采摘机器人机械手外文翻译@中英文翻译@外文文献翻译

毕业论文（设计） 外文翻译 题 目 ： 运动学和轨迹规划的黄瓜采摘机器人机械手 系部名称： 专业班级： 学生姓名： 学 号： 指导教师： 教师职称 ： 20*年 03 月 10 日 张 利兵 、 王雁 、 杨庆华 、 宝冠君 、 高锋 、 薰易 (教育部重点实验室的机械制造及自动化 、浙江理工大学、中国杭州 310012) 摘要 ： 为了降低成本，提高黄瓜收获经济效益，黄瓜收获机器人得以发展。 黄瓜果蔬采摘机器人由一辆汽车 ,一个四自由度关节机械手 ,一个手端 ,一个上一个视觉系统与监控、四直流伺服驱动系统 组成。 把黄瓜的运动学果蔬采摘机器人机械手使用 D- H 标系建立了框架模型。 而且它提供了一个逆运动学轨迹规划的基础已经解决了逆变换技术。 摆线针轮运动 ， 它具有的性能的连续性和零速度和加速度的港口及有界区间 ， 采用一种可行的 方法在关节空间轨迹规划 ， 研究了果蔬采摘机器人的机械臂的黄瓜。此外 ， 硬件和摘要软件基 于上面的显示器之间的交流及关节的控制器的设计。实验结果表明 ， 上面的显示器与四关节控制器的沟通 ， 有效地摘要错误的思想和综合四关节角不超过四度。误差产生的可能因素分析及相应的解决方案 ， 为提高测量精度的措施提出了建议。 关键词 ： 黄瓜果蔬采摘机器人轨迹规划、关节机械臂、运动、摘要、摆线针轮 分类号： 10.3965/j.issn.1934-6344.2009.01.001-007。 引文： 张 利兵，杨庆华，宝冠君，高锋，薰易。运动学和轨迹规划黄瓜收获机器人的机械手。农业与生物学工程， 2009； 2（ 1）： 1-7。 一介 绍 水果和蔬菜的收获是一个劳力密集的工作，由人类劳动和收获的成本大约是 33 总数的 50，生产成本 1。因此，机械化和自动化，迫切需要水果和蔬菜收获。目前，许多国家正在研究。 收稿日期： 08-11-20 接受日期： 009-03-28 传记 ： 张 利兵，教授，博士，主要从事农业机器人，机电一体化和控制。王雁，博士候选人浙江工业大学，主要从事，机器人，智能仪表。杨庆华，教授，博士，主要从事机器人技术，机电一体化和控制。宝冠君，讲师，博士，主要从事机器人技术，控制人数及机器视觉。高峰，副教授，博士，主要从事机电工 程等。薰易，博士，主要从事视觉系统和图像处理。 通讯作者 : 张 利兵， 教育部重点实验室机械制造、自动化、浙江工业大学 310012 技术 ,中国 ,杭州， 310012。电话及传真： +86-571-88320007。电子邮箱： 研究了果蔬采摘机器人 ,尤其是荷兰和日本。机器人的一些收获 ,如黄瓜、西红柿、葡萄收获机器人已广泛应用在温室里和其他人在农场上 2、 3。在中国 ,虽然研究是迟于果蔬采摘机器人在发达国家 ,一些有利的方面取得通过努力在国内许多高等院校和研究机构 ,就是这样的采摘机器人的设计由中国茄子农业大学和一个番茄收获机器人浙江大学开发的。 国家高技术 大力支持下 ,国家级高新技术研究和发展计划 (863)(2007AA04Z222),第一个系统化的黄瓜研究了果蔬采摘机器人在中国是联合研制开发的中国农业大学和浙江工业大学技术。 它由一个车，一个 4自由度（简称自由度）关节机械手，一最终效应，一上位，视觉系统和四个直流伺服驱动系统。由浙江工业大学， 利用一种工业机械手来代替四自由度关节机械手的 关节，旨在减少成本和适应环境 的收获。 本文主要考察了四自由度铰接式机器人运动学和轨迹规划，这是概述如下。在第一节中，结构黄瓜收获机器人机械臂描述。机械手的运动学建造的第 2 节逆运动学和第 3节中得到解决。第 4节的轨迹规划算法摆线运动。硬件和软件设计轨迹规划基于 CAN 总线技术的引入第 5 节。实验测量的实际位置 4 节进行抢修，对错误的可能原因在第 6 节进行了分析。最后，结论是画在第 7节。 二黄瓜采摘机器人机械手结构 本文详细介绍了运动学机械手和轨迹规划的实现基于 CAN 控制总线。线图和关节机械手的照片显示在图 1。它是由四个旋转接头：腰围关节（ J1），肩关节（ J2），肘关节（ J3）和手腕联合（ J4）。一端固定在底座上，另一端连接到终端效应其中包含两个部分：一爪 抓 水 果 和 切 割 设 备 另 外 从 植 物 的 果 图 1线框图和相片的黄瓜果蔬采摘机器人机械臂 该系统采用黄瓜采摘机器人多 CPU，分布式控 制，上位机和联合伺服控制器的结构。 此外，四个关节驱动的完美和谐的工作通过 CAN 总线通讯，有效支持分布式实时控制系统。该通信系统黄瓜收获机器人如图 2 所示。在上位监控用于监控和管理整个机器人系统，找到黄瓜目标，并规划轨迹。 CAN 总线是传输的桥梁上位监控和联合控制器。伺服控制器，分布在各个关节驱动力矩马达和他们能够实现闭环控制从接受角度编码器反馈信号。 图 2通信系统中的黄瓜收获机器人 三学模型坐标框架 运动学模型坐标框架 Denavit-Hartenberg模型 ,构造了 (D- H型 ),这已被广泛使用在机器人由于它吗明确的机制和物理解释在相对容易实施的程序机器人操作臂控制的。 D- H标系框架模型基于任务的笛卡尔坐标框架固定相对于机器人机械臂的每一环节。而且它描述了空间变换关系两个连续的 44 连结变换矩阵我 i-1 Ai，以链接的氮转化成相应的坐标框 架坐标系可以被写为 4,5： 其中 a 是一个 是 接近的方向向量； 0 定向的矢量， n = 0 a 是一个正常的向量； P 为最终效应相对位置向量基础坐标系。 在 D- H的变换矩阵 i-1Ai关一数的旋转和平移两连续帧坐标表示为 6， 7： 其中是联合角； i是扭转角； di是一个联合抵消； ai是一个链路长度。 图 3所示的 D H坐标系的帧机器人机械臂和表 1总结它的 D H 参数。 图 3 D H坐标系黄瓜收割机器人操作臂控制 表 1机器人的机械臂 D H参数 四黄瓜收获机器人的机械手逆运动学 逆运动学问题的机器人机械手是要找到一个载体，联合变量产生一个理想的最终效应位置和方向。逆变换技术来解决问题 8,9。为了挑选黄瓜方便，腕关节，必须平行于 X轴的坐标系的基础，所以可以得到： 2 + 3 + 4 = 0 对 于方程（ 1），它可以改写为： 而 首先，让等式（ 3,4）矩阵（ 4）及（ 5）是等价的， 1可表示为： 那就让等式（ 1， 4）和（ 2,4）矩阵（ 4）及（ 5）是等价的，下面的公式可以得到： 通过简化方程（ 7）： 从方程（ 7），可得出 2 ， 3 可表示为： 五在关节空间轨迹规划的基础上摆线运动 该机器人的机械 手 轨迹规划以这种方式 定义：找到共同的时空运动规律位置，速度和 加速度，根据给定操作的最终效应。运动规律由轨迹规划师产生的必须使用一些特别是战略来消除额外的运动，如抖振和共鸣。他们必须是足够光滑，连续的第一及第二衍生物 10,11。在规划数算法，摆线运动，尤其适合适用于点对一点，因为它的轨迹规划金额较小的计算，平滑度和连续性，零速度和加速度，并在最初的功能和有界区间 12终点。它的运动曲线可以描述为 13： 那么它的第一和第二导数可以表示为： 而 是常规时间， T为一个收获的工作时间。 图 4显示了弯的摆线针轮运动和它的第一和第二衍生物在规范区间 (- 1,1)。