并联机器人原文知识分享

并联机器人原理
并联机器人是一种由多个机械臂和连接它们的关节组成的机器人系统。

与传统的串联机器人不同，每个机械臂都可以独立运动，同时协同工
作以完成任务。

这种并联结构为机器人带来了更高的精度、速度和灵
活性。

并联机器人由基座、运动平台、连杆和关节组成。

基座是机器人的固
定部分，通常安装在地面上或其他支撑物上。

运动平台是相对于基座
移动的部分，它支撑着连杆和工具端执行器。

连杆是连接运动平台和
工具端执行器的部分，它们通常由多个轴组成，并且能够扭曲和伸缩
以适应不同的任务需求。

关节是连接连杆和运动平台或工具端执行器
的旋转点，使得整个系统能够实现各种运动。

并联机器人采用了“约束自由度”控制策略，即通过将一个或多个自
由度限制在特定范围内来控制整个系统。

这种控制方式可以减少系统
中不必要的自由度，并提高精度和稳定性。

并联机器人还可以通过使用力传感器实现力控制。

力传感器可以检测
到机器人与工作物件之间的力和扭矩，并将其转换为电信号，以便机
器人系统可以实现精确的力控制和力反馈。

总之，通过并联结构和约束自由度的控制策略，以及使用力传感器实现精确的力控制和反馈，使得并联机器人在工业生产、医疗保健、科学研究等领域具有广泛应用前景。

并联机器人原理1. 引言随着科技的不断发展，机器人在各个领域中的应用越来越广泛。

并联机器人作为机器人领域的一个重要分支，在工业自动化、医疗手术、航天等领域中发挥着重要作用。

本文将介绍并联机器人的原理、结构和应用，并从机构设计、运动学分析、动力学模型等方面进行深入探讨。

2. 并联机器人的定义和分类并联机器人是指由两个以上的机器人并联组成的机器人系统。

根据其结构和运动特点的不同，可以将并联机器人分为平台式并联机器人、串联式并联机器人和混联式并联机器人。

2.1 平台式并联机器人平台式并联机器人由一个移动平台和多个执行器组成，执行器通过机械连接装置连接到移动平台和工作台之间。

它具有高精度、高刚度和高灵活性的特点，在精密加工、装配和仿真等应用中得到广泛应用。

2.2 串联式并联机器人串联式并联机器人由多个运动杆件组成，杆件通过运动副连接在一起，形成一个连续链式结构。

串联式并联机器人通过杆件之间的相对运动实现工作台的运动，具有较大的工作空间和自由度，适用于需要较大工作范围和高精度运动的应用。

2.3 混联式并联机器人混联式并联机器人是平台式和串联式并联机器人的结合，既可以实现平台式并联机器人的高刚度和高精度，又能够实现串联式并联机器人的大工作空间和自由度。

