| 立体苗盘管理机器人的机械臂参数优化与试验 |
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| 引用本文： | 权龙哲,彭涛,沈柳杨,安思宇,季忠良,孙涛.立体苗盘管理机器人的机械臂参数优化与试验[J].农业工程学报,2017,33(7):10-19. |
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| 作者姓名： | 权龙哲 彭涛 沈柳杨 安思宇 季忠良 孙涛 |
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| 作者单位： | 1. 东北农业大学工程学院,哈尔滨,150030;2. 哈尔滨工业大学机器人技术与系统国家重点实验室,哈尔滨,150080;3. 海马汽车有限公司,郑州,450016;4. 长安汽车股份有限公司,重庆,404100 |
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| 基金项目： | 黑龙江省普通高等学校青年创新人才培养计划（LR-356214）；黑龙江省博士后基金（LBH-Z13022）；哈尔滨市科技局产业化重点项目（2014DB6AN026）；国家自然科学基金资助项目（51405078） |
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| 摘 要： | 为使立体苗盘管理机器人的机械臂能够在植物工厂狭窄的作业环境下,灵活、高效地完成目标工作空间的所有搬运和喷洒动作任务需求,同时尽量减小机械臂的操纵空间和结构尺寸,采用理论与试验相结合的方法对机械臂参数进行了优化设计。首先采用D-H法建立了机器人的运动学模型,然后通过工作空间分析确定出优化参数的工作空间约束条件。在此基础上,以"距离最短"和"结构紧凑"为性能指标建立目标优化函数,并利用遗传算法求解出最优的大臂杆长648 mm、中臂杆长472 mm和小臂杆长396 mm,最优机械臂关节转角极限值为96°、68°和126°。最后进行机器人样机的搬运和喷洒运动规划试验,并借助高速摄像系统标记机械臂末端运动轨迹坐标。试验结果表明:优化后的机械臂能够到达目标工作空间的所有极限位置及其他特征位置点,最大绝对定位误差为9.8 mm,最大相对定位误差为0.98%,在允许的误差范围内,能够满足机械臂工作空间对目标工作空间的有效包容。
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| 关 键 词： | 机械臂 优化 试验 工作空间 植物工厂 遗传算法 高速摄像 |
| 收稿时间： | 2016/8/23 0:00:00 |
| 修稿时间： | 2017/3/17 0:00:00 |
Parameter optimization and experiment of manipulator for three-dimensional seedling tray management robot |
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| Quan Longzhe,Peng Tao,Shen Liuyang,An Siyu,Ji Zhongliang and Sun Tao.Parameter optimization and experiment of manipulator for three-dimensional seedling tray management robot[J].Transactions of the Chinese Society of Agricultural Engineering,2017,33(7):10-19. |
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| Authors: | Quan Longzhe Peng Tao Shen Liuyang An Siyu Ji Zhongliang and Sun Tao |
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| Institution: | 1. College of Engineering, Northeast Agricultural University, Harbin 150030, China;,2. State Key Laboratory of Robotics and System, Harbin Institute of Technology, Harbin 150080, China;,1. College of Engineering, Northeast Agricultural University, Harbin 150030, China;,3. Hippocampus Car Co., Ltd, Zhengzhou 450016, China;,4. Changan Automobile Co., Ltd, Chongqing 404100, China; and 1. College of Engineering, Northeast Agricultural University, Harbin 150030, China; |
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| Abstract: | With the rapid development of modern agricultural technology, plant factory has become the most advanced development stage of facility agricultural. At present, the majority of work tasks in plant factory completed by manpower are labor-intensive and low efficient, therefore, the agricultural intelligent equipment system has become a hot spot in the development of plant factory. In view of the task demand of the carrying and spraying of the three-dimesional seedling tray, the three-dimesional seedling tray management robot was developed. In order to make the manipulator of three-dimesional seedling tray management robot complete all carrying and spraying tasks flexibly and efficiently, meanwhile to reduce operating space and structure size of manipulator, parameters of the manipulator were optimized by the method of theory and experiment. Firstly, in order to determine the relationship between the end coordinate of the manipulator's connecting rod and the base coordinate system, the kinematic model of the robot system was established by D-H method, which was important theoretical basis for the workspace analysis. Then the workspace of manipulator was constructed by graphic method, and the workspace constraint conditions were determined according to the condition that manipulator workspace accommodated target workspace. Based on that, the objective function was established according to shortest distance and compact structure, and genetic algorithm was used to solve the objective function. The optimal rod lengths (big arm, medium arm, small arm) of the manipulator were 648, 472, and 396 mm, and the limit values of the optimal joint angle were96°, 68°,and126°.The workspace and the target workspace of the robot were depicted in the MATLAB (Matrix Laboratory) software platform according to the optimal solution of the manipulator parameters, the kinematics equation of the robot and the range of the manipulator's parameters. The simulation result showed that the target workspace was between the inner limiting envelope interfaceand the outer limiting envelope interface of the manipulator, which verified the manipulator's ability to cover the target workspace, and the rationality of the theoretical optimization for the parameters of the manipulator was proved. Finally, in order to further validate whether the manipulator could complete all the action tasks of the target workspace, the robot prototype and the three-dimesional seedling tray experimental platform were built in the laboratory, and the motion planning test of carrying and spraying of the robot system prototype was carried out. The carrying test was planned as follows: According to the target workspace size and the theoretical position coordinate value, the manipulator was controlled to move vertically upward from the lowermost (lower limit) to the topmost (upper limit) of the target workspace, this group of actions were repeated 100 times, and seedling tray was always placed horizontally during carrying. The carrying test mainly verified the manipulator's ability to cover the target workspace in the vertical direction. Spraying test steps were as follows: 1) The initial spraying height value was 100 mm; 2) Divide the seedling disk plane intom×n grids, and each grid point represented the spray position point,m=10,n=20; 3) The target path point group consisted of all the spray points at the current height, and the manipulator was controlled to pass through the target path point group sequentially; 4) The spraying height valuewas increased by 20 mm; 5) Repeat step 2), 3) and 4) until the spraying height value was equal to 1020 mm. The spraying test mainly verified the manipulator's ability to cover the target workspace in the horizontal direction. The high-speed video camera system was used to mark trajectory coordinates of manipulator in the motion planning test of carrying and spraying (high-speed camera was KODAK's color CCD (charge coupled devices) camera, a resolution of 512×480 pixels, frame rate of 125 frames/s). Test results showed that the optimized manipulator could reach all limiting positions and other characteristic positions of target workspace, and the maximum relative positioning error was 0.98% which was within error range and could meet the accuracy requirements for manipulator containing the target workspace effectively; what was more, it was proved that the optimal parameters of manipulator were reasonable. Parameters optimization and experiment of three-dimesional seedling tray management robot could provide the reference for trajectory planning and motion control. |
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| Keywords: | manipulators optimization experiments workspace plant factory genetic algorithm high-speed camera |
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