从图 4,它可以清楚地看出摆线针轮运动是平的 ；同时 ,充分的速度和加速度运动和价值观都是连 续的。 图 4 摆线运动和第一及第二衍生物 开始和结束点的区间 0 1足轻重。这证明了机器人末端执行器的的运动机器人操作臂控制 不会 抖振 ， 所以它可以确保运动稳定性的机器人系统。 如属联名我，轨迹规划和位置依赖定位最终效应。 所以 ,第一步的获取轨迹规划是三维的描述目标的空间小黄瓜。这描述是基于感官信息等机器视觉以及先验信息机器人的机械臂运动 学结构 。 从目标位置的机器人末端执行器与逆 6 日运动学 (Eqs 10、 12、 13)。开始后关节角 qi(f)我问被红牌罚下 ,通过从关节控制器的摘要 ,这个位置 ,速度 ,加速度方程的基础上摆线针轮运动可以表达为 :开机后关节角度 qi(0)智商已经从通过 CAN 总线控制器的联合，位置，速度，加速度方程的基础上摆线运动可以表示为： 六硬件和软件设计的轨迹规划基于 CAN 总线 6 1. 接口电路的 CAN 总线 控 制器区域网络（ CAN）是一种先进的串行通讯协议的分布式实时控制系统。不同的设备，如处理器，传感器和执行器可以连接到 CAN 总线通过双绞线，可以互相沟通通过交换信息。最大传输速率可达 1Mbps 的在嘈杂的环境。和它利用载波感测多重存取及碰撞检测（ CSMA/ CD）为仲裁机制使其附着节点有访问总线 14-16。黄瓜收获机器人系统采用点多点的 CAN 总线通信。该上 位机和四个控制器是由联合 dsPIC30F4012 为数字信号处理器包含标准 CAN 控制器和 MCP2551 收发器。和一个 4 线接口的设计基于 CAN 总线协议（ CAN2.0A），它提供电源，接地和基础两个数据线（ CAN 高和 CAN 低）。该接口的 CAN总线电路示于图 5。和上监视电路板如图 6所示。该的 CAN 总线通信，采用 1Mbps 的传输率，和消息传递由 2个字节的标识符， 1个字节的数据长度和 8字节的数据。消息以时间为 10毫秒内透光根据收获的要求。 CAN 总线通信具有良好的实时性能，在实际申请专利。 图 5接口电路的 CAN 总线 图 6上监视电路板 6 1. 软件设计的轨迹规划黄瓜采摘机器人 上部显示器具有管理职能和监理的机器人系统，黄瓜目标位置和轨迹规划。该方案设计采用了模块化的构想，是由几个子程序。图 7 说明过程为黄瓜收获机器人轨迹规划。它包括如 CAN 总线发送和子程序接收，黄瓜目标捕获，逆运动学和轨迹规划。 图 7 流程图的轨迹规划 七实验和分析 为了验证弹道精度规划算法和 CAN 总线通信，实验测量的实际位置的四个黄瓜收获机器人的机械手的执行关节与坐标测量机（ CMM）的法鲁技术白金 FaroArm 测量臂法团。作为世界上最 畅销的便携式测量臂，铂 FaroArm 测量臂是在尺寸规格从 1.2 米到 3.7 米，有精度高达 0.013 毫米。 实验进行如下： 1）设置最终 effecor 位置： Px = 700mm, Py = 200mm, Pz = 668mm 。 通过利用逆运动学，四个关节角度可以计算出来方程（ 6） （ 13）： 1 =15.95， 2 =55.82 ， 3 =-33.48， 4 =-22.34 。 2）对每一节理面与摆线轨 迹运动算法和发送邮件的计划角通过 CAN 总线控制器的联合。 3）使用铂 FaroArm 测量臂的角度来衡量实际扭矩马达的旋转。 4）其他 9 月底效应，重复（ 1） （ 3）步的位置。实验结果列于表 2。 实验结果表明，四个关节角度的综合误差不超过四度。对实验误差的可能原因是： （ 1）单关节控制精度为 0 1 ，（ 2）机械结构错误，包括安装和变形误差 ；（ 3）最终没有意识到效应闭环位置控制。相应的解决方案是：（ 1）添加一些补偿算法，以提高单关节控制精度，（ 2）代替铝用于 PVC 合金制造的机械手，以减少机械误差 ；（ 3）安装在一 个小型摄像机最终效应，实现了闭环控制机械手。 表 2实验结果对实际测量的位置机器人机械手的四个关节 理论值（度） 测量值（度） 八结论 1)研究了果蔬采摘机器人运动学的黄瓜机械手使用 D H坐标系建立了框架模型。逆向运动学 ,它提供了一个轨迹规划的基础 ,已经解决了反变换技术。 2） 摆线运动，它的性质连续性，计算量小，速度为零并在有界区间的港口加速，是建议，作为可行的方法进行规划，关节轨迹空间机器人的机械手。 3） 软件和 CAN 总线的硬件上位机之间的沟通和联合控制器的设计。 4） 实验结果表明 ,上面的显示器 有四个共同控制器有效地沟通 摘要的 ,综 合误差四关节角均小 于四度。 承认： 这项工作是支持国家自然科学中国基金（ 50575206）和国家高技术研究与发展（ 863）中国项目方案（ 2007AA04Z222）。 九参考文献 【 1】唐秀英，张铁忠。 机器人吃水果和蔬菜收获的综述 ：机器人， 2005,27 （ 1）： 90-96。 【 2】 E. J. Van Henten, J. Hemming 等。 无碰撞采摘黄瓜的运动规划机器人。生物系统工程， 2003； 86(2): 135 144. 【 3】阿锐玛斯，科东恩。黄瓜采摘机器人和植物培训体系。作者：机器人与机电一体化，1999； 11(3)： 208 212。 【 4】熊有伦。机器人技术。武汉：华中大学科技出版社， 1996； pp.18 22。 【 5】 M.Abderrahim, A.R.Whittaker。运动学模型 工业机械手的鉴定。 机器人与 计算机集成制造， 2000； 16: 1 8。 【 6】陈宁，焦恩章。一种新的解决 逆运动学方程的 方案彪马 机械手。南京林业大学。 2003； 27(4): 23 26。 【 7】傅晶逊。机器人。 北京：中国科学 技术出版社， 1989； pp.26 36。 【 8】王萍，杨艳萍，邓晓。研究运动控制模具抛光机器人系统。中国机械工程， 2007；18(20): 2422 2424。 【 9】 Anatoly P. Pashkevich, Alexandre B. Dolgui.机器人定位 运动学方面的制度 ,以电弧焊接的应用程序。控制工程实践， 2003； 11: 633 647。 【 10】 Neelam R Prakash, Kamal T S ,智能规划的挑战和地方行动轨迹。 见：触发。对系统，人与控制论国际会议。 200； 55 60。 【 11】 A. Gasparetto, V. Zanotto. 一个应用程序在弧焊机器人运动学定位系统方面。控制工程实践， 2007； (42): 455 471。 【 12】庄鹏，姚政秋。弹道悬浮电缆并联机器人运动规划的基础上摆线法议案。 机械设计， 2006； (9): 21 24。 【 13】豪尔赫洛杉矶。该机器人的机械系统原理。 北京：机械工业出版社， 2004； 141-148。 【 14】 Hofstee J W, Goense D.模拟一个基于 CAN 拖拉机实施现场总线，符合 DIN 9684。农机工程研究所， 1999； 73（ 4）： 383-394。 【 15】杨向辉。工业通讯和控制网络。北京：清华大学出版社， 2003。 第 84-85。 【 16】 Navet N, Song Y Q. 可靠性的改进下不可靠传输的双优先级的协议。