混联式并联机器人在飞行器研究、空间站维修等领域具有广泛应用。

3. 并联机器人的机构设计并联机器人的机构设计是实现其运动特性的关键。

机构设计主要包括支撑结构、传动机构和执行机构。

3.1 支撑结构支撑结构是并联机器人的基础，负责支撑整个机器人系统的重量和载荷。

支撑结构应具有足够的刚度和稳定性，以保证机器人在工作过程中的精度和稳定性。

3.2 传动机构传动机构是实现并联机器人运动的关键组成部分，可以通过齿轮传动、皮带传动、链传动等方式实现。

传动机构应具有较高的传动精度和可靠性，以保证机器人的运动精度和稳定性。

3.3 执行机构执行机构是并联机器人的动力来源，可以是液压驱动、电动驱动或气动驱动等。

并联机器人原文Virtual Prototyping of a Parallel Robot actuated by Servo-Pneumatic Drives using ADAMS/ControlsWalter Kuhlbusch, Dr. Rüdiger Neumann, Festo AG & Co., Germany SummaryAdvanced pneumatic drives for servo-pneumatic positioning allow for new generations of handlings and robots. Especially parallel robots actuated by servo-pneumatic drives allow the realization of very fast pick and place tasks in 3-D space. The design of those machines requires a virtual prototyping method called the mechatronic design [ 1]. The most suitable software tools are ADAMS for mechanics and Matlab/Simulink for drives and controllers. To analyze the overall behavior the co-simulation using ADAMS/Controls is applied. The combination of these powerful simulation tools guarantees a fast and effective design of new machines.1. IntroductionFesto is a supplier for pneumatic components and controls in industrial automation.The utilization of pneumatic drives is wide spread in industry when working in open loop control. It’s l imited however, when it comes to multipoint movement or path control. The development has been driven to servo-pneumatic drives that include closed loop control. Festo servo-pneumatic axes are quite accurate, thus they can be employed as drives for sophisticated tasks in robotics. The special advantage of these drives is the low initial cost in comparison to electrical and hydraulic drive systems. Servo-pneumatic driven parallel robots are new systems with high potentials in applications. The dynamical performance meets the increasing requirements to reduce the cycle times.One goal is the creation and optimization of pneumatic driven multi-axes robots. This allows us to support our customers, and of course to create new standard handlings and robots (Fig. 1).The complexity of parallel robots requires the use of virtual prototyping methods.Fig. 1. Prototypes of servo-pneumatic driven multi-axes machinesPreferred applications are fast multipoint positioning tasks in 3-D space. Free programmable stops allow a flexible employment of the machine. The point to point (ptp) accuracy is about 0.5 mm. The continuous path control guarantees collision free movement along a trajectory.1.1. Why parallel robots?The main benefits using parallel instead of serial kinematics is shown in Fig. 2.Fig. 2. Benefits of robots with parallel kinematicsHigh dynamical performance is achieved due to the low moved masses. While in serial robots the first axis has to move all the following axes, the axes of a parallel robot can share the mass of the workpiece. Furthermore serial axes are stressed by torques and bending moments which reduces the stiffness. Due to the closed kinematics the movements of parallel robots are vibration free for which the accuracy is improved. Finally the modular concept allows a cost-effective production of the mechanical parts. On the other hand there is the higher expense related to the control.1.2. Why Pneumatic Drives?The advantages of servo-pneumatic drives are:direct drives→high accelerating powercompact (especially rodless cylinders with integrated guidance)robust and reliablecost-effectiveDirect drives imply a high acceleration power due to the low equivalent mass in relation to the drive force. With pneumatic drives the relationship is particularly favorable. Festo has already built up some system solutions, predominantly parallel robots (see Fig. 1), to demonstrate the technical potential of servo-pneumatics. Which performance can be reached is shown in Fig. 3. This prototype is equipped with an advanced model based controller that makes use of the computed torque method [ 3].Fig. 3. Performance of the Tripod2. Design MethodThe system design, where several engineering disciplines are involved in, requires a holistic approach. This method is the so-called mechatronic design. The components of a mechatronic system are the mechanical supporting structure, the servo drives as well as the control. All these components are mapped into the computer and optimized with respect to the mutual interaction. This procedure can be used to analyze and improve existing systems as well as to create new systems. The two main steps of the mechatronic design are first building models in each discipline, and secondly the analysis and synthesis of the whole system. These steps are done in a cycle for the optimization.The modeling can be carried out in two ways: Either you apply one tool to build up models in all disciplines, but with restrictions. The other way is to use powerful tools in each discipline and to analyze the whole system via co-simulation. In this case you have to consider some specials of the solving method like communication step size or direct feedthrough behavior.2.1. Why Co-Simulation?Co-simulation is used because of the powerful tools, each specialized in its own discipline. ADAMS is an excellent tool for the mechanical part and Matlab/Simulink is the suitable tool for controller development and simulation of pneumatics.The behavior of the