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月球探测机器人及其关键技术浅析王 巍1,梁 斌2,强文义1(1.哈尔滨工业大学 控制科学与工程系,黑龙江 哈尔滨150001 ;2.国家高技术航天领域空间机器人工程研究中心,北京100080)摘 要:参考国内外月球探测的现状,对月球探测机器人的关键技术进行了分析;根据月球探测机器人的任务要求,提出了开发我国月球探测机器人系统的具体实现方案.在该方案中,采用 “虚拟样机” 技术,建立一个集三维实体设计、 动力学建模、 控制、 可视化仿真于一体的虚拟月面计算机仿真环境,对月球机器人的静力学、 运动学以及动力学进行仿真研究,为月球探测机器人结构参数、 动力学参数及控制算法的优化提供了设计参数和验证场所;针对月面的复杂环境,提出建立一套智能传感系统的思想,从而实现机器人在复杂、 未知的环境中的自主导航与控制.关键词:月球探测机器人;虚拟样机;自主导航与控制中图分类号: TP114 文献标识码: A 文章编号: 036726234(2001)0320321205A general lunar roving robot and its critical technologyWANG Wei1, LIANGBin2, QIANG Wen2yi1(1. Dept. of Control Science and Engineering , Harbin Institute of Technology , Harbin 150001 , China ;2. National Space Robotic Center , Beijing , 100080 , China)Abstract : Discussess the critical technology for a lunar roving robot on the background of both domestic &foreign research status quo , suggests a realization project for developing a lunar roving robot system in thelight of the situation in China , by which , avirtual prototypingtechnique to develop a virtual computerbased simulating environment is introduced to integrate 3d design , dynamics modeling , control and visualsimulation to simulate the lunar surface situation and runs further study on the statics , kinematics and dy2namics of the lunar roving robot by taking full advantages of this integrated environment , so that the opti2mization of the structure parameters , dynamic parameter and control algorithm can be conveniently madeavailable and introduces. An intelligent sensing system is introduced to achieve the autonomous navigationand control of the lunar roving robot under the complicated , atrocious , unknown environment on the moon.Key words : lunar roving robot ; virtual prototyping; autonomous navigation and control 月球是当前继公海和南极之后又一争夺热点;它是地球唯一的天然卫星,是人类向外层空间发展的第一步,也可以成为飞向其他星球的基地和中转站.月球上有丰富的矿藏,具有潜在的重大经济意义.月球上没有大气干扰,重力小,磁场收稿日期: 2000 - 06 - 12.基金项目:国家863计划航天领域资助项目(863 - 2 - 4 - 2 - 8) .作者简介:王 巍(1974 - ) ,男,博士研究生;强文义(1937 - ) ,男,教授,博士生导师.小,是理想的科学实验和天文观测场所,也是难得的发射基地.目前又发现在月球两极储备有大量的冰水,具备了人类生存的基本条件,从而使月球可以成为人类最近的永久性空间站1.我国是世界上重要的空间大国之一,月球探测将是我国向星球探测走出的第一步.在进行月球探测、 月球基地建设和维护的各个阶段中,机器人是必不可少的工具和手段,月球探测机器人及遥科学技术将是其中的关键技术.第33卷 第3期 哈 尔 滨 工 业 大 学 学 报 Vol. 33 , No. 32 0 0 1年6月 JOURNAL OF HARBIN INSTITUTE OF TECHNOLOGY Jun . ,2001 1995-2005 Tsinghua Tongfang Optical Disc Co., Ltd. All rights reserved.1 月球探测机器人的任务要求月球探测的目的是为将来在月球上建造月球基地、 月球天文台以及有效地利用月球资源作准备.为此要完成观测月面活动时的放射线、 太阳风和陨石等状况,考察月球的地质、 地壳结构,探测月球资源储量等多项任务.为了达到上述目的,月球探测机器人必须满足下列要求:(1)月球探测机器人着陆后可能遇到各种各样的地理环境,这就要求月球探测机器人具有灵活性好、 机动性强的特点.同时,月球探测机器人应具备向各个方向行驶的能力,还应该具有原地打转的本领;这两个方面的结合,是月球探测机器人能够选择最佳路径的前提2.(2)月球探测机器人要有较好的爬坡和越障能力.要满足这样的要求,月球探测机器人应具有较强的驱动能力,因此采用多轮驱动的方式3.(3)为了月球探测机器人的安全和便于控制,要求月球探测机器人的速度相对较慢.因为车载控制系统接收到传感器的信号,并经过分析和处理,然后发出控制指令,是需要一定时间的;更何况月球探测机器人的控制除了自主控制之外,还有一定程度的遥操作,而这时还必须考虑地球与月球之间一个指令周期的时延.另外,月球上的重力虽然只有地球上的六分之一,但惯性是不变的.因此,月球探测机器人的运动速度必须有一个上限.2 月球探测机器人研究现状2. 1 月球探测机器人国外研究现状世界各国开发、 研制星球探测机器人系统已经有了多年的历史.由于星球探测机器人在任务、 功能、 结构、 控制方法、 主要问题等方面有很多类似之处,对其他星球探测机器人系统4的分析也将有助于月球探测机器人系统的研制.2. 1. 1 美国Rocky7 由美国J PL研制,用于在地面完成一段长距离(约50 km)的自主控制的旅行实验,以验证2010年左右发射自主控制的火星漫游车的可行性,如图1所示.Rocky7采用六轮摇杆悬吊式机械结构;带有黑白CCD立体相机三对,太阳姿态敏感器,三个石英陀螺加速计,车轮光学编码器.安装在底盘旁边的四自由度机械臂可以进行挖掘、 倾卸和抓取石块.安装在太阳能帆板的狭槽中具有三个自由度的较长的机械臂,可以将一个立体相机和滤光器支起高出地面1. 4 m;应用这些相机可以实时观测整个车体,并可以将一个重达0. 5 kg的仪器罐送到漫游者周围的目标处.有效载荷包括一个接近可见光反射比的分光仪,用于车上机械臂的定点和定位.彩色立体成像仪滤光器,在桅杆上装有一台带有RGB过滤器的CCD相机.带有多光谱LED显示功能的近焦距CCD相机和莫斯比犹尔分光仪,用于检测岩石和土壤中铁含量飞行检测仪.图1Rocky7结构图Fig. 1Over view of Rocky 72. 1. 2 索杰纳 由美国J PL在Rocky系列的基础上改进而成.由1997年7月发射到火星表面上,在火星探路者的可视范围之内,进行科学实验,如图2所示.图2 索杰纳整体视图Fig. 2Over view of SojournerSojourner整体结构基本上是按Rocky4设计的,采用六轮摇杆悬吊式结构,角上的4个轮有驱动和控制能力,一共有10个驱动部件.另外,在表面安装了一套特制的抗强辐射的零件.内部选用的电子元器件具备抗超高温、 超低温、 强辐射能力.有 效 载 荷 包 括 质 子、X射 线 分 光 计(APXS) ,车载电源采用镓砷太阳能电池和一块基本电池,最高功率可以达到16 W.采用航空速冻胶进行隔热,使索杰纳在火星的黑夜里能够保证- 40 以上的温度.2. 1. 3Nomad由美国CMU机器人研究所研制而成,于1997年通过了在智利阿特卡马沙漠上的测试.见图3 ,Nomad由四轮驱动和导向,采用了测距仪、 倾斜仪、 陀螺、 惯量计和GPS等比较传统的仪器结合起来进行定位.在已经获得了地形223哈 尔 滨 工 业 大 学 学 报 第33卷 1995-2005 Tsinghua Tongfang Optical Disc Co., Ltd. All rights reserved.图的地方,采用全景地平线成像技术进行定位.有效载荷包括天气传感器,包括测温计、 湿度计和风速测量仪.另外,在车顶的一个面板上装有三个彩色CCD相机,用于地质学的研究.图3Nomad整体视图Fig. 3Over view of Nomad2. 2 月球探测机器人国内研究现状为了迎接国际航天科技的挑战,在国内以航天科技集团502所、 清华大学、 哈尔滨工业大学、国防科技大学以及中国科学技术大学为主的一些高等院校和科研机构,相继开展了有关月球探测及遥科学方面的研究工作.在502所作者承担了 “月球表面探测机器人方案研究” 的 “863” 项目,运用 “虚拟样机” 技术构造了虚拟月面计算机仿真环境,对月球表面探测机器人的动力学特性进行了分析和仿真研究,对机器人的机械结构进行了优化设计,同时对月球表面探测机器人的关键技术进行了深入的研究.