控制工程实践， 1999（ 7）： 975-981。 Kinematics and trajectory planning of a cucumber harvesting robot manipulator Zhang Libin, Wang Yan, Yang Qinghua, Bao Guanjun, Gao Feng, Xun Yi (The MOE Key Laboratory of Mechanical Manufacture and Automation, Zhejiang University of Technology, Hangzhou 310012, China) Abstract:In order to reduce cucumber harvesting cost and improve economic benefits, a cucumber harvesting robot was developed. The cucumber harvesting robot consists of a vehicle, a 4-DOF articulated manipulator, an end-effector, an upper monitor, a vision system and four DC servo drive systems. The Kinematics of the cucumber harvesting robot manipulator was constructed using D-H coordinate frame model. And the inverse kinematics which provides a foundation for trajectory planning has been solved with inverse transform technique. The cycloidal motion, which has properties of continuity and zero velocity and acceleration at the ports of the bounded interval, was adopted as a feasible approach to plan trajectory in joint space of the cucumber harvesting robot manipulator. Moreover, hardware and software based on CAN-bus communication between the upper monitor and the joint controllers have been designed. Experimental results show that the upper monitor communicates with the four joint controllers efficiently by CAN-bus, and the integrated errors of four joint angles do not exceed four degrees. Probable factors resulting in the errors were analyse and the corresponding solutions for improving precision are proposed. Keyword:cucumber harvesting robot, articulated manipulator, trajectory planning, cycloidal motion, CAN-bus DOI:10.3965/j.issn.1934-6344.2009.01.001-007 Citation:Zhang Libin, Wang Yan, Yang Qinghua, Bao Guanjun, Gao Feng, Xun Yi. Kinematics and trajectory planning of a cucumber harvesting robot manipulator. Int J Agric & Biol Eng, 2009； 2(1): 1 7. 1 Introduction Fruit and vegetable harvesting is a labor-intensive job,and the harvesting cost by human labor is about 33% 50% of the total production cost1. Therefore, it isurgent to mechanize and automate fruit and vegetable harvesting. Currently, many countries are studying. Received date: 2008-11-20 Accepted date: 2009-03-28 Biographies:Zhang Libin, professor, Ph.D, mainly engaged in agricultural robot, mechatronics and control. Wang Yan, Ph.D candidate of Zhejiang University of Technology, mainly engaged in robotics, intelligent instruments. Yang Qinghua, professor, Ph.D, mainly engaged in robotics, mechatronics and control. Baoguanjun, lecturer, Ph.D, mainly engaged in robotics, control and machine vision. Gao Feng, associate professor, Ph.D, mainly engaged in electromechanical engineering. Xun Yi, Ph.D, mainly engaged in vision system and image processing. Corresponding author:Zhang Libin, MOE Key Laboratory of Mechanical Manufacture and Automation, Zhejiang University of Technology, Hangzhou 310012, China. Tel & fax: +86-571-88320007. Email: harvesting robot, especially Netherlands and Japan. Some of the harvesting robots, such as cucumber, tomato, grape harvesting robots have been