机器人柔性抓取试验平台的设计与抓持力跟踪阻抗控制
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摘要
为减小机器人在采摘过程中对果蔬的损伤,设计了机器人柔性抓取试验平台,提出了一种适合末端执行器双指抓取果蔬的抓持力跟踪阻抗控制算法,该算法将末端执行器抓持果蔬系统等效为阻抗-导纳模型,使手指力/位控制等效为期望的惯量-阻尼-刚度模型,可按需调节其参数实现抓持力与位置的动态关系。期望抓持力与采集果蔬实际接触力的偏差作为外环力阻抗控制器的输入,控制器生成对内部位置环参考轨迹的校正量。该算法仅考虑沿末端执行器双指夹持果蔬方向,避免了使用多自由度机械臂阻抗控制算法的复杂性,提高了控制的实时性,同时对抓取系统模型的不确定和力扰动具有较强的鲁棒性。机器人抓取试验证明了双指抓持力反馈阻抗柔顺控制算法的有效性,可实现机器人柔性抓取,减小抓取果蔬损伤和保证品质。该研究可为农业机器人无损抓取和采摘提供关键技术。
One of the major challenges of agricultural robots is the grasping and picking fresh fruit and vegetable without any damage under the complex environment. In order to minimize the harm due to robot grasp, this paper mainly introduces a dexterous multisensory gripper design and also develops a new force impedance control algorithm. First, the gripper with dual motor drive was designed, and each of fingers had an independent servo drive system and was integrated with force and tactile sensors. The calibration force sensors were mounted at the root of each finger, and the force signals were obtained by the force sensors. The expected force, position and speed parameters of the fingers can be set separately, so the grip centre and stroke can be controlled for the finger by pre-programming, the movement and forces of grasped objects can be actively controlled to achieve through the two-finger operations. The gripper with both the mechanical mechanism and control flexibility was mounted in the end of the industrial robot. The grasping experiment platform composed of industrial robot and dexterous gripper integrated monocular vision, force sensing and many kinds of sensors. The 2-D vision was able to quickly detect and locate grasped objects at the top of the experiment platform. Second, a force impedance control algorithm was proposed and used for one of fingers, position control was used for another finger, and it can regulate the grasping force by defining the target impedance between desired position and contact force. The whole grasping system can be equivalent to impedance & admittance model, and the finger force/position control can be equivalent to the expected target inertia-damping-stiffness model, and the model parameters can be adjustable according to the needs to realize the dynamic relationship between grasping force and position. The contact force errors between expected force value and actual force acquired from the force sensor were as the input of impedance controller and its output can be realized by the reference trajectory correction to the internal position control loop. The proposed algorithm only considered the direction of gripping fruit and vegetable, and the reference trajectory can be determined simply, and then avoids the use of complicated impedance control for multi-degree of freedom manipulators, through which it can improve the real-time control and robustness of the grasping system with model uncertainty or external force disturbance. Robot grasping experiments show that the system runs smoothly and reliably, the force-feedback impedance control is very effective, and the steady state error is maximum range within ± 0.4N in the experiment of grasping the tomatoes and eggs. It can make force track value with small force overshot and fast response simultaneously between the end-effector and fruit and vegetable, so it makes the force controller adaptive to the dynamic grasp process between the end-effector and fruit and vegetable, it can realize the flexible grasping and reduce damages and ensure the quality of the grasped fruit and vegetable. The research provides a key control technology for the compliant grasping of fruit and vegetable.