目前,对于本课题的研究已经做了大量的工作,并取得了很好的成果.清华大学在月球表面环境及月球巡游车几何建模方面做了大量的工作,并对所采用的电机进行了一定的研究.国防科学技术大学贺汉根教授领导的研究小组以Sojouner为蓝本,研制了试验样车,对自主导航及路径规划技术进行了研究.中国科学技术大学空间科学研究中心对月球巡游车的总体方案及关键技术进行了一系列的研究工作.此外,哈尔滨工业大学也已启动了月球探测的研究工作,并取得了初步的成果.3 月球探测机器人关键技术在吸收总结国外先进经验和技术的基础上,结合我国国情,国家高技术航天领域空间机器人工程研究中心就月球探测机器人所需执行的任务、 行走机构、 自主导航与控制、 路径规划、 环境辨识、 机器人系统动态辨识、 遥操作、 搭载仪器的小型化与轻型化、 电源、 通信以及取样器和科学观测等许多方面都进行了深入地研究.这里仅介绍其中的一部分工作和研究成果.(1)轻小型机械及驱动机构5月球探测机器人的机械结构应体现结构紧凑、 体积小、 质量轻的特点,同时与之配套的驱动机构应具备良好的稳定性和较强的爬坡和越障能力.目前已经出现的行驶机构主要有履带式、 腿式和轮式.其中轮式的效率最高,但适应能力最差;腿式的适应能力最强,但效率最差.(2)大时延遥操作技术月球探测机器人要通过一些复杂地形(如月南极、 环形山等) ,但是由于自身动力有限,加上严重的时延,会大大影响与地面的通信.另外时延本身会使连续遥操作闭环反馈控制系统变得不稳定.因此要使月球探测机器人在一些未知的恶劣环境下保持高度自主,本文采用一种有监督的自决策运行方案,同时采用3D预测仿真图形策略建立月球探测机器人和月球环境的预测仿真图形显示系统,在良好人机界面的条件下进行遥操作.月球探测机器人遥操作系统控制结构如图4所示.图4 月球探测机器人遥操作系统控制结构Fig. 4Telemanipulation of a lunar roving robot323 第3期 王 巍,等:月球探测机器人及其关键技术浅析 1995-2005 Tsinghua Tongfang Optical Disc Co., Ltd. All rights reserved.一方面月球探测机器人可以根据自身携带的计算机进行自主决策,实现一定程度的自主导航、 定位与控制;另一方面月球探测机器人也可以接受地面系统的遥操作控制指令.这种控制方案的优点在于可以提高系统的可靠性、 鲁棒性以及处理不确定问题的快速性.通过遥操作,还可以将人工操作的有关信息记录下来,提供给遥点的机器人系统,有助于提高月球探测机器人的智能水平.(3)自主导航与路径规划文献6中提出了一种基于案例的月球探测机器人自主导航与控制模糊决策算法.虽然取得了一定的成果,但仍存在一些局限性:1)需保留一个属性表;当属性表较大时,维护和查询均需要一定的时间,缺乏实时性. 2)需预先定义一系列算子,以针对不同的目标函数获得其匹配值;然后利用模糊综合决策的方法从候选的匹配结果中获得最终的匹配结果.所使用的算子和模糊决策函数都需用户预先定义,在处理复杂情况时,需用户在线设置. 3)另外,该方法缺乏较强的自学习能力.针对上述局限,为了使月球探测机器人自主导航与控制系统具有很高的智能,本文采用神经网络算法来进行路径规划,使用大量的功能简单的处理单元广泛连接而成一高度非线性的超大规模并行的自适应信息处理系统.由于神经网络把系统的所有信息分散地存储在各个神经元之间的连接中,使得它在处理信息时具有如下优点:a)大规模并行分布处理能力,使其能够在极短的时间内同时处理大量的多维信息;b)由于分布式存储参数,使其具有极强的容错能力和高度的鲁棒性;c)由于所有参数都保存在连接中,神经网络可以通过系统的历史数据进行训练,经过训练的神经网络具有一定的 “泛化” 能力,神经网络这种在线自学习、 自动获取知识和分类的能力,使其具有高度的自适应性和自组织性;d)神经网络还具有可塑性.对于机器人系统智能的获得,分两个阶段来进行:首先是有导师的学习.在地球上作模拟试验,让月球探测机器人逐步掌握人的驾驶经验.然后是月球探测机器人在操作人员监控下的自主导航与控制.这样月球探测机器人就能获得无导师的学习能力,从而自动完成一些操作,但动作的评判仍由人工来完成.在月球探测机器人不能处理的情况下,仍由操作人员提供选择,强化月球探测机器人进行学习.(4)多种传感器信息融合技术考虑到月面的情况比较复杂,为了使月球探测机器人实现灵巧而又安全的导航与控制性能,除了在机械结构和控制方面需要做很多工作之外,能否赋予月球探测机器人对其所处的环境进行切合实际的感知、 识别和建模的能力是一个关键.采用多传感器信息融合技术来解决这个问题.(5)信号的压缩、 传输与恢复由于通信距离远,月球探测机器人的发送信号功率和天线增益低,上行和下行链路的信噪比都极低,考虑采取伪随机扩频调制方式,用几十倍甚至上百倍的信道带宽换取信号增益.这里需要根据传输的数据类型和速率确定合适的扩频码,还要选择合适的信道编码,进一步提高信道抗干扰能力.另外,由于月球探测机器人向地球传送10 Mbps左右的宽带数据,再经过几十至上百倍的扩频,信道必须能够提供几十Mbps的带宽.研究表明,最有效的传输频段是EHF频段,这也有利于系统本身模块化、 微型化和极窄波束的形成.所以为了适应地月间的远距离数据传输,必须研制EHF频段大功率线性放大模块,需要在功率器件、 功率合成、 小型化、 模块化和散热等方面攻关.对于宽带扩频数据,必须研究高速数字调制解调技术.除此之外,还要对月球探测机器人的观测和分析数据在传输前和接收后进行高比例无损或近似无损压缩和解压缩.(6)能源问题月球探测机器人车载电源应能够完成三项任务:提供动力,仪器舱加热以及做仪器的电源.目前可选择的方案有:化学电池、 燃料电池、 太阳能电池和同位素电池.其中化学电池和燃料电池的寿命有限,无法满足要求,而太阳能电池也由于对太阳的过分依赖而不能在一些特殊的环境里工作(月夜长达几十天) .作者认为同位素电池由于对环境适应能力强,体积小,寿命长210 a ,功率密度大,是一种比较合适的选择方案.4 基于虚拟样机技术的仿真研究“虚拟样机” 技术是一个全新的概念,是在建造第一台物理样机之前,研究人员利用软件技术建立的机械系统计算机三维实体模型,进行仿真分析并以图形显示该系统在真实工程条件下的运动特性,从而修改并优化设计方案.它具有如下优点:(1)在真实系统出来之前,预测系统的行为;(2)在短时间内,进行多种设计的比较研究;423哈 尔 滨 工 业 大 学 学 报 第33卷 1995-2005 Tsinghua Tongfang Optical Disc Co., Ltd. All rights reserved.(3)在设计早期阶段确定关键的设计参数;(4)与真正的物理实验相比,仿真方法更经济,灵活性更好;(5)可视化的给出系统的行为;(6)实现CAD/ Control设计环境的集成.通过 “虚拟样机” 模型与控制系统设计软件(如MATLAB)相结合,能自行地仿真分析系统中所含有的非线性特性,改进控制系统的设计,最终达到机电一体化的优化结果,大大提高了系统方案的可行性.过去需要数星期、 数月才能完成的建造和测试物理样机的工作,现在利用 “虚拟样机” 技术仅需几个小时就可以完成.目前国家高技术航天领域空间机器人工程研究中心正在进行月球探测机器人系统虚拟样机及遥操作技术的研究.在对三维月球探测机器人系统模型进行动力学仿真的基础上,确定最佳月球探测机器人系统结构、 控制及遥操作方案,以更快、 更可靠地发展我国月球探测机器人系统7.5 结 论本文在总结当今国外月球探测经验基础上,结合我国国情,对月球探测的关键技术问题进行了深入地分析和研究,提出了开发我国月球探测机器人系统的具体实施方案.在该方案中,引入了智能控制的思想,提出了利用神经网络进行自主导航和路径规划的策略,从而建立一套智能传感系统,使其能够辨识目标并对其进行跟踪,避免与障碍碰撞,并且能够从自身环境中加以学习和修正,弥补了文献6 中方案的不足.同时,采用“虚拟样机” 技术,建立一个集三维实体设计、 动力学建模、 控制、 可视化仿真于一体的虚拟月面计算机仿真环境,对月球机器人的静力学、 运动学以及动力学进行了仿真研究,为月球机器人结构参数、动力学参数及控制算法的优化提供了的设计参数和验证场所.参考文献:1王旭东,梁斌,吴宏鑫,等.面向21世纪的我国遥科学空间机器人发展的建议A.空间机器人及遥科学技术研讨会论文集C. s l :s n ,1999.2KUNII Yasuharu , OTSUKA Masahiro. Tele2scienceby planetary rover : micro5 A .Fifth InternationalSymposium on Artificial Intelligence , Robotics andAutomation in SpaceC. s l : s n , 1999. 5532558. 3 KURODAYoji ,KONDOKoji ,NAKAMURAKazuaki ,et al.Low power mobility system for mi2cro planetary roverMicro5 ”A. Fifth Interna2tional Symposium on Artificial Intelligence , Roboticsand Automation in SpaceC. s l :s n , 1999.77282.4骆训纪,孙增圻,朱纪洪.月球探测机器人国外发展概况及我国的发展设想A.空间机器人及遥科学技术研讨会论文集C. s l : s n ,1999. 2152221.5 YOSHIOKA N , WAKABAYASHI Y, NISHIO Y.Driving technology and preliminary tests of a lunarroversA. IFAC 13thtriennial world congressC. sl :s n , 1996. 23228.6凌 彬,陈宗海.月球探测器路径规划的基于案例的学习算法研究A.