液压机械手的设计【五自由度】
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摘摘 要要液压机械手是模仿人的手部动作，按照给定的程序、轨迹通过液压系统实现抓取和搬运操作的自动装置。本次设计的液压传动机械手根据规定的动作顺序，综合运用所学的基本理论、基本知识和相关的机械设计专业知识，完成对机械手的设计，并绘制必要装配图、液压系统图、 。机械手的机械结构采用油缸、螺杆、导向筒等机械器件组成；在液压传动机构中，机械手的手臂伸缩采用伸缩油缸，手腕回转采用回转油缸，立柱的转动采用齿条油缸，机械手的升降采用升降油缸，立柱的横移采用横向移动油缸；通过控制电磁阀的开关来控制机械手进行相应的动作循环，当按下连续停止按钮后，机械手在完成一个动作循环后停止运动。 本设计拟开发的上料机械手可在空间抓放物体，动作灵活多样，可代替人工在高温和危险的作业区进行作业，可抓取重量较大的工件。可以改善劳动条件，避免人身事故。可以减少人力，并便于有节奏的生产。关键词： 机械手；液压；控制回路IIAbstractHydraulic robot mimic is the hand movements which in accordance with a given program, the path through the hydraulic system to achieve automatic device to capture and handling operations.The design of hydraulic drive manipulator movements under the provisions of the order ， use the basic theory, basic knowledge and related mechanical design expertise comprehensively to complete the design，and drawing the necessary assembly, hydraulic system map, PLC control system diagram . Manipulator mechanical structure using tanks, screw ,guide tubes and other mechanical device component ；In the hydraulic drive bodies ，manipulator arm stretching using telescopic tank ，rotating column of tanks used rack ，manipulator movements using tank movements ，the column takes the horizontal movement of tanks ； through the control of the solenoid valve to control the switch manipulator corresponding moves cycle ，after press the row stop button , the manipulator complete a cycle of action to stop after the hole campaign.The design of the proposed development of the information on the manipulator can grasp up in space objects ，flexible and varied movements ，can replace the artificial heat and dangerous operation conducted operations，and can grasp the larger work pieces . Can improve working conditions, avoid personal accident. Can reduce manpower, and to facilitate the there are-paced the production of.Keywords： Manipulator ；Hydraulic；Control Loop 目目 录录摘 要.IIIABSTRACT.IV目 录 .V1 绪论.11.1 机械手的基本概念的研究内容和意义.11.1.1 机械手的基本概念.11.1.2 机械手的研究意义.11.2 机械手的发展现状及应用.11.2.1 世界机器人发展状况.11.2.2 我国工业机器人的发展.21.3 本课题达到的要求.22 液压机械手主要结构的机械设计.42.1 臂力的确定.42.2 确定工作范围.42.3 确定运动速度.42.4 手臂的配置形式.42.5 位置检测装置的选择.52.6 驱动与控制方式的选择.52.7 本章小结.53 手部结构.73.1 概述.73.2 设计时应考虑的几个问题.73.3 驱动力的计算.83.4 两支点回转式钳爪的定位误差的分析.93.5 本章小结.94 腕部的结构.114.1 概述.114.2 腕部的结构形式.114.3 手腕驱动力矩的计算.114.4 本章小结.135 臂部的结构.145.1 臂部概述.145.2 手臂直线运动机构.145.2.1 手臂伸缩运动.145.2.2 导向装置.155.2.3 手臂的升降运动.165.3 手臂回转运动.17I5.4 手臂的横向移动.175.5 臂部运动驱动力计算.175.5.1 臂水平伸缩运动驱动力的计算.175.5.2 臂垂直升降运动驱动力的计算.185.5.3 臂部回转运动驱动力矩的计算.186 液压系统的设计.206.1 液压系统简介.206.2 液压系统的组成.206.3 机械手液压系统的控制回路.206.3.1 压力控制回路.206.3.2 速度控制回路.216.3.3 方向控制回路.216.4 机械手的液压传动系统.216.4.1 上料机械手的动作顺序.216.4.2 自动上料机械手液压系统原理介绍.226.5 机械手液压系统的简单计算.246.6 双作用单杆活塞油缸.246.7 无杆活塞油缸（亦称齿条活塞油缸）.276.7.3 单叶片回转油缸.276.7.4 油泵的选择.286.7.5 确定油泵电动机功率 N .297 结 论.30致 谢.31附 录.33 21 绪论绪论1.1 机械手的基本概念机械手的基本概念的研究内容和意义的研究内容和意义1.1.1 机械手的基本概念机械手的基本概念液压机械手，从本质上来说是属于工业机器人的范围的，机器人问题是最近几十年的热门研究课题。