applied in greenhouses and others on farms2,3. In China, though research on harvesting robot is later than that in developed countries,some favorable achievements have been made through efforts in many universities and research institutes, such as the eggplant picking robot designed by China Agricultural University and the tomato harvesting robot developed by Zhejiang University. Under the support of the National High-Tech Research and Development (863) Program of China(2007AA04Z222), the first systematical cucumber harvesting robot in China was jointly developed by China Agricultural University and Zhejiang University of Technology. It consists of a vehicle, a 4-degree of freedom (DOF for short) articulated manipulator, an end-effector, an upper monitor, a vision system and four DC servo drive systems. Instead of utilizing an industrial manipulator, the 4-DOF articulated manipulator was designed by Zhejiang University of Technology to reduce the cost and adapt to the harvesting environment. This paper mainly investigates the 4-DOF articulated manipulator kinematics and trajectory planning, and it is outlined as follows. In Section 1, the structure of cucumber harvesting robot manipulator is described. The kinematics of manipulator is constructed in Section 2 and the inverse kinematics is solved in Section 3. Section 4 presents the trajectory planning algorithm of cycloidal motion. The hardware and software design of trajectory planning based on CAN-bus is introduced in Section 5. Experiments measuring actual position of four joints are carried out and possible causes for errors are analyzed in Section 6. Finally, conclusions are drawn in Section 7. 2 Cucumber harvesting robot manipulator structure This paper describes in detail the kinematics of the robot manipulator and realization of trajectory planning control based on CAN-bus. The line diagram and photograph of the articulated manipulator is shown in Figure 1. It is composed of four rotation joints: waist joint (J1), shoulder joint (J2), elbow joint (J3) and wrist joint (J4). One end is fixed on the base, and the other end is connected to an end-effector which contains two parts: a gripper to grasp the fruit and a cutting device to separate the fruit from the plant. Figure 1 Line diagram and photograph of the cucumber harvesting robot manipulator The cucumber harvesting robot system employs multi-CPU, distributed control structure of upper monitor and joint servo controllers. Moreover, the four joints are driven to work in perfect harmony by CAN-bus communication which efficiently supports the distributed real-time control system. The communication system of the cucumber harvesting robot is shown in Figure 2. The Upper monitor is used to monitor and manage the whole robot system, locate cucumber target, and plan trajectory. The CAN-bus is the transmission bridge between upper monitor and joint controllers. The servo controllers are distributed in each joint to drive torque motors and they can realize close-loop control by receiving feed back signals from angle encoders. Figure 