中国科学技术大学空间信息中心月球车调研资料选编C. s l :s n , 2000.33238.(责任编辑 闫 彤)(上接第320页)参考文献:1闵桂荣.卫星热控技术 M.北京:宇航出版社,1991. 14 - 22.2陆 征.卫星热控制系统状态监测与故障诊断专家系统D.哈尔滨:哈尔滨工业大学, 1999.3RHEINBOLDT W. Numerical analysisof continuationmethods for nonlinear structural problemsJ . 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All rights reserved.第!卷第#期! $ $ % 年 ! 月兵工学报&(& &)*&*+,(&)-./01! ,/1#! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !2341!$%基于航向示教再现的履带式移动机器人路径跟踪龚建伟高峻尧熊光明（北京理工大学机器人研究中心， 北京， #$5#）摘要本文阐述了一种基于航向示教再现的履带式移动机器人路径跟踪控制方法， 人工示教时， 从示教路径起点至终点， 每隔一定距离记录移动机器人航向形成示教文件， 再现控制复现了示教文件记录的航向与里程的航迹推算函数关系。实验结果表明， 这种方法与有限的遥控干预相结合， 仅用电子罗盘和里程计两种设备可简单、 有效地实现移动机器人的路径跟踪。结合实验结果， 对利用该方法进行路径跟踪的误差形成原因及其消除方法进行了分析。关键词机器制造自动化；示教再现；移动机器人；航向控制；路径跟踪中图分类号(6!为进行火炮动目标射击试验， 需研制一种重型移动机器人拖带靶车在地面按预定路径运动， 它是一台无人驾驶车辆， 可遥控行驶。但在无道路、 标志物很少的空旷地带， 完全由遥控驾驶员操纵重型无人车辆在规定路径上高速行驶， 驾驶员会处于高度紧张状态， 在大转向时常出现转向不到位或过头的现象。本文利用航向示教再现控制原理使之具有一定的自主行驶属性， 实现了履带式移动机器人的航向和路径跟踪。示教再现方法通常用于工业机器人操作#， !， 其一般过程是： 示教阶段通过人工参与让机器人到达规定的位姿， 记录下各关节传感器信息，再现阶段将这些信息和传感器的实时反馈信息比较， 并通过某种控制算法来控制机器人的运动， 重现示教的位姿。示教再现在特定环境下有许多优点：能有效减少控制算法的开发工作， 比较容易实现复杂的动作， 还能降低传感器等硬件的投入等。!履带式移动机器人系统组成整个活动靶车系统由遥控指挥车、 履带式移动机器人 （含拖带的板靶） 和无线通信设备组成， 其结构如图 #1# 所示。移动机器人是由一辆履带式装甲车改装而成的， 改装后能够在计算机控制下完成全部驾驶操作， 所有的改装不影响原有的人工驾驶功能， 并能和人工驾驶切换。变速系统通过调节油门!$# 年 #! 月收稿， !$! 年 #! 月定稿。开度实现对速度的控制， 速度反馈由里程计得到。转向系统采用液压伺服控制方式， 通过操纵左、 右转向离合器实现转向功能。航向信息由电子磁罗盘提供。车速和航向均为闭环控制。遥控指挥车通过无线通信设备和履带式移动机器人通信， 传送遥控驾驶指令并得到机器人本身和前方道路状况信息。图 #1#履带移动机器人系统结构2781#1#9:;3= ;?3 /A B3=/4703 83 D3B703 ;:;3=航向示教航向示教的过程是： 开启履带式移动机器人上安装的里程计、 电子磁罗盘和示教数据采集程序， 人工驾驶履带式移动机器人从预定的路径起始点至终点行驶， 每隔一定距离记录一次电子磁罗盘提供的航向数据， 航向值是机器人正前方与北向的夹角， 距离间隔是通过里程计的计数脉冲转换得到的， 记录示教信息的程序框图如图 !# 所示。图 !$#航向示教流程图%&$!$#()*+&, -)*./&, 0123 ./*4-若履带式移动机器人在起始点的航向值为!5，以后每行驶! 记录一次航向值， 第 （ # 5， #， ，$）个航向记录点处的航向值为!， 这样就形成了一个以航向值集合表示的路径 % #!5，!#， ，!$ ，记录这些航向值的文件称为航向示教文件。 下面的推算可以说明这些航向值实质上表示的是对起始点的相对坐标。在图!&!中， 坐标原点 （5， 5） 是履带式移动机器人示教的起始点，(轴为北向， ) 轴为东向，（)，(） 表示第 （ # 5， #， ， $） 个航向记录点处的坐标值， 则有)# )*#+ !6&, （!*#）# )*!+ !6&, （!*!）+ !6&, （!*#）# !, # #6&, （!,*#）(# (*#+ !.26 （!*#）# (*!+ !.26 （!*!）+ !.26 （!*#）# !, # #.26 （!,*#）（!&#）从 （!&#）式可以看出， 通过航向示教得到的路径点是近似的， 点 （)，(） 并非履带式移动机器人的实际位置， 从点 （)*#，(*#）到点 （)，(） ， 其实际航向是在区间 !*#，! 变化的， 而且这种误差与记录间隔距离! 有关，! 越小， 误差越小， 但! 的选取又与履带式移动机器人车身长度、 控制计算机和传感器等诸多因素有关。图 !$!推算相对定位方法%&$!$!7)-/2+ 20 4)1*-&8) 926&-&2, 4).:2,&,!航向再现控制航向再现的过程如下： 将履带式移动机器人停放在示教起始点， 其航向尽量与起始点处的示教航向一致， 转向控制系统和速度控制系统在收到再现控制程序发来的转向和速度命令后控制移动机器人行驶。 在示教起始点， 从航向示教文件中读到其初始航向值， 作为转向控制器的期望航向， 以后每隔!读取航向数据来更新期望航向。再现航向的读取程序框图如图 ;# 所示。期望航向和履带式移动机器人行进中的实际航向比较后， 便得到了控制器输入偏差， 控制器输出转向离合器拉杆的行程， 并送给驱动油缸。控制框图如图 ;! 所示。由于履带式移动机器人行驶时振动剧烈， 电子磁罗盘的输出信息在示教和再现时都经过滤波。由于这种由航向与里程形成的航迹推算导航信息存在累积误差， 实际控制中可通过人工遥控干预来进行偏差纠正。再现控制过程中， 指挥车管理程序仍将遥控驾驶仪的操作命令发送给履带式移动机器人的运行控制程序， 转向控制按照遥控优先的原则， 只要遥控转向操作命令有变化， 就优先执行该命令。实验结果及分析实验是在一个开阔的平地进行， 根据履带式移;5#第 # 期基于航向示教再现的履带式移动机器人路径跟踪图 !#航向再现流程图$%&!#()*%+& ,-)./)01 2-34 05)67图 !8航向再现控制框图$%&!8()*%+& ,-)./)01 03+763- 05)67动机器人的特点， 航向控制器只采用 9: （比例积分）控制。图 ;# 是再现时航向跟踪结果。可以看出，航向的再现基本上是准确的， 但在弯道处出现了滞后。由图 ;,(6%?(+7)- 6(=-7图 ;8路径跟踪推算结果$%&;89)75 23-34%+& 6(013+%+& 6(=-7造成航向和路径跟踪偏差的原因一是由于履带式移动机器人行驶时产生的剧烈振动造成的， 电子磁罗盘提供的航向数据不稳定， 尽管经过滤波， 数据跳动仍很大； 二是大型履带式移动机器人本身的行驶特性造成的。该履带式移动机器人已在靶场上完成了动目标射击试验任务。参 考 文 献#杜现， 刘宝生， 赵锡芳 应用于机器人装配的实用示教技术与方法 组合机床与自动化加工技术， 8AA#， 8：; B C8吴威， 赵杰等 焊接机器人在线示教 焊接学报，#DDE，#： #C B#D;A#兵工学报第 8; 卷!#$%& (#)!%&*+,#-.#)/ .#0$ +#(! 12,23%&)2&(42, 124 # (4#)/$ 52.%, 42.2(!#$ %&#()&! %*#+,&#$ !*#$-&#$（!#$%& !()*&+ ,-$*，.%/%-0 1-($%$2$ 3 4&+-506，.%/%-0，788897）!#$%&$: +);%-0 $)&+%-0 #)(; =)$+ 355?%-0 &-$*5 $+; ?%$+ $+ 5)($ ;A%&( 3*$*)&; #%5 *#$ %( =*(-$;B 1- $+ $)&+%-0 =*&(，$+ +);%-0 3 $+ *#$ %( *&*; )-; +5; %-$+ $)&+%-0 3%5 3* )&+ 3%C; ;%($)-&B 4+6 )* $+- 2(; )( $+ ;(%*; +);%-0 %- $+ +);%-0 =5)6#)&-$*55*B 4+ -)A%0)$%-)5 =*%-&%=5 3 $+ $+; %( ;);-%-0B DC=*%-$)5 *(25$( (+? $+)$，&#%-; ?%$+ 5%$; $5&-$*5 %-$*3*-&，%$ &)- 3253%55 $+ =)$+ (%=56 )-; 33&$%A56BE*A*，)&*;%-0 $ $+ C=*%-$)5 *(25$(，$+ &)2( 3 $+ 355?%-0 * %( )-)56F; )-; ( ?)6($ A*& $+ )* 0%A-B()* +,%-#)&+%-*6 )-23)&$2* )2$)$%-，$)&+%-0，#%5 *#$，+);%-0 &-$*5，=)$+ 355?%-!0 简讯 兵工学报 编辑部召开在京常务编委座谈会兵工学报 编辑部于 G88H 年 7 月 GI 日召开了在京常务编委座谈会。 兵工学报 在京常务编委和部分编委参加了座谈， 中国兵工学会副秘书长王智忠出席会议并发言。 兵工学报 主编朱荣桂研究员，兵工学报 副主编、 中国兵工学会副秘书长许毅达共同主持了会议。副秘书长刘春生和学会部主任王秀娟出席了会议。会上， 编辑部姜金涛代表编辑部向与会编委汇报了 兵工学报 编辑部 G88G 年工作进展情况： 编辑部严格按照新一届编委会明确的编辑工作流程处理来稿， 工作质量有了一定提高； 在办公自动化方面实现了编辑人手一台计算机， 开始使用 “审稿数据库系统” ， 由计算机跟踪控制整个审稿过程， 并建立了较为系统的审稿专家数据库。