导航控制研究

介绍了一种室内移动机器人CASIA-I.对该机器人的运动机构做了较为详细地阐述, 针对该运动机构给出了机器人的运动方程和一种导航控制算法,并根据该算法进行了软件仿真 和实物实验.在软件仿真和实物实验两种环境下,机器人都能够实时避开障碍物奔向目标.仿真 和实验表明:该移动平台具有良好的可靠性,且该导航控制算法是一种有效的导航算法.     

A Navigation System for Cleaning Robots

Free navigation in indoor environments is one of the main enabling technologies for many service robot applications. The SIEMENS navigation system SINAS which is primarily targeted towards cleaning robot applications, has proved its suitability for tough everyday operation since August 1996 on several occasions, e.g., in several chain store supermarkets. This paper discusses the main requirements of a navigation system for cleaning robots, presents the architecture and main modules of the SINAS system, and reports on real-world experiences.     

室内移动机器人导航中信息获取方法研究综述

应用传感器感知环境信息实现室内移动机器人导航是自主移动机器人最基本、也是最关键的方法。本文对室内移动机器人导航所采取的信息获取方法进行了综述,分析比较了各国研究人员为实现室内自主移动机器人导航所采用的各种不同的信息获取方法及多传感器融合算法。并总结了各种方法的优缺点。探讨了现有的信息获取方法的存在的难点问题,并提出了该研究的发展方向。     

An indoor localization system in a multiblock workspace

As service robots and other ubiquitous technology have evolved, an increasing need for the autonomous navigation of mobile objects has arisen. In a large number of localization schemes, the absolute-position estimation method, which relies on navigation beacons or landmarks, has been widely used as it has the advantages of being economical and accurate. However, only a few of these schemes have expanded their application to complicated workspaces, or those that have many rooms or blocks. As the navigation of mobile objects in complicated workspaces is vital for ubiquitous technology, multiblock navigation is necessary. This article presents methodologies and techniques for the multiblock navigation of the indoor localization system with active beacon sensors. This new indoor localization system design includes ultrasonic attenuation compensation, dilution-of-precision analysis, and a fault detection and isolation algorithm using redundant measurements. This work was presented in part at the 13th International Symposium on Artificial Life and Robotics, Oita, Japan, January 31–February 2, 2008     

Building geometric feature based maps for indoor service robots

This paper presents an efficient geometric approach to the Simultaneous Localization and Mapping problem based on an Extended Kalman Filter. The map representation and building process is formulated, fully implemented and successfully experimented in different indoor environments with different robots. The use of orthogonal shape constraints is proposed to deal with the inconsistency of the estimation. Built maps are successfully used for the navigation of two different service robots: an interactive tour guide robot, and an assistive walking aid for the frail elderly.     

基于认知模型的室内移动服务机器人人机耦合协同作业机制

针对老年人和残疾人这类特殊用户群体与服务机器人构成的人机智能系统,提出了基于ACT-R(理性思维的适应性控制)认知架构模型的室内移动服务机器人人机耦合协同作业机制.基于ACT-R认知架构对人机一体化室内移动服务机器人人机协同作业系统进行了总体设计,利用简单自然的人机效应通道,设计了基于ACT-R认知架构的人机耦合界面;通过人-机-环境空间感知耦合,提出并建立了室内移动服务机器人人机一体化协同决策作业机制.最后在室内环境下进行移动服务机器人人机协同作业实验,系统安全高效地完成了作业任务,验证了该机制的有效性.     

A Human–Robot Cooperative Learning System for Easy Installation of Assistant Robots in New Working Environments

One of the applications of service robots with a greater social impact is the assistance to elderly or disabled people. In these applications, assistant robots must robustly navigate in structured indoor environments such as hospitals, nursing homes or houses, heading from room to room to carry out different nursing or service tasks. Among the main requirements of these robotic aids, one that will determine its future commercial feasibility, is the easy installation of the robot in new working domains without long, tedious or complex configuration steps. This paper describes the navigation system of the assistant robot called SIRA, developed in the Electronics Department of the University of Alcalá, focusing on the learning module, specially designed to make the installation of the robot easier and faster in new environments. To cope with robustness and reliability requirements, the navigation system uses probabilistic reasoning (POMDPs) to globally localize the robot and to direct its goal-oriented actions. The proposed learning module fast learns the Markov model of a new environment by means of an exploration stage that takes advantage of human–robot interfaces (basically speech) and user–robot cooperation to accelerate model acquisition. The proposed learning method, based on a modification of the EM algorithm, is able to robustly explore new environments with a low number of corridor traversals, as shown in some experiments carried out with SIRA.     

A faster path planner using accelerated particle swarm optimization

The idea of placing small mobile robots to move around in a large building to detect potential intruders has been around for some time. However, there are still two major hurdles to overcome: to locate itself in the environment and to make a decision on how to move around safely and effectively at a reasonable computation cost. This paper describes a mathematical model for developing a scheme for an autonomous low cost mobile robot system using visual simultaneous localization and mapping and accelerated particle swarm intelligent path planner. The results indicated that this system could provide a solution for the problem of indoor mobile robot navigation. Advances in computer technology make this technique a cost effective solution for a future home service robot.     

Vision for mobile robot navigation: a survey

Surveys the developments of the last 20 years in the area of vision for mobile robot navigation. Two major components of the paper deal with indoor navigation and outdoor navigation. For each component, we have further subdivided our treatment of the subject on the basis of structured and unstructured environments. For indoor robots in structured environments, we have dealt separately with the cases of geometrical and topological models of space. For unstructured environments, we have discussed the cases of navigation using optical flows, using methods from the appearance-based paradigm, and by recognition of specific objects in the environment