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爬墙机器人气压传动系统及控制硬件设计【全套6张cad图纸和毕业论文】

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关键词：: 机器人气压传动系统控制节制硬件设计全套 cad 图纸以及毕业论文

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目录
1 绪论 1
1.1引言 1
1.2国外爬壁机器人研究现状 1
1.3国内爬壁机器人研究现状 2
1.4爬壁机器人的发展趋势 3
1.5课题的目的及意义 3
1.6课题内容及工作思路 4
2 机器人的结构设计 5
2.1 机构设计 5
2.2 动作原理 6
3 爬壁机器人的气压传动系统设计 7
3.1 气压控制回路设计 7
3.2 选择执行元件 8
3.3 真空发生器、过滤器、吸盘的选择 8
3.4选择控制元件 9
3.4.1选择类型 9
3.4.2选择主控阀 9
3.4.3 选择减压阀 9
3.5选择气动辅件 10
3.6 确定管道直径、验算压力损失 10
3.6.1 确定管径 10
3.6.2 验算压力损失 11
3.7 选择空压机 16
3.7.1 自由空气量的计算 16
3.7.2 气缸的理论用气量 16
3.7.3 选择空压机 17
4 单片机控制设计 18
4.1 AT89C2051单片机简介 18
4.2 单片机的接线 19
5 无线遥控电路设计 20
5.1 TX2/RX-2遥控集成电路简介 20
5.1.1 TX-2／RX-2遥控集成电路的特点 20
5.1.2 TX-2／RX-2电参数引脚功能 20
5.1.3 TX-2／RX-2引脚功能 21
5.2遥控发射、接收电路 23
6 软件设计 25
参考文献 31
致谢 32
爬壁机器人气压传动系统及控制硬件设计
学生姓名：曾巧芸班级：050313
指导老师：袁坤
摘要：目前应用于实际的或文献报道的爬壁机器人的步行机构通常采用基于仿真原理的六足或四足等多足步行机构。本文根据具体要求采用了八足步进机构，设计了一种爬壁机器人的气压传动系统及控制硬件。本机器人的结构简单，由横纵两个垂直的机械结构组成，横向结构实现向左、向右的动作，纵向结构实现向上、向下的动作。该机器人机身采用有机玻璃制造，重量轻、易加工。系统是根据真空吸附原理设计的一个能在垂直墙面上通过脚步行进方式，在4个方向垂直移动的爬壁机器人及其控制系统。由气缸驱动机器人脚步的交替移动以实现在垂直表面的自由移动。控制系统采用单片机控制，通过接收无线遥控信号来实现上升、下降、向左、向右及停止五个基本动作的有序控制，为进一步实现复杂动作及实际应用打下了良好的基础。整个设计从机器人的本体结构开始，然后根据机器人的结构设计相应的气动回路，计算所需参数，选择气动气动系统的各执行元件、控制元件及辅件。再由机器人的动作原理选择单片机型，确定各引脚的接线。无线遥控系统选用了现在普遍使用的TX-2/RX-2，接收电路的引脚与单片机的引脚相连，接收电路接收发射电路发出的信号，通过单片机产生相应输出使机器人完成相应的动作。
关键词：爬壁机器人气压传动无线遥控单片机控制

Wall-climbing robot and control of air pressure drive system and hardware design
Student name: Zeng Qiaoyun Class:050313
Supervisor: Yun Kun
Abstract：Currently applies to actual or reported in the literature of the foot wall-climbing robot usually based on simulation Principle or the six-legged quadruped walking and other agencies. In this paper, according to the specific requirements of the use of stepping foot eight institutions, located Of a wall-climbing robot's pneumatic drive system and control hardware. The robot has Simple structure,the horizontal and vertical components of the mechanical structure, horizontal structure to the left, right action, vertical structure upward and downward movements. The robot used plexiglass manufacturing body, light weight, easy processing. The system is based on the principle of the design of the vacuum adsorption. It is a vertical wall in the road on the way through the steps in the direction of vertical movement 4 wall-climbing robot and its control system. Control system uses a single-chip control, wireless remote control signal through the receiver to achieve an increase, decrease, left, right and stop of the five basic moves in an orderly control. It can further the realization of the complexity of action and is a time when the application has laid a good foundation.The whole design of the body structure from the beginning of the robot, and then in accordance with the structural design of the robot corresponding pneumatic circuit to calculate the required parameters, select pneumatic pneumatic system of the implementation of components, control components and accessories. Robot moves from the principle of choice-based single-chip, to establish the connection pin.Optional wireless remote control system is now widely used TX-2/RX-2, the receiving circuit and MCU pin connected to the pin, receiving circuit to receive signals from transmitter, through the single-chip output to enable the robot to produce complete the corresponding action.