mechanical part is modeled at best usingADAMS/View. The advantages of ADAMS are:fast physically modeling of rigid and elastic bodiesextensive features for parameterizationanimation of simulation resultssolving inverse kinematics by “general point motion”visualization of eigenmodes (ADAMS/LINEAR)export of linear models (A,B,C,D)A big advantage is the automatic calculation of the direct and inverse kinematics. The direct kinematics of parallel structures often cannot be solved analytically. Furthermore different kinematics can be compared to each other very easily when you define a trajectory of the end-effector via “general point motion”.Applying these two software tools guarantees a high flexibility regarding the design of new systems. It is very important to analyze the closed loop behavior at an early stage. This makes a big difference between the mechatronic design and the conventional design. Furthermore the visualization of the mechanical system makes the discussion within a team very easy.2.2. RestrictionsA disadvantage is that the model of the mechanics is purely numerically available. However some symbolic code of the mechanical system is needed for the control hardware when the system becomes realized. In general we have to derive the equations of the inverse kinematics, which are used in the feed forward control. For specific robot types a controller with decoupling structure is necessary in order to fulfill the requirements. Then the symbolic code of the dynamics is needed. For this we have to pull up further tools to complete the task.2.3. What has to be analyzed?For the design of new robots it is important to know about the effect on the system stability and accuracy. The main properties that influence stability and accuracy are opposed in Table 1 for different kinematical structures.Table 1: Properties of different kinematical configurationsWith respect to the control the cartesian type is the best one. But the main disadvantage of a serial robot compared with a parallel one is the lower dynamics and the lower stiffness (see Fig. 2).Depending on the requirements with regard to dynamics and accuracy different control approaches must be applied. As mentioned above we prefer to employ a standard controller SPC200 for a single axis. Due to the coupling of the axes the stability of the closed loop system must be checked.3. Model of the TripodThe model of the Tripod consists of three parts: the mechanics, the pneumatic drives, and the controller.3.1. Mechanics (ADAMS)We apply the so-called delta-kinematics which causes a purely translational movement of the tool center point (tcp). An additional rotary drive allows the orientation of the gripper in the horizontal plane. Together with the rotary drive the machine has four degrees of freedom.Fig. 4. Degrees of freedom and structure of the TripodThe tripod is modeled using rigid body parts what is often sufficient for the present type of parallel structure. The upper and lower plates are fixed to ground. The profile tubes are connected to these plates via fixed joints. Eachslider has one translational degree of freedom. Both ends of a rod are connected to the neighbored parts by universal joints. Including the rotary drive, the model verification results in four Gruebler counts and there are no redundant constraints. The model is parameterized in such a way that different kinematical configurations can be generated very easily by means of design variables. The most important parameters are the radiuses of the plates (see Fig. 4) and the distances to each other. For instance the following configurations can be achieved just by variation of these parameters or design variables.Fig. 5. Variation of kinematics by “design variables”3.2. Servo-Pneumatic Drives (Simulink)The models of the servo-pneumatic drives are developed by means of Matlab/Simulink. Depending on the requirements several controller models were developed. It is common to all that they are highly non-linear. Mainly the compressibility of air makes a more complex control system necessary. All controller models including the standard controller SPC200 are available asC-coded s-functions. This allows to use the same code in the simulation as well as on the target hardware.A survey of the control scheme is shown in Fig. 6. For this contribution it is important to know about the interface for the co-simulation. The calculated forces of the servo pneumatics are the inputs to the mechanics. The slider positions are the outputs of the mechanics. Detailed information on the controllers can be found in [ 2] and [ 3].Fig. 6. Control structure4. Analyzing the behavior of the whole systemWhen the modeling is done we can go on with the second step of the mechatronic design. In the following it is assumed that the SPC200 controller always controls the machine. The task is the analysis and synthesis of different parallel kinematics relative to stability, dynamics, and accuracy for a given workspace.Some studies, e.g. concerning the workspace, can be made exclusive using ADAMS. Others such as feedback analysis are carried out by means of co-simulation.The workspace can be determined by varying all drive positions in all combinations. After simulation the end-effector positions are traced using the feature “create tracespline”.Fig. 7. Drive motions