他还汇报了今年工作设想： G88H 年编辑部将试行新的审稿费标准和责任编辑制度， 对有条件的审稿人试行用 J )%5 进行审稿， 力争缩短学报的稿件发表周期， 同时加大对学报的宣传力度， 扩大 兵工学报 的社会影响。与会编委对编辑部一年来的工作给予充分肯定， 认为编辑部的同志们为提高学报的质量及影响做了大量工作， 学报有了欣欣向荣的景象。各位常务编委还就如何提高 兵工学报 质量， 提高学报的知名度和影响进行了热烈讨论。编委提出，兵工学报 作为一级学术期刊， 应努力倡导学术民主， 开展学术批评； 学报要扩大国际影响， 一定要在条件成熟的情况下尽快出版英文版， 并争取尽早改成双月刊。朱主编、 许副主编对各位编委关心学报发展、 热心学报工作的精神表示了感谢， 并向与会编委表达了新春的良好祝福。会后， 副主编许毅达和编辑部人员还专程探望了德高望重的严沛然先生， 对他为学报做出的贡献表示感谢。（ 兵工学报 编辑部）K87第 7 期基于航向示教再现的履带式移动机器人路径跟踪 J. Cent. South Univ. (2013) 20: 6270 DOI: 10.1007/s11771-013-1460-8 A reconfigurable tracked mobile robot based on four-linkage mechanism LUO Zi-rong(罗自荣), SHANG Jian-zhong(尚建忠), ZHANG Zhi-xiong(张志雄) School of Mechatronics and Automation, National University of Defense Technology, Changsha 410073, China Central South University Press and Springer-Verlag Berlin Heidelberg 2013 Abstract: A novel reconfigurable tracked robot based on four-link mechanism was proposed and released for the complicated terrain environment. This robot was modularly designed and developed, which is composed of one suspension and one pair of symmetrical deployed reconfigurable track modules. This robot can implement multiple locomotion configurations by changing the track configuration, and the geometric theory analysis shows that the track length keeps constant during the process of track reconfiguration. Furthermore, a parameterized geometric model of the robot was established to analyze the kinematic performance of the robot while overcoming various obstacles. To investigate the feasibility and correctness of design theory and robot scheme, an example robot was designed to climb 45 slopes and 200 mm steps, and a group of design parameters of the robot were determined. Finally, A prototype of this robot was developed, and the test results show that the robot own powerful mobility and obstacle overcoming performance, for example, running across obstacle like mantis, extending to stride over entrenchment, standing up to elevate height, and going ahead after overturn. Key words: tracked mobile robot; four-linkage mechanism; mobility; reconfigurable robot Foundation item: Project(2007AA04Z256) supported by the National High Technology Research and Development Program of China Received date: 20120113; Accepted date: 20120630 Corresponding author: LUO Zi-rong, PhD; Tel: +8613787202856; E-mail: 1 Introduction Tracked robots have excellent terrain adaptability, powerful mobility and obstacle overcoming ability, and they are widely applied in the military and security fields 1. According to the number and layout of track, current tracked robot can be classified into single track robot 2-3, fin track robot 4, four-track robot 5-7 and six-track robot 8, etc. MATILDA 9 and Lemming 10 belong to the single track robots. The tracks of MATILDA form a slope at the front of the robot body that can improve its obstacle performance. Lemming is a conventional tracked robot with big track wheels. Usually, its a hard mission for single track robots to overcome obstacle higher than track top point. To overcome this weakness, multiple and variable configuration tracked robots were proposed 1112. IRobot of America proposed an improved solution and developed the PackBot series with fin track structures 1314. According to different missions, PackBot robot can be lay out with a pair of fin tracks or two pairs of fin tracks fore-and-aft. By the rotation of the fin tracks, the robot can overcome larger obstacles. Apart from PackBots idea of fin tracked structure and modular design, further related research has been carried out. Inuktun of Canada had developed a scout robot named VGTV, which can change its track configuration according to different terrain environments. When the track is at low positions, the robot works like a military tank. In order to improve the ability of adaptation to terrain and obstacle negotiation, the track can be transformed into a triangle-type track 15. In 2007, Elbit company of Israel developed a reconfigurable robot named VIPER, which integrated the virtue of wheeled and tracked robots. Because the track can be contracted into the wheel, by a track transformation mechanism, the robot has two kinds of locomotion configurations: wheeled and tracked 16. However, along with the increase of mechanisms, this may increase the weight of the robot as well as the energy consumption. According to the description