Keywords: wall-climbing robot pneumatic transmission wireless remote control single-chip control
Signature of supervise:

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内容简介：: 毕业设计（论文）任务书I、毕业设计(论文)题目：爬墙机器人气压传动系统及控制硬件设计II、毕业设计(论文)使用的原始资料(数据)及设计技术要求：原始资料：爬墙机器人文献20余篇设计技术要求：机器人爬行速度：02m/min( 无级可调)控制方式：无线遥控或程序控制吸附方式：负压吸附（正常负压为600mmH2O）；最大有效负载：15Kg；要求方案论证充分以单片机为控制器核心III、毕业设计(论文)工作内容及完成时间：1、外文翻译(6000实词以上)； (1周) 2月23日 2月27日2、收集有关资料，写出开题报告； (3周) 3月2日 3月20日3、系统方案设计； (4 周) 3月23日 4月17日4、气压传动系统计算与设计； (3 周) 4月20日 5月8日5、控制系统硬件设计； (2周) 5月11日 5月22日6、撰写论文； (2周)5月25日 6月5日7、毕业设计审查、毕业答辩（2周）6月8日 6月19日、主要参考资料：1.章宏甲等.机械设计手册气压传动分册M.机械工业出版社，1994年8月2.谈土力，龚振邦，张海洪等.壁面自动清洗机器人研制J.高技术通报,2003,12(2): 83-873.高学山，徐殿国，王炎.新型壁面清洗机器人的研究与设计J.高技术通报,2004,13(4): 39444.赵兴飞，周忆，石崇辉.气动爬壁机器人设计与计算J.机床与液压,2003,32(3):61625.B.Bahr,Y.Li and M.Najafi.Design and suction cup analysis of a wall climbing robotJ.Computers Elect. Engng.2006,22(3):193-209 6.高明.微机应用系统设计M.北京航空航天大学出版社,2003年3月航空与机械工程学院机械设计制造及其自动化专业类 050313 班学生（签名）：曾巧芸日期：自 2009 年 2 月 23 日至 2009 年 6 月 19 日指导教师（签名）：袁坤助理指导教师(并指出所负责的部分)：系（室）主任（签名）：文档包括:说明书一份,32页,10500字左右.任务书一份.开题报告一份.翻译一份.图纸共6张:A0-装配图.dwgA1-气动回路.dwgA2-QGB主气缸.dwgA3-QGX副气缸.dwgA4-真空发生器.dwgA4-真空吸盘.dwg爬壁机器人气压传动系统及控制硬件设计学生姓名：曾巧芸班级：050313指导老师：袁坤摘要：目前应用于实际的或文献报道的爬壁机器人的步行机构通常采用基于仿真原理的六足或四足等多足步行机构。本文根据具体要求采用了八足步进机构，设计了一种爬壁机器人的气压传动系统及控制硬件。本机器人的结构简单，由横纵两个垂直的机械结构组成，横向结构实现向左、向右的动作，纵向结构实现向上、向下的动作。该机器人机身采用有机玻璃制造，重量轻、易加工。系统是根据真空吸附原理设计的一个能在垂直墙面上通过脚步行进方式，在4个方向垂直移动的爬壁机器人及其控制系统。由气缸驱动机器人脚步的交替移动以实现在垂直表面的自由移动。控制系统采用单片机控制，通过接收无线遥控信号来实现上升、下降、向左、向右及停止五个基本动作的有序控制，为进一步实现复杂动作及实际应用打下了良好的基础。整个设计从机器人的本体结构开始，然后根据机器人的结构设计相应的气动回路，计算所需参数，选择气动气动系统的各执行元件、控制元件及辅件。再由机器人的动作原理选择单片机型，确定各引脚的接线。无线遥控系统选用了现在普遍使用的TX-2/RX-2，接收电路的引脚与单片机的引脚相连，接收电路接收发射电路发出的信号，通过单片机产生相应输出使机器人完成相应的动作。关键词：爬壁机器人气压传动无线遥控单片机控制指导老师签名：Wall-climbing robot and control of air pressure drive system and hardware designStudent name: Zeng Qiaoyun Class:050313Supervisor: Yun KunAbstract：Currently applies to actual or reported in the literature of the foot wall-climbing robot usually based on simulation Principle or the six-legged quadruped walking and other agencies. In this paper, according to the specific requirements of the use of stepping foot eight institutions, located Of a wall-climbing robots pneumatic drive system and control hardware. The robot has Simple structure,the horizontal and vertical components of the mechanical structure, horizontal structure to the left, right action, vertical structure upward and downward movements. The robot used plexiglass manufacturing body, light weight, easy processing. The system is based on the principle of the design of the vacuum adsorption. It is a vertical wall in the road on the way through the steps in the direction of vertical movement 4 wall-climbing robot and its control system. Control system uses a single-chip control, wireless remote control signal through the receiver to achieve an increase, decrease, left, right and stop of the five basic moves in an orderly control. It can further the realization of the complexity of action and is a time when the application has laid a good foundation.The whole design of the body structure from the beginning of the robot, and then in accordance with the structural design of the robot corresponding pneumatic circuit to calculate the required parameters, select pneumatic pneumatic system of the implementation of components, control components and accessories. Robot moves from the principle of choice-based single-chip, to establish the connection pin.Optional wireless remote control system is now widely used TX-2/RX-2, the receiving circuit and MCU pin connected to the pin, receiving circuit to receive signals from transmitter, through the single-chip output to enable the robot to produce complete the corresponding action.Keywords: wall-climbing robot pneumatic transmission wireless remote control single-chip controlSignature of supervise:目录1 绪论1 1.1引言1 1.2国外爬壁机器人研究现状1 1.3国内爬壁机器人研究现状2 1.4爬壁机器人的发展趋势3 1.5课题的目的及意义3 1.6课题内容及工作思路42 机器人的结构设计5 2.1 机构设计5 2.2 动作原理63 爬壁机器人的气压传动系统设计7 3.1 气压控制回路设计7 3.2 选择执行元件8 3.3 真空发生器、过滤器、吸盘的选择8 3.4选择控制元件9 3.4.1选择类型9 3.4.2选择主控阀9 3.4.3 选择减压阀9 3.5选择气动辅件10 3.6 确定管道直径、验算压力损失10 3.6.1 确定管径10 3.6.2 验算压力损失11 3.7 选择空压机16 3.7.1 自由空气量的计算16 3.7.2 气缸的理论用气量16 3.7.3 选择空压机174 单片机控制设计18 4.1 AT89C2051单片机简介18 4.2 单片机的接线195 无线遥控电路设计20 5.1 TX2/RX-2遥控集成电路简介20 5.1.1 TX-2RX-2遥控集成电路的特点20 5.1.2 TX-2RX-2电参数引脚功能20 5.1.3 TX-2RX-2引脚功能21 5.2遥控发射、接收电路236 软件设计25参考文献31致谢32IIClimbing Robots in Natural TerrainTimothy Bretl, Teresa Miller, and Stephen RockJean- Claude LatombeAerospace Robotics LabRobotics LaboratoryDepartment of Aeronautics and AstronauticsComputer Science DepartmentStanford University, Stanford, CA 94305Stanford University, Stanford, CA 94305tbretl, tgmiller, rocksun- latombeKeywordsMotion planning, climbing, robotics,legged robots, high- risk access, natural terrain.AbstractThis paper presents a general framework for plan-ning the quasi- static motion of climbing robots. Theframework is instantiated to compute climbing motionsof a three- limbed robot in vertical natural terrain. Anexample resulting