for the workspace calculationThe data can be visualized in ADAMS or any other graphics tool. As an example the workspace of the Tripod configuration of Fig. 7 is represented in Fig. 8Fig. 8. Workspace of the Tripod (configuration as in Fig. 7) Measuring the velocity of the end-effector at the same time delivers the gear ratios of all drives over the workspace.To examine the behavior of the closed loop system ADAMS/Controls is used to couple ADAMS and Simulink. Before the model can be exported some inputs and outputs of the plant must be defined by state variables. The inputs of the Tripod are the drive forces. Though the controller makes only use of the drive position some additional signals are defined as outputs: The drive velocities are needed for solving the differential equations of the pressures in the pneumatics model. Furthermore we need the velocity of the tool center point to calculate the non-linear gear ratios. Finally the drive accelerations serve for the calculation of the equivalent moved masses. The whole system is shown in Fig. 9.Fig. 9. Model of the whole systemThe model of the mechanics is embedded in Simulink. ADAMS/Controls makes the interface available by means of s-function.The equivalent moved masses depend on the positions of drives. The non-linearity of the robot grows with the strength of this dependency. As shown in Table 1 with the parallel kinematics there is a medium strong coupling of the dynamics. This coupling is neglected, if we use the standard SPC200 controller. Nevertheless there is an influence on the stability of theclosed loop system. To initialize and parameterize this controller we need the following information from the mechanics model:equivalent moved mass of each drive (depends on slider positions)gravity forces in initial positionCoulomb and viscous frictionThe controller is designed for a single axis with a constant mass. Due to the position dependency of the equivalent moved masses of the robot we have to choose an average value for each drive. Unfortunately with ADAMS there is no easy way to calculate the equivalent moved masses along atrajectory. We tried to apply different methods such as dividing a drive force by its acceleration during a slow motion, but this method yielded not insatisfying results. The best method found is the linearization of the system.However this requires ADAMS/Linear. When we define the drive accelerations as plant outputs in ADAMS/Controls the direct feed through matrix D of the exported linear system delivers the mass matrix in the defined operating point as1)()(-⋅=q q D f MCorresponding to the three degrees of freedom of the rigid body system the size of the mass matrix M(q) is three by three. It depends on the vector of the generalized coordinates of the drives. The non-diagonal elements cause the coupling between the axes. The factor f depends on the units chosen for the inputs and outputs. Whenthe forces are given in [N] and the accelerations are given in [mm/s 2] f is 0.001.With a slider mass of 2 kg and an end-effector mass of 2 kg the massmatrix for the three positions shown in Fig. 10 are:The gravity forces can be calculated very easily by static simulation.Likewise it is easy to model the friction in ADAMS. Nevertheless theparameters can differ very strong from one application to another one.With the parameterized controller the stability should be checked inseveral operating points by means of eigenvalues and the dynamics of the closed loop system can be analyzed by means of frequency responses.Of course with a robust controller you can start with a simulation in time domain. This gives information about the accuracy and system limits. For this we need the references for the drives. For a reference trajectory of the tool center point ADAMS applying the “general point motion” can generate the drive positions.Fig. 10. Solving inverse kinematics by feature "general point motion"In the following the simulation results are presented for a tripod configuration shown in Fig. 10. The workspace of this machine is illustrated in Fig. 8.Fig. 11. Left: Trajectory of the tool center point. Right: Drive references and measures5. ConclusionThe coupling of the software tools ADAMS and Simulink via co-simulation is a powerful method of virtual prototyping. This method enables an efficient design and optimization of servo-pneumatic driven robots. Especially robots with parallel kinematics can be analyzed very fast using ADAMS. Due to the potential of the linear analysis the use of ADAMS/Linear is meaningful. Particularly with controlled systems the linear analysis is required.Literature[ 1] Kuhlbusch, W., Moritz, W., Lückel, J., Toepper, St., and Scharfeld, F.: T RI P LANAR - A New Process-Machine Type Developed by Means of Mechatronic Design. Proceedings of the 3rd International Heinz Nixdorf Symposium on Mechatronics and Advanced Motion Control, Paderborn, Germany, 1999.[ 2] Neumann, R., Göttert, M. Ohmer, M.: Servopneumatik – eine alternative Antriebstechnik für Roboter, Robotik 2002, 19-20. Juni in Ludwigsburg, Germany, 2002, VDI-Bericht Nr. 1679 p. 537-544.[ 3] Neumann, R., Leyser, J., Post, P.: Simulationsgestützte Entwicklung eines servopneumatisch angetriebenen Parallelroboters. TagungsbandSIM2000 – Simulation im Maschinenbau, Dresden, Germany, 2000, p. 519-536.。