given above, it is clear that the mechanisms of the PackBot and the VGTV are complex, which may increase the difficulties in maintenance and motion control. A property of four- linkage mechanisms is that the total length of all linkage is constant without relationship to the motion state, and the topological structure of the mechanism is maintained. Based on the property of the four-linkage mechanism, a novel reconfigurable tracked mobile robot named RTMBot, as shown in Fig.1, was developed. In this work, a novel mechanical structure and transmission system of the RTMBot were proposed. Furthermore, a parameterized geometric model of the J. Cent. South Univ. (2013) 20: 6270 63 Fig. 1 A reconfigurable tracked mobile robot RTMBot was established to analyze the kinematic performance of the robot while overcoming various obstacles. Finally, a prototype of the robot was developed. 2 Principle of RTMBot 2.1 Structure of RTMBot As shown in Fig. 2(a), the prototype of RTMBot was modularly designed and developed, which is composed of one suspension and one pair of symmetrical deployed reconfigurable track modules. As shown in Fig. 2(b), each reconfigurable track module is composed of one four-linkage mechanism, one track and four tracked wheels. In the prototype, the four-linkage mechanism is composed of suspension, driving crank, driven crank and link. Each reconfigurable track module robot has four tracked wheels surrounded by one track, and the tracked wheels are fixed with link shaft supported by bearings fixed with link shaft with bearings. The power and drive system of RTMBot is shown in Fig. 2(c). The robot has four degrees of freedom driven by Motor M1, M2, M3 and M4, respectively. Motors M1 and M2 are driving motors, and they are utilized to drive driven wheels and produce the translational motion of tracks, by controlling the running speeds of M1 and M2. The robot can move forward or backward in a straight line or turn around at any position. Motors M3 and M4 are configuration motors, and they are used to change configuration of four-linkage mechanism during robot moving, which helps to improve the mobility of tracked robot. 2.2. Geometrical principle of reconfigurable track The principle of the reconfigurable track based on four-linkage mechanism is shown in Fig. 3. The length of the fixed link AD is equal to the length of the link BC, (|AD|=|BC|=L1). The lengths of the cranks AB and CD are also equal, (|AB|=|CD|=L2). The radius of each wheel is r. Fig. 2 Structure and principle of RTMBot: (a) Prototype of RTMBot; (b) Mechanical structure of RTMBot; (c) Driving system of RTMBot Fig. 3 Track reconfiguration principle J. Cent. South Univ. (2013) 20: 6270 64 At any state of the track during reconfiguration, the configuration angle between the crank CD and the fixed link AD is , and the contact angles of the track and wheels are 1, 2, 3 and 4, respectively. Thus, the total length of the track is 121212121222|LLLA AB BC CD D (1) where A1A2, B1B2, C1C2, and D1D2 are the lengths of the contact arc between the tracks and the wheels. The arc lengths can be expressed as the product of radius (r) and angle (1, 2, 3 and 4, respectively), thus the total length is 1212342()()LLLr (2) For any configuration angle , as shown in Fig. 3, 1=3, 2=4, and 1+2=3+4=. Using Eq. (2), the total length is L=2(L1+L2)+2r (3) Equation (3) shows that the total length of the track is determined by the length of the link L1, the length of the crank L2 and the radius of the wheel r, which is independent of the configuration angle . So, the length of the track remains constant in the reconfiguring process. 2.3 Locomotion configurations of RTMBot The RTMBot can implement multiple locomotion configurations by changing the track configuration. Thus, the robot can adapt to the complicated terrain environment, such as step, stairs and entrenchments. 2.3.1 Climbing up obstacle The structure of RTMBot is symmetrical in the front and back, which means that the robot can overcome obstacles uniformly in both directions. As shown in Fig. 4(a) and Fig. 4(b), if the robot meets a vertical obstacle in the forward direction, motors M3 and M4 will start working and turn the driving crank AB clockwise to overcome the obstacle. If the robot moves backward, motors M3 and M4 will rotate reversely and turn the driving crank CD anticlockwise. In this way, the robot can overcome the obstacle successfully, as shown in Fig. 4(c). 