path through a large simulatedenvironment is presented. The planning problem is oneof five fundamental challenges to the development ofreal robotic systems able to climb real natural terrain.Each of the four other areashardware design,control, sensing, and graspingis also discussed.1 IntroductionThe work described in this paper is part of an effortto develop critical technologies that will enable thedesign and implementation of an autonomous robotable to climb vertical natural terrain. To our knowl-edge, this capability has not been demonstratedpreviously for robotic systems. Prior approaches havedealt with artificial terrain, either using special“grasps” (e.g., pegs, magnets) adapted to the terrainssurface or exploiting specific properties or features ofthe terrain (e.g., ducts and pipes) 1- 12.Developing this capability will further our under-standing of how humans perform such complex tasksas climbing and scrambling in rugged terrain. Thismay prove useful in the future development ofsophisticated robotic systems that will either aid orreplace humans in the performance of aggressive tasksin difficult terrain. Examples include robotic systemsfor such military and civilian uses as search- and-rescue, reconnaissance, and planetary exploration.Many issues need to be addressed before real robotscan climb real, vertical, natural terrain. This paperconsiders five of the most fundamental of these issues:hardware design, control, sensing, planning, andgrasping. One of these issues in particular, the motion-planning problem, is described in more detail. Ageneral framework for climbing robots is presentedand this framework is instantiated to compute climbingmotions of the three- limbed robot shown in Figure 1.Simulation results are shown for the robot in anexample vertical environment.2 MotivationThe results of research in this area will benefit anumber of applications and have implications forseveral related research areas.2.1ApplicationsThis paper is motivated by a need for robotic sys-tems capable of providing remote access to high- risknatural environments.There are many terrestrial applications for thesesystems, such as search- and- rescue, cave exploration,human assistance for rock and mountain climbing, andtactical urban missions. Each of these applicationsrequires climbing, descending, or traversing steepslopes and broken terrain, and thus involves consider-able human risk.Several space applications could also benefit fromthese aggressive robotic systems. For example, sites onMars with potentially high science value have beenidentified on cliff faces 13. Often, it is neitherpractical nor feasible for flying robots to access theseFig 1. A three- limbed climbing robot moving vertically on naturalsurfaces.locations. Therefore, to reach these sites, robots mustclimb, descend, or traverse steep slopes. Future goalsfor exploration on other planetary bodies may requireaccess to equally rugged terrain.2.2ImplicationsIn addition to furthering the development of aclimbing robot for vertical natural terrain, the results ofresearch in this area could provide fundamental insightinto several related research areas. For example, thisstudy could lead to the development of better strategiesfor robotic walking or dexterous manipulation. Humanclimbers often comment on an increase in balance andan expanded range of movement in everyday activityas they become more proficient at the sport. Thisenhanced mobility is often referred to as “discoveringnew degrees of freedom,” and is related to the idea ofdiscovering useful new modes of mobility for ex-tremely complicated humanoid robots or digital actors.Also, the development of planning algorithms forclimbing robots could lead to a better set of criteria forthe design of these types of robots. These algorithmscould be applied to candidate designs in simulation todetermine the capabilities of the resulting robots, andthus to select a design.3 Fundamental IssuesThere are five fundamental issues involved inclimbing steep natural terrain: hardware design,control, sensing, grasping, and planning. A substantialamount of work needs to be done in each of these areasin order to develop a real climbing robot. This sectiondescribes the challenges involved in the first four ofthese areas; the planning problem will be discussed inmore detail in Section 4.3.1Hardware DesignA good hardware design can increase the perform-ance of the robot, and often can make each of the otherfundamental issues easier to deal with. However, pastuse of hardware solutions in maintaining equilibriumgenerally resulted in a fundamental limitation on theterrain that could be traversed.Wheeled robotic systems have been used to ascendand traverse natural slopes of up to 50 degrees, todescend slopes of up to 75 degrees, and to climb oversmall obstacles in rough terrain. These systems eitheruse some form of active or rocker- bogie suspension asin 12, 14- 16, or use rappelling as in 1. Similarresults have been obtained using legged rappellingrobots 3, 17 and a snake- like robot 4.The terrain