One of the major challenges of agricultural robots is the grasping and picking fresh fruit and vegetable without any damage under the complex environment. In order to minimize the harm due to robot grasp, this paper mainly introduces a dexterous multisensory gripper design and also develops a new force impedance control algorithm. First, the gripper with dual motor drive was designed, and each of fingers had an independent servo drive system and was integrated with force and tactile sensors. The calibration force sensors were mounted at the root of each finger, and the force signals were obtained by the force sensors. The expected force, position and speed parameters of the fingers can be set separately, so the grip centre and stroke can be controlled for the finger by pre-programming, the movement and forces of grasped objects can be actively controlled to achieve through the two-finger operations. The gripper with both the mechanical mechanism and control flexibility was mounted in the end of the industrial robot. The grasping experiment platform composed of industrial robot and dexterous gripper integrated monocular vision, force sensing and many kinds of sensors. The 2-D vision was able to quickly detect and locate grasped objects at the top of the experiment platform. Second, a force impedance control algorithm was proposed and used for one of fingers, position control was used for another finger, and it can regulate the grasping force by defining the target impedance between desired position and contact force. The whole grasping system can be equivalent to impedance & admittance model, and the finger force/position control can be equivalent to the expected target inertia-damping-stiffness model, and the model parameters can be adjustable according to the needs to realize the dynamic relationship between grasping force and position. The contact force errors between expected force value and actual force acquired from the force sensor were as the input of impedance controller and its output can be realized by the reference trajectory correction to the internal position control loop. The proposed algorithm only considered the direction of gripping fruit and vegetable, and the reference trajectory can be determined simply, and then avoids the use of complicated impedance control for multi-degree of freedom manipulators, through which it can improve the real-time control and robustness of the grasping system with model uncertainty or external force disturbance. Robot grasping experiments show that the system runs smoothly and reliably, the force-feedback impedance control is very effective, and the steady state error is maximum range within ± 0.4N in the experiment of grasping the tomatoes and eggs. It can make force track value with small force overshot and fast response simultaneously between the end-effector and fruit and vegetable, so it makes the force controller adaptive to the dynamic grasp process between the end-effector and fruit and vegetable, it can realize the flexible grasping and reduce damages and ensure the quality of the grasped fruit and vegetable. The research provides a key control technology for the compliant grasping of fruit and vegetable.
引文
[1]刘继展,白欣欣,李萍萍,等.果实快速夹持复合碰撞模型研究[J].农业机械学报,2014,45(4):49-54.Liu Jizhan,Bai Xinxin,Li Pingping.Complex collision model in high-speed gripping of fruit[J].Transactions of the Chinese Society for Agricultural Machinery,2014,45(4):49-54.(in Chinese with English abstract)
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[3]王学林,姬长英,周俊,等.基于灰色预测控制的果蔬抓取系统设计与试验[J].农业工程学报,2010,26(3):112-117.Wang Xuelin,Ji Changying,Zhou Jun,et al.Design and experiment of fruit and vegetable grasping system based on grey prediction control[J].Transactions of the Chinese Society of Agricultural Engineering(Transactions of the CSAE),2010,26(3):112-117.(in Chinese with English abstract)
[4]周俊,杨肖蓉,朱树平.基于自适应神经模糊网络的果蔬抓取力控制[J].农业机械学报,2014,45(7):67-72.Zhou Jun,Yang Xiaorong,Zhu Shuping.Griping force control using adaptive neuro-fuzzy inference systems[J].Transactions of the Chinese Society for Agricultural Machinery,2014,45(7):67-72.(in Chinese with English abstract)
[5]Li Zhi Guo,Liu JiZ han,Li PingP ing.Study on the collision-mechanical properties of tomatoes gripped by harvesting robot fingers[J].African Journal of Biotechnology,2009,8(24):7000-7007.
[6]鲍官军,张水波,陈亮,等.基于气动柔性驱动器的球果采摘末端抓持器[J].农业机械学报,2013,44(5):242-246.Bao Guanjun,Zhang Shuibo,Chen Liang,et al.Design of spherical fruit end-grasper based on FPA[J].Transactions of the Chinese Society for Agricultural Machinery,2013,45(5):242-246.(in Chinese with English abstract)
[7]Shuichi W,Koichi S,Keiko O.Miniature pneumatic curling rubber actuator generating bidirectional motion with one air-supply tube[J].Advanced Robotics,2011,25(9/10):1311-1330.