2.3.2 Striding over ditch If a RTMBot is confronted with a wide ditch, the configuration motors M3 and M4 will turn the crank AB in line with link AD, which will lengthen the robot and enable it to span across the ditch, as shown in Fig. 4(d). 2.3.3 Getting across obstacles directly If obstacles are small, the configuration motors M3 and M4 are able to drive the crank AB to raise suspension to its optimum height, which enables it to clear the obstacles, as shown in Figs. 4(e) and 4(f). 2.3.4 Moving after overturn Practical circumstances may cause the RTMBot to be overturned, as shown in Fig. 4(g), but even in this position, the robot can reconfigure its tracks and continue to move, as shown in Fig. 4(h). 3 Kinematics model of obstacle climbing 3.1 Geometry model The parametric geometrical model of RTMBot climbing over a step obstacle is shown in Fig. 5. In Fig. 5, Oxy is the robot coordinate system, is the configuration angle between the link CD and the fixed link AD, is the inclined angle between the slope and the horizontal plane, H is the step height, and T is the contact point of the track and the step. It is assumed that the driving force of each motor is large enough for the robot to function, and there is no slipping between the robot and the ground. It is clear that, if geometry center Ob of the track wheel B is higher than the contact point T of the track, the robot can overcome the step successfully. This geometry condition can be expressed as 2sinrLH (4) If Eq. (4) is satisfied during robot overcoming obstacle, the contact point T must be positioned in a track segment between A1A2, A2B1 or B1B2. Furthermore, Taking the robot coordinate system (Oxy) as the reference frame, the coordinate equation of the contact point T(xt, yt) at any segment can be obtained as follows. 1) If the contact point T is positioned between A1 and A2, then the step height (0,cos Hrr, and the coordinate equation of point T is 22t1t/ 2()xLrrHyH (5) 2) If the contact point, T, is positioned between A2 and B1, the step height H(rrcos, r+L2sinrcos, and the coordinate equation of point T is t1t/ 2sin(cos )ctgxLrHrryH (6) 3) If the contact point T is positioned between B1 and B2, then the step height H(r+L2sinrcos, r+L2sin, and the coordinate equation of point T is 22t122t/ 2cos(sin)xLLrrLHyH (7) Since the contact point T is determined, the direction of the contact force Nt between the track and the step can also be calculated. If point T is positioned between A1 and A2, the direction of the contact force Nt will pass through the center of tracked wheel A and contact point T. The azimuth angle between Nt and the x axis, for any J. Cent. South Univ. (2013) 20: 6270 65 Fig. 4 Locomotion configurations of RTMBot: (a) Overcoming an obstacle forward; (b) Climbing over an obstacle; (c) Overcoming an obstacle backward; (d) Stretching to bridge an entrenchment; (e) Raising suspension; (f) Raising suspension to clear obstacle; (g) Robot turning over; (h) Moving after turnover Fig. 5 Parametric geometry model of RTMBot random pair of and H, can be expressed as arcsin()/ ), (0,cos rHrHrr (8) 2) If point T is positioned between B1 and B2, the direction of the contact force Nt will pass through the center of the tracked wheel B and contact point T, and the azimuth angle of contact force Nt is obtained as 222arcsin(sin)/ )(sincos ,sin LhrrHrLrrL (9) 3) If point T is positioned between A2 and B1, the direction of the contact force will pass through point T and normal to the track, and the azimuth angle of the contact force Nt is obtained as 2 / 2(cos ,sincos HrrrLr (10) 3.2 Velocity model It is assumed that the track speed of the robot is V at the moment that the robot contacts the obstacle. It is further assumed that the contact point between the ground and the track is D2, in Fig. 3, and the contact point between the obstacle and the track is T. At any J. Cent. South Univ. (2013) 20: 6270 66 contact point, the instant translational velocity of the robot is Vdt. If it is assumed that there is no slipping at the two contact points, the translational velocity of the track segment D2A1 should equal that of the track segment A2B1 in the direction of D2T. Since this is simply a kinematic