that these rovers can traverse robustly isimpressive, but none of the existing systems has beenshown to be capable of climbing natural slopes of 90degrees or higher. Wheeled rovers and snake- likerobots have an inherent grasping limitation thatprevents their use in ascending sustained near- verticalor descending sustained past- vertical natural slopes.Existing legged robotic systems do not have thislimitation, but still have bypassed the issue of main-taining contact with the slope by using rappel tethers.Reliance on these tethers prohibits initial cliff ascent,and limits the slope grade on cliff descent to below 90degrees.A wide variety of robots capable of climbing verticalartificial surfaces is available. Most of these robotsexploit some property of the surface for easy grasping.For example, some of these robots use suction cups orpermanent magnets to avoid slipping 5- 8. Others takeadvantage of features such as balcony handrails 9 orpoles 10. However, the surface properties that areexploited by these robots generally are not available innatural terrain.In contrast, the simpler hardware designs used by 2,11 had no such limitations. It is expected thatsolutions to the planning problem such as the onepresented in this paper will allow basic natural verticalterrain to be climbed by similar systems, in addition tothe ducts and pipes climbed by existing systems, andwill suggest design modifications for better perform-ance.Future studies could address the use of other types oftools for grasping vertical natural surfaces, such astools for drilling bolts or placing other types of gear inrock. The use of these tools would allow morechallenging climbs to be accomplished, in the sameway that “aid” helps human climbers 18, 19.However, these tools bring an increase in weight andcomplexity, slowing movement and limiting potentialapplications.3.2ControlThere are three primary components of the controlproblem for a climbing robot: maintenance of equilib-rium, endpoint slip control, and endpoint force control.These three components are tightly related. In order tomaintain balance, both the location of the center ofmass of the robot and the forces from contacts withnatural features must be controlled. Control of slip atthese contacts is directly related to the direction andmagnitude of the contact forces.Existing control techniques such as those based onthe operational space formulation 20 could form abaseline approach to the design of a control architec-ture for a climbing robot. However, these techniquescould be extended in a number of different ways toachieve better performance. For example, futureresearch might address the design of an endpoint slipcontroller that is stable with respect to the curvature ofa contact surface, rather than with respect to a pointcontact only.3.3SensingFor control and grasping, the robot must be capableof sensing the orientation of its body with respect tothe gravity vector, the location of its center of mass,the relative location of contact surfaces from its limbendpoints, and the forces that it is exerting at contactswith natural features. For planning, the robot mustadditionally be able to locate new holds and generate adescription of their properties, possibly requiring ameasurement of levels of slip at contact points. Sensorintegration, in order to acquire and use this informationwith algorithms for control, grasping, and planning, isa challenging problem.Existing engineering solutions are available whichcan lead to the development of a baseline approach ineach case. For example, sensors such as those de-scribed in 21, 22 can provide basic endpoint forceand slip measurements, an inertial unit and magneticcompass can provide position information, an on- boardvision system can provide a rough characterization ofhold locations and properties, and encoders canprovide the location of the center of mass. However,the improvement of each of these sensorsin terms ofperformance, mass reduction, or cost reduc-tionpresents an open area for research.Although the performance of the planning frame-work that will be presented in Section 4 would beimproved with better sensor information, it does notdepend on a perfect model of the environment a priori.Since the framework leads to fast, online implementa-tion, plans can be updated to incorporate new sensorinformation as it becomes available.3.4GraspingThe performance of a climbing robot is dependenton its ability to grasp “holds,” or features on a steepnatural surface. It has already been noted that special-ized grasping schemes, relying on specific propertiesof the surface such as very smooth textures, pegs, orhandles, cannot be used for grasping arbitrary naturalfeatures. The problems involved in grasping naturalholds will be examined further in this section.Traditionally grasp research has been interested ineither picking up an object or holding it immobile (alsocalled “fixturing.”) Research in this subject dates as farback as 1876 it was shown that a planar object couldbe immobilized using a minimum of four frictionlesspoint constraints 23. Good overviews of more recentwork can be found in 24, 25. In this field an impor-tant concept is “force- closure,” defined as a grasp that“can resist all object motions provided that the end-effector can apply sufficiently large forces at theunilateral contacts.” 