它包括了机械工程、计算机科学、电子工程和自动控制以及人工智能等多种学科，体现了机电一体化技术的最新成就，是当代科学技术发展最活跃的范围之一，也是我国科技界跟踪国际高技术发展的重要课题。“机械手” （Machanical Hand）：大部分是指附属于主机、程序固定的自动抓取、操作装置（我国一般称作机械手或专用机械手） 。比如自动生产线、自动机的上下给料系统，加工中心自动化装置1。1.1.2 机械手的研究意义机械手的研究意义1.可以提高生产过程的自动化程度。应用机械手有利于在自动生产线中实现材料的传送、工件的装卸、刀具的更换、以及机器的装配等的自动化程度，从而提高劳动生产率，降低生产成本。2.可以改善劳动条件，避免人身事故。3.可以减少人力，并便于有节奏的生产。 4.用液压系统来控制机械手，比一般的机械控制具有更好的稳定性，并且控制的精确度更高。5.运用机械手可以实现连续的生产，而大大提高在生产线的工作的时间，从而能大幅提高劳动的生产率。 1.2 机械手的发展现状及应用机械手的发展现状及应用机械手的迅速发展是因为它的积极作用正逐渐被人们所认可；第一，它能部分代替体力人工操作；第二，它可以按照生产工艺的要求，按照一定的程序，时间和位置来完成工作的传送和装卸；第三，它能操作必要的器具进行焊接和装配。从而改善人们的劳动条件，显著的提高劳动生产率，加快实现工业生产机械化和自动化的步伐。因此，各先进工业国家都对此十分重视，投入大量的人力物力进行研究和应用。尤其在高温、高压、粉压、噪音以及带有放射性的污染的场合应用得更为广泛。在我国，近几年来也有较快的发展，并取得一定的效果，受到机械工业和铁路工业部门的重视2。1.2.1 世界机器人发展状况世界机器人发展状况国外机器人领域发展近几年有如下几个趋势：（1）. 工业机器人性能不断提高（高速度、高精度、高可靠性、便于操作和维修） ，而单机价格不断下降。（2） 机械结构向模块化、可重构化发展。例如关节模块中的伺服电机、减速机、检测系统三位一体化；由关节模块、连杆模块用重组方式构造机器人整机；国外已有模块化装配机器人产品问市。（3） 工业机器人控制系统向基于 PC 机的开放型控制器方向发展，便于标准化、网络化；大大提高了系统的可靠性、易操作性和可维修性。（4） 机器人中的传感器作用日益重要，除采用传统的位置、速度、加速度等传感3器外，装配、焊接机器人还应用了视觉、力觉等传感器，多传感器融合配置技术在产品化系统中已有成熟应用。（5） 虚拟现实技术在机器人中的作用已从仿真、预演发展到用于过程控制。（6） 当代遥控机器人系统的发展特点不是追求全自治系统，而是致力于操作者与机器人的人机交互控制，使智能机器人走出实验室进入实用化阶段。(7)机器人化机械开始兴起。从 94 年美国开发出“虚拟轴机床”以来，这种新型装置已成为国际研究的热点之一，纷纷探索开拓其实际应用的领域3。1.2.2 我国工业机器人的发展我国工业机器人的发展有人认为，应用机器人只是为了节省劳动力，而我国劳动力资源丰富，发展机器人不一定符合我国国情。这是一种误解。在我国，社会主义制度的优越性决定了机器人能够充分发挥其长处。它不仅能为我国的经济建设带来高度的生产力和巨大的经济效益，而且将为我国的宇宙开发、海洋开发、核能利用等新兴领域的发展做出卓越的贡献。我国的工业机器人从 80 年代“七五”科技攻关开始起步，在国家的支持下，通过“七五”、 “八五”科技攻关，目前已基本掌握了机器人操作机的设计制造技术、控制系统硬件和软件设计技术、运动学和轨迹规划技术，生产了部分机器人关键元器件，开发出喷漆、弧焊、点焊、装配、搬运等机器人；其中有 130 多台套喷漆机器人在二十余家企业的近30 条自动喷漆生产线（站）上获得规模应用，弧焊机器人已应用在汽车制造厂的焊装线上。但总的来看，我国的工业机器人技术及其工程应用的水平和国外比还有一定的距离，如：可靠性低于国外产品；机器人应用工程起步较晚，应用领域窄，生产线系统技术与国外比有差距；在应用规模上，我国已安装的国产工业机器
COMBINATION OF ROBOT CONTROL AND ASSEMBLY PLANNING FOR A PRECISION MANIPULATOOR
Abstract
This paper researches how to realize the automatic assembly operation on a two-finger precision manipulator. A multi-layer assembly support system is proposed. At the task-planning layer, based on the computer-aided design (CAD) model, the assembly sequence is first generated, and the information necessary for skill decomposition is also derived. Then, the assembly sequence is decomposed into robot skills at the skill-decomposition layer. These generated skills are managed and executed at the robot control layer. Experimental resulte show the feasibility and efficiency of the proposed system.
Keywords ：Manipulator Assembly planning Skill decomposition Automated assembly
1Introduction
Owing to the micro-electro-mechanical systems (MEMS) techniques, many products are becoming very small and complex, such as microphones, micro-optical components, and microfluidic biomedical devices, which creates increasing needs for technologies and systems for the automated assembly have been focused on microassembly technologies. However, microassembly techniques of high flexibility, efficiency, and reliability skill open to further research. This paper researches to how to realize the automatic assembly operation on a two-finger micromanipulator. A muli-layer assembly support system is proposed.