2 Communication system of the cucumber harvesting robot 3 Coordinate frames of kinematics models Coordinate frames of kinematics models are constructed by Denavit-Hartenberg model (D-H for short), which has been widely adopted in robotics due to its explicit physical interpretation of mechanisms and relatively easy implementation in the programming of the robot manipulator. D-H coordinate frame model is based on assignment of Cartesian coordinate frames fixed relative to each link of robot manipulator. And it describes spatial transformation between two consecutive links by 4 4 transformation matrix i-1Ai, so the transformation of link n coordinate frame into the basecoordinate frame can be written as4,5: where a is the vector of approaching direction； 0 is orientation vector, n = a 0 is the normal vector；P is the position vector of end-effector relative to thebase coordinate frame. The D-H transformation matrix i-1Ai relating to a number of rotations and translations between two consecutive coordinate frames is expressed as6,7: Where i is joint angle； i is twist angle；di is joint offset；ai is the length of link. Figure 3 illustrates the D-H coordinate frames of the robot manipulator and Table 1 summarizes its D-H parameters. Figure 3 D-H coordinate frames of the cucumber harvesting robot manipulator Table 1 D-H parameters of the robot manipulator 4 Inverse kinematics of the cucumber harvesting robot manipulator The inverse kinematics problem for a robot manipulator is to find a vector of joint variables that produces a desired end-effector position and orientation. The inverse transform technique is used to solve the problem8,9. In order to pick cucumbers conveniently, the wrist joint has to be parallel to X axis of the base coordinate frame, so it can be obtained: 2 + 3 + 4 = 0 For equation (1), it can be rewritten as: Where First, let element (3,4) of matrix (4) and (5) be equal, 1 can be given by: Then let element (1, 4) and (2, 4) of matrix (4) and (5) be equal, the following equations can be obtained: By simplifying equation (7): From equation (7), 2, 3 can be expressed as: 5 Trajectory planning in joint space based oncycloidal motion Trajectory planning of the robot manipulator is defined in this way: find temporal motion laws for joint position, velocity and acceleration according to a given operation of the end-effector. The motion laws generated by trajectory planner have to use some particular strategies to eliminate extra movements such as chattering and resonance. They have to be smooth enough, and continuous for their first and second derivatives10,11. Within a number of planning algorithms, cycloidal motion is especially suitable to apply in point-to-point trajectory planning because of its smaller amount of calculation, smoothness and continuity, and features of zero velocity and acceleration at the initial and end points of the bounded interval12. Its motion curve can be described as13: Then its first and second derivatives can be expressed as: Where is normalized time； T is a single harvest operation time. Figure 