25 Nearly all research on graspshas focused on selecting, characterizing, and optimiz-ing grasps that have the property of force- closure.However, for the task of climbing a grasp need notachieve force- closure to be a useful grasp. Forexample, a robot may find a shelf- like hold veryeffective for pulling itself up, even though this graspwould be completely unable to resist forces exerted inother directions. For this reason, the techniques forselecting, characterizing, and optimizing grasps mustbe expanded significantly to apply to climbing robots.Characterization involves examining the directionand magnitudes of forces and torques (also calledwrenches) that can be exerted by the grasp. Forexample, for one- finger grasps on point holds, anadequate representation of this information is a frictioncone, which will be used for the planning algorithmdescribed in Section 4.The idea of characterization also encompasses a“quality factor.” Measures of grasp quality have beenresearched extensively and are well reviewed in 26.This work lists eight dexterity measures that includeminimization of joint angle deviations and maximiza-tion of the smallest singular value of the grasp matrix.Other relevant research has been done using theconcept of the wrench space. Using this concept,quality is defined as the largest wrench space ball thatcan fit within the unit grasp wrench space 27. Thevolume of the grasp wrench space, or of morespecialized task ellipsoids, could be used as a qualitymeasure 28. These ideas have been expanded toinclude limiting maximum contact force and applied ina grasp simulator to compute optimal grasps withvarious hands in 3D 29, 30.However, the concept of grasp quality is ill definedfor grasps that do not provide force- closure. Depend-ing on the direction that a climber wishes to go,different grasps may be of higher quality. Furthermore,grasp quality generally includes a concept of securityor stability, and this too is ill defined for non- force-(a)(b)(c)(d)Fig. 2. Four different human climbing grasps, the (a) open grip, (b)crimp, (c) finger- lock, and (d) hand jam.closure grasps. Again, depending on the direction ofapplied forces, the security of a grasp may change. Theconcept of hold quality must be defined before usefuloptimization is possible. Also, an efficient way oftransmitting this information to a controller or planneris necessary to accomplish the climbing task.A qualitative classification of different types ofgrasps already exists in the literature for humanclimbers 19, 31. In this classification, grasps are firstbroken into two categories, those meant for pockets,edges, and other imperfections on otherwise unbrokenvertical rock faces, and those meant for sustainedvertical cracks. Several examples of different face andcrack grasps are shown in Figure 2. The literaturegives a rough idea of the quality and use of each typeof grasp in terms of criteria such as a perceived levelof security, the amount of torque that can be exerted ona hold, and the amount of friction at the “power point.”Not only is this expert intuition qualitative, but alsoit is clear that human climbers need to performadditional grasp planning for specific cases. As put byLong, “There are as many different kinds of holds asthere are ways to grab them 31.” However, thisintuition can be used as a starting point for determiningmeaningful quantitative criteria for grasp selection andoptimization.A comparison of the climbing literature with pastwork on robotic grasp planning reveals several otherfundamental differences between the two applicationsthat may become important in future research. Forexample, many climbing holds are very small, so thefingers used in a climbing grasp often have largediameters relative to the object to be grasped. Litera-ture on robotic grasping primarily considers the casewhere the fingers have small diameters relative to theobject. In addition, some climbing grasps, as men-tioned above and shown in Figure 2, are based onjamming fingers in a crack. This technique is verydifferent from one a robot might use to pick up anobject, and requires a high degree of flexibility andsmall degrees- of- freedom in order to “un- jam” thefingers. Clearly, continued work on climbing robotseventually will lead to the consideration of a wealth ofnew issues in grasping.4 PlanningThe planning problem is the fifth fundamentalchallenge for climbing robots in natural terrain. Detailsof the motion- planning framework presented in thissection are given in 32.4.1ChallengesThe planning problem for a climbing robot consistsof generating a trajectory that moves the robot througha vertical environment while maintaining equilibrium.This problem is challenging even for human climb-ers! Climbing is described by Long as a “singular(a)(b)(c)Fig. 3. Three different human climbing “moves,” the (a) back- step,(b) stem, and (c) high- step.challenge, where each route up the rock is a mentaland physical problem- solving design whose sequenceand solution are unique. Every climb is different 31.”Much of the sequence for a particular route might becomposed of one of a variety of different types of“moves,” such as a back- step, stem, mantel, high- step,counterbalance, counterforce, lie- back, down- pressure,or under- cling. Some of these moves are shown inFigure 3. Each “move” is a learned technique formaintaining balance that may seem counterintuitive. Inaddition to these heuristics, movement through a largenumber of other very specific body positions might benecessary to progress towards the top of a climb.The importance of planning a sequence of movesbefore actually climbing is emphasized by Graydonand Hanson 19, who recommend that climbers“identify and examine difficult sections before theyget to them, make a plan, and then move through themquickly.” The human motivation for this approach isprimarily to minimize the effort required for eachmove and to conserve energy, since most people havehard strength and endurance limits.The planning problem for a climbing robot is quitesimilar. The robot likely will be equipped withactuators that can exert high torques only for shortamounts of time, so planning a sequence of movesbefore climbing is important for a robotic system aswell. Likewise, a climbing robot will be subject to thesame hard equilibrium constraints, and will need toselect between a similarly wide range of possiblemotions. Therefore, the development of a planningalgorithm for an autonomous climbing robot is a verychallenging problem.4.2Related WorkThe search space for a climbing robot is a hybridspace, involving both continuous and discrete actions.Many different methods are available for motionplanning through continuous spaces, including celldecomposition, potential field, and roadmap algo-rithms 33. Discrete actions can be included in thesemethods directly, for example at the level of nodeexpansion in roadmap algorithms, but this approachgenerally leads to a slow implementation that isspecific to a particular system.Previous work on motion planning for legged robotshas developed tools for addressing these hybrid searchspaces for some systems. This work can be categorizedby whether or not the planning is done offline, in orderto generate a reactive gait, or online, in order to allownon- gaited motion specific to a sensed environment.Gaited planners generate a predefined walkingpattern offline, assuming a fairly regular environment.This pattern is used with a set of heuristics or behav-iors to control the robot online based on current sensorinput. Gaited planning was used by 2, 11, forexample, to design patterns for climbing pipes andducts. Other methods such as 34 are based on thenotion of support triangles for maintaining equilib-rium. Stability criteria such as the zero- moment- pointhave been used to design optimal walking gaits 35.Dynamic gaiting and bounding also have beendemonstrated 36- 38. Recent work 39, 40 hasattempted to provide unifying mathematical tools forgait generation. Each of these planning algorithmswould be very effective in portions of a naturalclimbing environment with a sustained feature such asa long vertical crack of nearly uniform width. How-ever, something more is needed for irregular environ-ments such as the one studied in this paper, where thesurfaces on which the robot climbs are angled andplaced arbitrarily.Non- gaited planners use sensed information aboutthe environment to create feasible motion plans online.Most previous work on non- gaited motion planning forlegged robots has focused on a particular systemmodel, the spider robot. The limbs of a spider robot areassumed to be massless, which leads to elegantrepresentations of their free space for quasi- staticmotion based on support triangles 41- 43. Thesemethods have been extended to planning dynamicmotions over rough terrain 44, 45. The analysis usedin these methods breaks down, however, whenconsidering robots that do not satisfy the spider- robotassumption. For example, additional techniques werenecessary in 46, 47 to plan non- gaited walkingmotions for humanoids, which clearly do not satisfythis assumption. To address the high number ofdegrees of freedom and the high branching factor ofthe discrete search through possible footsteps, thesetechniques were based on heuristic discretization andsearch algorithms. This paper considers a robot withfewer degrees of freedom in a more structured searchspace where it is possible to achieve much betterperformance than with these heuristic methods. Similarissues were addressed by 48 in designing a motion-planning algorithm for character animation, althoughthis algorithm was meant to create “realistic,” ratherthan strictly feasible, motion.There is also some similarity between non- gaitedmotion planning for legged locomotion and forgrasping and robotic manipulation, particularly