Automatic assembly is a complex problem which may involve many different issues, such as task planning, assembly sequences generation, execution, and control, etc. It can be simply divided into two phases, the assembly planning and the robot control. At the assembly-planning phase, the information necessary for assembly operation, such as the assembly sequence, is generated. At the robot control phase, the robot is driven based on the information generated at the assembly-planning phase, and the assembly operations are conducted. Skill primitives can work as the interface of assembly planning to robot control. Several robot systems based on skill primitives have been reported. The basic idea behind these systems is the robot programming. .Robot movements are specified as skill primitives, based on which the assembly task is manually coded into programs. With the programs, the robot is control to assembly tasks automatically.
A skill-based micromanipulation system has been developed in the authors’ lab, and it can realize many micromanipulation operations. In the system, the assembly task is manually discomposed into skill sequences and complied into a file. After importing the file into the system, the system can automatically execute the assembly task. This paper attempts to explore a user-friendly, and at the same time easy, sequence-generation method, to relieve the burden of manually programming the skill sequence.
It is an effective method to determine the assembly sequence from geometric computer-aided design (CAD) models. Many approaches have been proposed. This paper applies a simple approach to generate the assembly sequence. It is not involved with the low-level data structure of the CAD model, and can be realized with the application programming interface (API) functions graph among different components is first constructed by analyzing the assembly model, and then, possible sequences are searched, based on the graph. According to certain criterion, the optimal sequence is finally obtained.
To decompose the assembly sequence into robot skill sequences, some works have been reported. In Nnaji et al.’work, the assembly task commands are expanded to more detailed commands, which can be as robot skills, according to a predefined format. The decomposition approach of Mosemann and wahl is based on the analysis of hyperarcs of AND/OR graphs representing the automatically generated assembly plans. This paper proposes a method to guide the skill decomposition .The assembly processes of parts are grouped into different start atate and target of the workflow, the skill generator creates a series of skills that can promote the part to its target state.