4 shows the curves of the cycloidal motion andits first and second derivatives in canonical interval (-1,1). From Figure 4, it can be clearly seen that the cycloidal motion is adequately smooth； also, the velocity and acceleration motions are continuous and the values at Figure 4 Cycloidal motion and its first and second derivatives the initial and end points of interval 0 1 are zeros.This demonstrates that the motion of the end-effector of robot manipulator won t result chattering, so it can ensure motion stability of the robot system. For joint i , trajectory planning relies on position and orientation of end-effector. So, the first step of trajectory planning is acquiring the three dimensional space description of the target cucumber. This description is based on sensory information such as machine vision as well as priori knowledge about kinematics structure of robot manipulator. Then the goal angles qi(f) of the four joints can be obtained from the target position of the end-effector with inverse kinematics (Eqs 6, 10, 12, 13). After the start joint angles qi(0) i q being sent from joint controllers through CAN-bus, the position, velocity, acceleration equations based on cycloidal motion can be expressed as: 6 Hardware and software design of trajectory planning based on CAN-bus 6.1 Interface circuit of CAN-bus Controller Area Network (CAN) is an advanced serial communication protocol for distributed real-time control system. Different devices such as processors, sensors and actuators can be connected to CAN-bus via twisted-pair wires and can communicate with each other by exchanging messages. The maximum transmission rate can reach up to 1Mbps in a noisy environment. And it utilizes Carrier Sense Multiple Access with Collision Detection (CSMA/CD) as the arbitration mechanism to enable its attached nodes to have access to the bus14-16. The cucumber harvesting robot system employs the point to multi-points communication of CAN-bus. The upper monitor and four joint controllers are composed of dsPIC30f4012 digital signal processor which contains standard CAN controller and MCP2551 transceiver. And a 4-wire interface is designed based on CAN-bus protocol(CAN2.0A), which provides power, ground and two data lines(CAN High and CAN Low). The interface circuit of CAN-bus is shown in Figure 5. And the upper monitor circuit board is shown in Figure 6. The Baudrate of CAN-bus communication is adopted 1Mbps, and the messages transmitted consist of 2-byte identifier, 1-byte data length and 8-byte data. Messages are transmitted with a time internal of 10 ms according to the harvesting requirements. CAN-bus communication exhibits good real-time performance in practical application. Figure 5 Interface circuit of CAN-bus Figure 6 Upper monitor circuit board 6.2 Software design for trajectory planning of the cucumber harvesting robot The upper monitor has functions of management and supervision for the robot system, location of cucumber target and trajectory planning. The program design employs the modularization idea which is composed of