in theconcept of a manipulation graph 24, 49- 51. Bothtypes of planning require making discrete andcontinuous choices.None of these existing planning techniques is suffi-cient to address even the simplest version of theclimbing problem in natural vertical environments, inwhich quasi- static motion, perfect information, andone- finger grasps on point holds are assumed. Theproblem becomes even more complicated if the quasi-static and perfect information assumptions are relaxed,and if more complicated grasps are considered.4.3Planning FrameworkIn this section, we will describe our planningframework in the context of a specific climbing robot,shown in Figure 1. This robot consists of three limbs.Each limb has two joints, one located at the center ofthe robot (called the pelvis) and one at the midpoint ofthe limb. Motion is assumed to be quasi- static (as isusually the case in human climbing) and to occur in avertical plane, with gravity. The low complexity of thisrobots kinematics makes it suitable for studying theplanning of climbing motions.The terrain is modeled as a vertical plane to which isattached a collection of small, angled, flat surfaces,called “holds,” that are arbitrarily distributed. Theendpoint of each robot limb can push or pull at a singlepoint on each hold, exploiting friction to avoid sliding.A climbing motion of the robot consists of succes-sive steps. Between any two consecutive steps, allthree limb endpoints achieve contact with distinctholds. During each step, one limb moves from onehold to another, while the other two endpoints remainfixed. The robot can use the degrees of freedom in thelinkage formed by the corresponding two limbs tomaintain quasi- static equilibrium and to avoid slidingon either of the two supporting holds. In addition,during a step, the torque at any joint should not exceedthe actuator limits and the limbs should not collidewith one another. These constraints define the feasiblesubset of the configuration space of the robot in eachstep. A path in this subset defines a one- step motion.The overall planning problem is the following: givena model of the terrain, an initial robot configurationwhere it rests on a pair of holds, and a goal hold,generate a series of one- step motions that will allowthe robot to move in quasi- static equilibrium from theinitial configuration to an end configuration where onelimb endpoint is in contact with the goal hold.In 32 we presented the details of a framework toaddress this planning problem. This framework can besummarized as follows.First, we presented a detailed analysis of one- stepmotion for the three- limbed climbing robot. Theproperties of the continuous configurations at whichthe robot is in equilibrium were established, and wereused to define the feasible set of robot configurationsat each pair of holds. In particular, it was shown thatthe connectivity of the four- dimensional continuousfeasible space of the robot could be preserved whenplanning in a two- dimensional subspace. This resultreduced the complexity of the one- step planningproblem and led to a fast, online implementation.Then, the overall planner combined this “localplanner” with a heuristic search technique to determinea sequence of holds from the initial configuration tothe goal hold. The heuristic methods were based onobservation of the way in which human climbers plantheir motion.4.4ResultsOur work in 32 presented only one set of simula-tion results, for a particular vertical environment. Thispaper presents a second set of results, for a morechallenging environment. This environment, as shownin Figure 4, contains 50 arbitrarily placed and angledholds. The robot is initially located on the two holds atthe bottom of the environment, and is required to reachthe top two holds.A plan was found in 3.0 seconds using a 450 MHzPowerPC processor, which is typical for an environ-ment containing 50 holds. Planning times for smallerenvironments are on the order of 0.1 seconds.A representative continuous configuration from eachone- step motion in the planned sequence is shown inFigure 5. Many of these configurations are remarkablysimilar to human configurations. For example, theconfiguration shown in Figure 5(a) is similar to the“stem” shown in Figure 3(b). Likewise, Figures 5(i)and 5(n) depict configurations similar to the “back-step” of Figure 3(a) and the “high- step” of Figure 3(c),respectively.Each frame of Figure 5 also shows the equilibriumregion for the current pair of holds on which the robotis standing. This is the region over which the center ofmass of the robot can move while remaining in quasi-static equilibrium without slipping, and is a completespecification of the equilibrium constraint on the robot.Notice that in each configuration shown, the center ofmass of the robot lies within the equilibrium region, asexpected.More results, including animated 3D- visualizations,are available online at /tbretl/.5 ConclusionThis paper described the challenges to developing anautonomous climbing robot and presented a frameworkfor