The hierarchy of the system proposed here, the assembly information on how to assemble a product is transferred to the robot through multiple layers. Te top layer is for the assembly-task planning. The information needed for the task planning and skill generation are extracted from the CAD model and are saved in the database. Base on the CAD model, the assembly task squences are generated. At the skill-decomposition layer, tasks are decomposed into skill sequences. The generated skills are managed and executed at the robot control layer.
2 Task planning
Skills are not used directly at the assembly-planning phase, the concept of a task is used. A task can fulfill a series of assembly operations, for example, from locating a part, through moving the part, to fixing it with another part. In other words, one task includes many functions that may be fulfilled by several different skills. A task is defined as:
T = (Base Part; Assembly Part; Operation)
Based-part and Assembly-Part are two parts that are assembled together. Base-part is fixed on the worktable, while Assembly-Part is handled by robot’s end- effector and assembled onto the Base-Part. Operation describes how the Assembly-Part is assembled with the Base-Part; Operation={Intertion-T,serew-T,align-T,…}.
The structure of microparts is usually uncomplicated, and they can be modeled by the constructive solid geometry (CAG) method. Currently, many commercial CAD software packages can support 3D CSG modeling. The assembly model is represented as an object that consists of two parts with certain assembly relations that define how the parts are to be assembled. In the CAD model, the relations are defined by geometric constraints. The geometric information cannot be used directly to guide the assembly operation-we have to derive the information necessary for assembly operations from the CAD model.
Through searching the assembly tree and geometric relations (mates’ relations) defined in the assembly’s CAD model, we can generate a relation graph among parts, for example, In the graph, the nodes represent the parts. If nodes are connected, it means that there are assembly relations among these connected nodes (parts).
2.1 Mating direction
In CSG, the relations of two parts, geometric constraints, are finally represented as relations between planes and lines, such as collinear, coplanar, tangential, perpendicular, etc. For example, a shaft is assembled in a hole. The assembly relations between the two parts may consist of such two constraints as collinear between the centerline of shaft Lc-shaft and the centerline of hole Lc-hole and coplanar between the P-Shaft and the plane P-Hole. The mating direction is a key issue, for an assembly operation. This paper applies the following approach to compute the possible mating direction based on the geometric constraints (the shaft-in-hole operation of Fig. 3 is taken as an example):
For a part in the relation graph, calculate its remaining degrees of freedom, also called degrees of separation, of each geometric constraint.
For the conplanar constraint, the remaining degrees of freedom are R1= {x,y,Rotz }. For the collinear constraint, the remaining degrees of freedom are R2= {z,Rotz}. R1 and R2 can also be represented as R1= {1,1,0,0,0,1} and R2{0,0,1,0,0,1}. Here, 1 means that there is a degree of separation between the two parts. R1R2= {0,0,0,0,1},and so, the degree of freedom around the z axis will be ignored in the following steps.
In the ease that there is loop in the relation graph, such as parts Part5,Part6, and Part 7 in Fig. 2,the loop has to be broken before the mating direction is calculated. Under the assumption that all parts in the CAD model are fully constrained and not over-constrained, the following simple approach is adopted. For the part t in the loop, calculate the number of is in Nin=Ri1Ri2...Rin; where R is the remaining degrees of freedom of constraint k by part i. For example, in Fig. 2, given that the number of 1s in U is larger than U, then it can be regarded that the position of part 7 is determined by constraints between part 5 and part 6,while Part5 and Part6 can be fully constrained by constraints between Part 5 and Part 6. we can unite Part 5 and Part 6 as one node will be regarded as a single, but it is obvious that the composite node implies an assembly sequence.
Calculate mating directions for all nodes in the relation graph. Again, beginning at the state that the shaft and the hole are assembled, separate the part in one degree of separation by a certain distance (larger than the maximum tolerance), and than check if interference occurs. Separation in both ±x axis and ±y axis of R1 causes the interference between the shaft and the hole. Separation in the +z direction raises on interference. Then, select the +z direction as the mating direction, which is represented as a vector M measured in the coordinate system of the assembly. It should be noted that , in some case, there may be several possible mating directions for a part. The condition for assembly operation in the mating direction at the assembled state, which can be checked simply with geometric constraints, the end condition is measured by force sensory information, whereas position information is used as an end condition.