several subprograms. Figure 7 illustrates the process of the trajectory planning for the cucumber harvesting robot. It consists of subprograms such as CAN-bus sending and receiving, acquisition of cucumber target, inverse kinematics and trajectory planning. Figure 7 Flow chart for the trajectory planning 7 Experiments and analysis In order to verify the accuracy of the trajectory planning algorithm and CAN-bus communication, experiments to measure the actual position of the four joints of the cucumber harvesting robot manipulator were performed with the coordinate measurement machine(CMM) Platinum FaroArm of FARO Technologies Incorporation. As the world s best-selling portable measurement arm, Platinum FaroArm is available in sizes ranging from 1.2 m to 3.7 m and has precision of up to 0.013 mm. Experiments were carried out as follows: 1) Set the position of the end-effecor:Px = 700mm, Py = 200mm, Pz = 668mm . By utilizing the inverse kinematics, the four joint angles can be computed from equation (6) (13): 1 =15.95， 2 =55.82 ， 3 =-33.48， 4 =-22.34 . 2) Plan trajectories for each joint with cycloidal motion algorithm and send the planned angle messages to joint controllers by CAN-bus. 3) Use Platinum FaroArm to measure the actual angles that torque motors have rotated. 4) Set other 9 positions of end-effector, repeat (1) (3) steps. Experimental results are presented in Table 2. Experimental results indicate that the integrated errors of four joint angles didn t exceed four degrees. The possible reasons for experimental errors are: (1) controlling precision of single joint is 0 1； (2) mechanical structure error including installation and deformation error；(3) the end-effector hadn t realized closed-loop position control. The corresponding solutions are: (1) add some compensation algorithm to improve control precision of single joint； (2) substitute Aluminum alloy for PVC to manufacture the manipulator to decrease mechanical error； (3) mount a mini camera on the end-effector to realize the close-loop control of manipulator. Table 2 Experimental results on measuring actual position of the four joints of robot manipulator 8 Conclusions 1) Kinematics of the cucumber harvesting robot manipulator was constructed using D-H coordinate frame model. The inverse kinematics, which provides a foundation for trajectory planning, has been solved with inverse transform technique. 2) The cycloidal motion, which has properties of continuity, small amount of calculation, and zero velocity and acceleration at the ports of the bounded interval, is proposed as a feasible approach to plan trajectory in joint space of the robot manipulator. 3) Software and hardware of CAN-bus communication between the upper monitor and the joint controllers have been designed. 4) Experimental results show that the upper monitor communicated with four joint controllers efficiently by the CAN-bus, and the integrated errors of four joint angles were less than four degrees. Acknowledgment This work is supported by the Natural Science Foundation of China (50575206) and the N