addressing the planning problem.Fig. 4. An example vertical environment for the three- limbedclimbing robot.Current work deals with the application of theplanning framework to a real robotic system, using realhardware. As part of this effort, the framework is beingextended to handle additional motion constraints, morecomplicated robot geometries, imperfectly knownenvironments, and three- dimensional terrain.Future work will address the other four fundamentalissueshardware design, control, sensing, andgraspingand their relationship to the planningproblem.AcknowledgementsT. Bretl is partially supported by anNDSEG fellowship through ASEE and by a Herbert KunzelFellowship. The authors would also like to thank D. Halperin for hishelpful comments.References1 P. Pirjanian, C. Leger, E. Mumm, B. Kennedy, M. Garrett, H.Aghazarian, S. Farritor, and P. Schenker, Distributed Controlfor a Modular, Reconfigurable Cliff Robot, IEEE Int. Conf. onRobotics and Automation, 2002.2 A. Madhani and S. Dubowsky, Motion Planning of MobileMulti- Limb Robotic Systems Subject to Force and FrictionConstraints, IEEE Int. Conf. on Robotics and Automation,1992.3 S. Hirose, K. Yoneda, and H. Tsukagoshi, Titan Vii:Quadruped Walking and Manipulating Robot on a Steep Slope,IEEE Int. Conf. on Robotics and Automation, 1997.4 M. Nilsson, Snake Robot - Free Climbing, in IEEE ControlSystems Magazine, vol. 18, Feb 1998, pp. 21- 26.(a)(b)(c)(d)(e)(f)(g)(h)(i)(j)(k)(l)(m)(n)(o)(p)(q)(r)(s)(t)Fig. 5. Representative steps of the robots motion for the example environment shown in Figure 4. The dark circle in each frame is the center ofmass of the robot. The shaded column is the region over which the center of mass can move while the robot remains in equilibrium.5 J. C. Grieco, M. Prieto, M. Armada, and P. G. d. Santos, ASix- Legged Climbing Robot for High Payloads, IEEE Int.Conf. on Control Applications, 1998.6 H. Dulimarta and R. L. Tummala, Design and Control ofMiniature Climbing Robots with Nonholonomic Constraints,4th World Congress on Intelligent Control and Automation, Jun2002.7 S. W. Ryu, J. J. Park, S. M. Ryew, and H. R. Choi, Self-Contained Wall- Climbing Robot with Closed Link Mecha-nism, IEEE/RSJ Int. Conf. on Intelligent Robots and Systems,2001.8 W. Yan, L. Shuliang, X. Dianguo, Z. Yanzheng, S. Hao, and G.Xuesban, Development & Application of Wall- ClimbingRobots, IEEE Int. Conf. on Robotics and Automation, 1999.9 H. Amano, K. Osuka, and T.- J. Tarn, Development ofVertically Moving Robot with Gripping Handrails for FireFighting, IEEE/RSJ Int. Conf. on Intelligent Robots and Sys-tems, 2001.10 Z. M. Ripin, T. B. Soon, A. B. Abdullah, and Z. Samad,Development of a Low- Cost Modular Pole Climbing Robot,TENCON, 2000.11 W. Neubauer, A Spider- Like Robot That Climbs Vertically inDucts or Pipes, IEEE/RSJ/GI Int. Conf. on Intelligent Robotsand Systems, 1994.12 K. Iagnemma, A. Rzepniewski, S. Dubowsky, P. Pirjanian, T.Huntsberger, and P. Schenker, Mobile Robot Kinematic Re-configurability for Rough- Terrain, Sensor Fusion and Decen-tralized Control in Robotic Systems III, 2000.13 E. Baumgartner, In- Situ Exploration of Mars Using RoverSystems, AIAA Space 2000, 2000.14 R. Simmons, E. Krotkov, L. Chrisman, F. Cozman, R.Goodwin, M. Hebert, L. Katragadda, S. Koenig, G. Krishnas-wamy, Y. Shinoda, W. R. L. Whittager, and P. Klarer, Experi-ence with Rover Navigation for Lunar- Like Terrains, Intelli-gent Robots and Systems, 1995.15 K. Iagnemma, F. Genot, and S. Dubowsky, Rapid Physics-Based Rough- Terrain Rover Planning with Sensor and ControlUncertainty, IEEE Int. Conf. on Robotics and Automation,1999.16 T. Estier, Y. Crausaz, B. Merminod, M. Lauria, R. Pguet, and R.Siegwart, An Innovative Space Rover with Extended ClimbingAbilities, Space and Robotics, 2000.17 J. E. Bares and D. S. Wettergreen, Dante Ii: TechnicalDescription, Results and Lessons Learned, Int. J. of RoboticsResearch, vol. 18, pp. 621- 649, 1999.18 J. Long and J. Middendorf, Big Walls: Chockstone Press, Feb1997.19 D. Graydon and K. Hanson, Mountaineering: The Freedom ofthe Hills, 6th Rev edition ed: Mountaineers Books, Oct 1997.20 O. Khatib, A Unified Approach for Motion and Force Controlof Robot Manipulators: The Operational Space Formulation,IEEE J. of Robotics and Automation, vol. RA- 3, 1987.21 R. Howe, N. Popp, P. Akella, I. Kao, and M. Cutkosky,Grasping, Manipulation and Control with Tactile Sensing,IEEE Int. Conf. on Robotics and Automation, 1990.22 D. Johnston, P. Zhang, J. Hollerbach, and S. Jacobsen, A FullTactile Sensing Suite for Dextrous Robot Hands and Use inContact Force Control, IEEE Int. Conf. on Robotics andAutomation, 1996.23 F. Reuleaux, The Kinematics of Machinery: Outlines of aTheory of Machines. London: Macmillan, 1876.24 A. Bicchi and V. Kumar, Robotic Grasping and Contact: AReview, IEEE Int. Conf. on Robotics and Automation, 2000.25 A. Miller, Graspit!: A Versatile Simulator for RoboticGrasping, Columbia University, Jun 2001.26 K. Shimoga, Robot Grasp Synthesis Algorithms: A Survey,Int. 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