model, the direction of gravity and the slope angle need not to be considered. As shown in Fig. 6, Vdt can be expressed as dt1tcos(arctan()/ 2HVVLx 1tcos(arctan()/ 2HVLx (11) By solving Eq. (11), the robot configuration angle, , when overcoming an obstacle, can be determined as 1t2arctan()/ 2HLx (12) Fig. 6 Kinemics model of robot Adopting the idea of differential calculus, and presuming that after a very short time dt, the obstacle height that the robot has overcome is dH, and the displacement along the x-axis is dxt, and presuming that the velocity of the track is V, it gives dsindddtHVtxVt (13) Combining Eqs. (12) and (13), d is given as follows: 1tt1tdd2(arctan()arctan()/ 2d/ 2HHHLxxLx (14) The angle is the control parameter in controlling the track configuration and hence the ability to compute the required value of to overcome particular obstacle geometry is a requirement. Using Eqs. (12), (13) and (14), it is possible to compute the required change in the configuration angle at any time during the process of the robot overcoming the obstacle. 3.3 Torque and stability model In order to dynamically reconfigure the track, by changing the angle , it is necessary to apply an appropriate torque to the active crank AB. During the process of climbing the step, whose height is H, and at the moment of the tracked wheel leaving the ground, the forces on the robot are shown in Fig. 7, which are the gravity force, G, the contact force between the track and the obstacle, Nt, the contact force between the ground and the track, Nd, and the friction force, fd. Fig. 7 Forces analysis of robot Taking the whole robot as a free body and presuming that the point O is the center of rotation of the robot, then, according to the balance conditions of the forces and the torques, there will exist dTdT1ddTtTsincossincossin2 cos()NNGfGNLNfrNxNHhr (15) Then, taking the driving crank AB as the studied object and assuming that the driving torque acting on it is TA, according to the balance condition of the forces and the torques, then there is 1ATTtcos()sin()2LTNHrNx (16) Combining Eqs. (15) and (16), the driving torque of the crank AB can be expressed as 1t1A1t(cos2sin)(cos () sin (/2)sin2cos2sin2cos ()GLrHrxLTLrxHhr (17) When the tracked wheel A is in contact with the obstacle during obstacle climbing, the robot should satisfy the stability condition to avoid overturn. The restrict condition is that the projection of gravity should J. Cent. South Univ. (2013) 20: 6270 67be restricted to the area surrounded by the front and rear wheels, as shown in Fig. 8. The mathematical model for this condition is 11arcsin(/)arcsin(2 /) / 2aHLh L (18) Fig. 8 Anti-inversion condition of robot 4 Design of obstacle climbing To investigate the feasibility and correctness of design theory, an example robot was designed to climb 45 slopes and 200 mm steps. According to the geometry condition Eq. (4) and stability condition Eq. (16), a group of design parameters of the robot were determined, as shown in Table 1. Table 1 Design parameters of RTMbot Parameter Value Parameter Value L1/mm 450 H/mm 200 L2/m 200 G/N 300 r/mm 45 H/mm 45 L/mm 1 611 a /4 4.1 Geometric condition design According to Eq. (4), the relationship between the minimum primary configuration angle and the height H is shown in Fig. 9. It can be concluded that if the obstacles height H is 200 mm, the least configuration angle satisfying the geometry condition of overcoming the obstacle is 50.805. 4.2 Velocity condition design To analyze the influence of the primary configuration angle during the configuration process, it was assumed that the track velocity is 0.5 m/s, and there was no slipping during the obstacle climbing process. According to Section 4.1, the least primary angle satisfying the geometry condition of overcoming the obstacle is 50.805. Four arithmetical progressions were Fig. 9 Relationship between minimum primary configuration angle and obstacle height chosen as the primary angles, which are 51, 64, 77 and 90, respectively. The climbing process includes three steps. In the first step, the robot moves towards the obstacle until the track contacts the obstacle. During this process, the primary configuration angle remains constant, as shown in Fig. 10(a). Fig. 10 Active reconfiguration of configuration angle J. Cent. South Univ. (2013) 