Calculate the grasping position. In this paper, parts are handled and manipulated with two separate probes, which will be discussed in the Sect.4, and planes or edges are considered for grasping. In the case that there are several mating directions, the grasping plans are selected as G1G2…Gi, where Gi is possible grasping plane/edge set for the ith mating direction when the part is at its free state. For example, in Fig. 4, the pair planes P1/P1’, P2/P2’, and P3/P3’ can serve as possible grasping planes, and then the grasping planes are {P1/P1’, P2/P2’, P3/P3’}/{P1/P1’, P3/P3’}/{P1/P1’,P2/P2’}={P1/P1’}
The approaching direction of the end-effector is selected as the normal vector of the grasping planes. It is obvious that not all points on the grasping plane can be grsped. The following method is used to determine the grasping area. The end-effector, which is modeled as a cuboid, is first added in the CAD model, with the constraint of coplanar or tangential with the grasping plane. Beginning at the edge that is far away from the Bae-Part in the mating direction, move the end-effector in the mating direction along the grasping plane until the end-effector is fully in contact with the part, the grasping plane is fully in contact with the end-effector, or a collision occurs. Record the edge and the distance, both of which are measured in the part’s coordinate system.
Separate gradually the two parts along the mating direction, which checking interference in the other degrees of separation, until no interference occurs in all of the other degrees of separation. There is obviously a separation distance that assures interference not to occur in every degree of separation. It is called the safe length in that direction. This length is used for the collision-free path calculation, which will be discussed in the following section.
2.2 Assembly sequence
Some criteria can be used to search the optimal assembly sequence, such as the mechanical stability of subassemblies, the degree of parallel execution, types of fixtures, etc. But for microassembly, we should pay more attention to one of its most important features, the limited workspace, when selecting the assembly sequence. Microassembly operations are usually conducted and monitored under microscopy, and the workspace for microassembly is very small. The assembly sequence brings much influence on the assembly efficiency. For example, a simple assembly with three parts. In sequence a, part A is first fixed onto part B. In the case that part C cannot be mounted in the workspace at the same time with component AB because of the small workspace, in order to assemble part C with AB, component AB has to unmounted from the workspace. Then, component C is transported and fixed into the workspace. After that, component AB is transported back into the workspace again. In sequence b, there is no need to unmount pay part. Sequence a is obviously inefficient and may cause much uncertainty by an assembly sequence , the more inefficient the assembly sequence. In this paper, due to the small-workspace feature of microassembly, the number of times necessary for mounting of parts is selected as the search criteria to find the assembly sequence that has a few a number of times for the mounting of parts as possible.
This paper proposes the following approach to search the assembly sequence. The relation graph of the assembly is used to search the optimal assembly sequence. Heuristic approaches are adopted in order to reduce the search times:
Check nodes connected with more than two nodes. If the mating directions of its connected nodes are different, mark them as inactive nodes, whereas mark the same mating directions as active mating direction.
Select a node that is not an inactive node. Mark the current node as the base node (part). The first base part is fixed on the workspace with the mating direction upside (this is done in the CAD model).Compare the size (e.g., weight or volume) of the base part with its connected parts, which can be done easily by reading the bill of materials (BOM) of the assembly. If the base part is much smaller, then mark it as an inactive node.
Select a node connected with the base node as an assembly node (part). Check the mating direction if the base node needs to be unmounted from the workspace. If needed, update a variable
In the CAD model, move the assembly part to the base part in the possiblemting direction, which checking if interference (collision) occurs. If interference occurs, mark the base node as an inactive node and go to step 2, whereas select the Operation type according to parts’ geometric features. In this step, an Obstacle Box is also computed. The box, which is modeled as a cuboid , includes all parts in the workspace. It is used to calculate the collicion-free path to move the assembly part, which will be introduced in the following section. The Obstacle Box is described by a position vector and its width, height, and length.
Record the assembly sequence with Operation type, the mating direction, and the grasping position.