并联正文：1.简介本文档是一个并联的详细说明，包括的结构、工作原理、控制系统等方面的内容。

2.结构2.1 机械结构并联的结构由多个关节和连杆组成，其中关节连接主要的动力元件，连杆连接各个关节。

机械结构的设计需要考虑的运动范围、负载能力以及稳定性等因素。

2.2 末端执行器并联的末端执行器通常包括夹爪、工具等，用于完成特定的任务，如抓取、装配等。

3.控制系统并联的控制系统主要包括硬件和软件两个部分。

3.1 硬件硬件部分包括传感器、驱动器和控制器。

传感器用于对的姿态、位置等进行测量，驱动器用于驱动机械结构的关节，控制器则用于运行控制算法并实施控制策略。

3.2 软件软件部分包括运动规划、路径规划等算法的开发与实现。

通过软件控制，可以使在特定的工作空间内完成精确的运动任务。

4.工作原理并联通过控制系统的指令实现工作任务，其工作原理基于运动学和动力学原理。

的工作过程需要考虑运动学约束、静力学约束等因素。

4.1 运动学的运动学描述的位置和姿态之间的关系。

运动学约束主要包括正向运动学和逆向运动学。

4.2 动力学的动力学描述在外部力作用下的运动学特性。

动力学约束主要包括速度和加速度的限制。

5.应用领域并联广泛应用于汽车制造、航空航天、医疗卫生等领域。

的高精度、高效率和精确性使其成为许多工业任务的理想选择。

附件：本文档涉及的附件包括相关设计图纸、算法代码等。

法律名词及注释：1.并联：由多个关节和连杆组成的结构，具有高度精确性和高效率的特点。

2.运动学：描述的位置和姿态之间的关系的科学。

3.动力学：描述在外部力作用下的运动学特性的科学。

并联机器人的设计讲义
一.并联机器人的定义
并联机器人是一种由多个机械臂连接在一起的可移动机器人。

它的特点是机械臂可以独立活动，它们之间的旋转和移动有一个统一的控制器。

它可以用于复杂的加工，如焊接、装配和组装，也可以用于物料搬运、操作、维修和检查。

二.并联机器人的优势
1、操作灵活：并联机器人具有操作灵活的特点，它可以自由组合不同的机械臂，并可根据任务的不同而变换机械臂，可以解决不同空间的工作要求，可以完成不同的任务；
2、可重复性：并联机器人可以完成同一任务的多次重复操作，使操作精度大大提高，而且可以保持一定的精度；
3、可靠性：并联机器人可以通过可靠的控制系统、高精度的传感器和自动化操作系统，保证机器运行的可靠性；
4、安全性：并联机器人可以通过一些保护措施，比如安全光栅等，防止人员受到意外的伤害；
三.并联机器人的设计
1、机械结构设计：并联机器人的机械结构定义了它的工作范围，要求设计师要根据机器人实际的工作空间，进行机械臂和运动系统的精心设计，以便达到机器人的精度和覆盖范围；
2、控制系统设计：并联机器人的控制系统设计是机器人自动化的核心。