20: 6270 68 In the second step, the robot begins to change configuration angle, , to obtain a more suitable angle, according to Eq. (11), and to prepare for overcoming the obstacle. This means that the robots configuration motors M3 and M4 drive crank AB to rotate until the configuration angle satisfies Eq. (12). This configuration step makes the robot in its optimized configuration angle. For example, if the primary angle is 51, the configuration angle changes from 5 to 36, and if the primary angle is 90, the configuration angle changes from 90 to 47. After this configuration process, the center of gravity of the robot will be raised and Eq. (4) and Eq. (12) are both satisfied, as shown in Fig. 10(b) . In the third step, the robot begins to overcome the obstacle with a track velocity of 0.5 m/s. Using Eqs. (12), (13) and (14), the track configuration angle change process can be determined. The change curve of with time is shown in Fig. 10(c). It can be seen that the robot can overcome a 200 mm obstacle at different primary configuration angles between 51 and 90, but with deferent speeds. If the primary angle is 90, the robot can reconfigure to overcome the obstacle within the shortest time, only 0.83 s. If the primary angle is 64, it needs 1.02 s. From the analysis above, it can be concluded that the robot can overcome the obstacle in a shorter time if a larger primary configuration angle is used. 4.3 Torque and stability design According to Eqs. (5)(10) and (17), the relationship between the driving torque of the crank AB, the track configuration angle , and the step height H is shown in Fig. 11. From Fig. 11, it can be seen that, for the same configuration angle , the larger the height of the obstacle, the bigger the driving torque (TA) on the crank AB is required. It can also be seen that, if the obstacle height (H) is less than the track wheel radius (r=45 mm), the smaller the configuration angle, the bigger the driving torque on the crank AB is required. If the obstacle height (H) is larger than the track wheel radius, the bigger the configuration angle, the bigger the driving torque on the crank AB is required. As shown in Fig. 11, if the configuration angle is 90, during overcoming a 200 mm obstacle, the maximal driving torque that the crank AB needs is 20.042 Nm, and this torque can be used to choose the driving motor M1, as shown in Fig. 2. Assuming that the maximal height that the robot can overcome is 200 mm and the maximal angle of slope is 45, using Eq. (18). It is possible to show that the maximal distance permitted between the center of gravity Fig. 11 Driving torque of crank AB needed of the robot and the geometric center of the wheel is 52.48 mm. The height h used in Table 1 is 45 mm, which means that the dimensions of the robot meet the condition for avoiding overturn. 5 Experiments and discussion A RTMBot prototype was developed, as shown in Fig. 2(a). The outline dimensions of the prototype are 700 mm long, 500 mm wide and 300 mm high, and the design parameters are listed in Table 1. A handcart was utilized to test the obstacle overcoming performance of the robot. In Fig. 12(a), the robot moved and approached the obstacle with in-line configuration. On running close the obstacle, the robot reconfigured from the in-line configuration to the parallel link configuration, as shown in Fig. 12(b). While the track contacted the obstacle, the robot changed configuration angle in time and returned the track to its in-line configuration, as shown in Fig. 12(c). Figure 12(d) shows that the robot overcomes the obstacle and leaves the platform. The process of climbing stairs is shown in Fig. 13. In Fig. 13(a), the robot is shown to lower the driving crank in order to climb the first step. Figure 13(b) shows that the robot has returned to its in-line configuration and is climbing the steps. If the robot approaches a small obstacle, such as the stool in the case shown in Fig. 14(a), the robot can reconfigure from its in-line configuration to its parallel link configuration and the suspension is raised, as shown in Fig. 14(b). The robot can pass the obstacle directly, as shown in Fig. 14(c). If the robot suffers turnover, it can lift its body and continue moving in the inverted orientation, as shown in Fig. 15. J. Cent. South Univ. (2013) 20: 6270 69 Fi