If all nodes have been searched, then mark the first base node as an inactive node and go to step 2. If not, select a node connected with the assembly node. Mark it as an assembly node, and the assembly node that is same as the mating direction of the former assembly node. If there is, use the former mating direction in the following steps. Go to step 3.
After searching the entire graph , we may have search assembly sequence s. Comparing the values of mount , the more efficient one can be selected. If there are N nodes in the relation graph of Fig. 2b , all of which are not classed as inactive node, and each node may have M mating directions, then it needs M computations to find all assembly sequences. But because, usually, one part only has one mating direction, and there are some inactive nodes, the computation should be less than Mn.
It should be noted that, in the above computation, several coordinate systems are involved, such as the coordinates of the assembly sequences, the coordinates of the base part, and the coordinates, of the assembly. The relations among the coordinates are represented by a 4*4 transformation matrix , which is calculated based on the assembly CAD model when creating the relations graph. These matrixes are stored with all o the related parts in the database. They are also used in skill decomposition.
3 Skill decomposition and execution
3.1 Definition of skill primitive
Skill primitives are the interface between the assembly planning and robot control. There have been some definitions on skill primitives. The basic difference among these definitions is the skill’s complexity and functions that one skill can fulfill. From the point of view of assembly planning, it is obviously better that one skill can fulfill more functions. However, the control of a skill with many functions may become complicated. In the paper, two separate probes, rather than a single probe or process is not easy. In addition, for example, moving a part may involve not only the manipulator but also the worktable. Therefore, to simplify the control process, sills defined in the paper do not include many functions.
More importantly, the skills should be easily applied to various assembly tasks, that is, the set of skill should have generality to express specific tasks. There should not be overlap among skill. In the paper, a skill primitive for robot control is defined as:
Attribute -I, Action -i(Attribute -i),
Si= Start -i(Attribute -i), End -i(Attribute -i)
Condition -i(Attribute -i).
Attribute –I Information necessary for Si to be executed. They can be classified as required attributes and option attributes, or sensory attributes and CAD-model-driven attributes. The attributes are represented by global variables used in different layers.
Action_I Robots’ action, which is the basic sensormotion. Many actions are defined in the system, such as Move_Worktable, Move_Probes, Rotation_Worktable, Rotation_Probes, Touch, Insert, Screw, Grasp, ect. For one skill, there is only one Action. Due to the limited space, the details of actions will not be discussed in the paper.
Start_i The start state of Action_i, which is measured by sensor values.
End_i The end state of Action_i, which is measured by sensor values.
Condition_i The condition under which Action_i is executed.
From the above definitions, we may find that skill primitives in the paper bobot motions with start state and end state, and that they are executed under specific conditions. Assembly planning in the paper is to generate a sequence of robot actions and to assign values to attributes pf thede actions.
3.2 Skill decomposition
Some approaches have been proposed for skill decomposition. This paper presents a novel approach to guide the skill decomposition. As discussed above, in the present paper, a task is to assemble the Assembly_Part with the Base_part. We define the process from the state that Assembly_Part is at a free state to the state it is fixed with Bese_Part as the assembly lifestyle of the Assembly_Part. In its assembly lifecycle, the Assembly_Part may be at different assembly states. Here shows a shaft’s sates show as blocks and associated workflows of an insertion task. A workflow consisting of group of skills pushes forward the Assembly_Part from one state to another state. A workflow is associated with a specific skill generator that is in charge of generating skills. For different assembly tasks, the same workflows may be uded, though specific skills generated for different tasks may be different.
The system provides default task templates, in which default states are defined. These templates are imported into the system and instantiated after they are associated with the corresponding Assembly_Part. In some cases, some states defined by the default template may be not needed. For example, determined by the fixture, then the Free and In_WS states can be removed from the shaft’s assembly lifecycle. The system provides a tool for users to modify thede templates or generate their own templates. The tool’s user interface is displayed in.
For a workflow, the start state is measured by sensory values, which the target state is calculated based on the CAD model and sensory attributes. According to the start state and target state, the generator generates a series of skills. Here, we use the Move workflow in as an example to show how skills are gener
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