[8]Morris D M,Hebbar R,Newman W S.Force guided assemblies using a novel parallel manipulator[C]//Robotics and Automation,2001.Proceedings 2001 ICRA.IEEE International Conference on,2011:325-330.
[9]Rabenorosoa K,Clévy C,Lutz P.Active force control for robotic micro-assembly:Application to guiding tasks[C]//Robotics and Automation 2010 IEEE International Conference on.IEEE,2010:2137-2142.
[10]Huang S,Liu Yuchi,Hsiang S.Robotic end-effector impedance control without expensive torque/force sensor[J].World Academy of Science,Engineering and Technology,International Journal of Mechanical,Aerospace,Industrial and Mechatronics Engineering,2013,7(7):516-523.
[11]Hogan N.Impedance control:An approach to manipulator:Part I-III[J].Transactions of American Society of Mechanical Engineers,Journal of Dynamic System,Measure Control,1985,107(1):1-24.
[12]杨振.机器人阻抗控制算法的参数调整研究[J].枣庄学院学报,2008,25(2):89-93.Yang Zhen.An research on the adjustment of parameters of robot based on the impedance control[J].Journal of Zaozhuang Univerisity,2008,25(2):89-93.(in Chinese with English abstract)
[13]Fan Xinjian,Wang Xuelin,Xiao Yongfei.A combined2D-3D vision system for automatic robot picking[C]//Proceedings of the 2014 International Conference on Advanced Mechatronic Systems,Kumamoto,Japan,2014:513-516.
[2]姬伟,罗大伟,李俊乐,等.果蔬采摘机器人末端执行器的柔顺抓取力控制[J].农业工程学报,2014,30(9):19-26.Ji Wei,Luo Dawei,Li Junle,et al.Compliance grasp force control for end-effector of fruit-vegetable picking robot[J].Transactions of the Chinese Society of Agricultural Engineering(Transactions of the CSAE),2014,30(9):19-26.(in Chinese with English abstract)
[3]王学林,姬长英,周俊,等.基于灰色预测控制的果蔬抓取系统设计与试验[J].农业工程学报,2010,26(3):112-117.Wang Xuelin,Ji Changying,Zhou Jun,et al.Design and experiment of fruit and vegetable grasping system based on grey prediction control[J].Transactions of the Chinese Society of Agricultural Engineering(Transactions of the CSAE),2010,26(3):112-117.(in Chinese with English abstract)
[4]周俊,杨肖蓉,朱树平.基于自适应神经模糊网络的果蔬抓取力控制[J].农业机械学报,2014,45(7):67-72.Zhou Jun,Yang Xiaorong,Zhu Shuping.Griping force control using adaptive neuro-fuzzy inference systems[J].Transactions of the Chinese Society for Agricultural Machinery,2014,45(7):67-72.(in Chinese with English abstract)
[5]Li Zhi Guo,Liu JiZ han,Li PingP ing.Study on the collision-mechanical properties of tomatoes gripped by harvesting robot fingers[J].African Journal of Biotechnology,2009,8(24):7000-7007.
[6]鲍官军,张水波,陈亮,等.基于气动柔性驱动器的球果采摘末端抓持器[J].农业机械学报,2013,44(5):242-246.Bao Guanjun,Zhang Shuibo,Chen Liang,et al.Design of spherical fruit end-grasper based on FPA[J].Transactions of the Chinese Society for Agricultural Machinery,2013,45(5):242-246.(in Chinese with English abstract)
[7]Shuichi W,Koichi S,Keiko O.Miniature pneumatic curling rubber actuator generating bidirectional motion with one air-supply tube[J].Advanced Robotics,2011,25(9/10):1311-1330.
[8]Morris D M,Hebbar R,Newman W S.Force guided assemblies using a novel parallel manipulator[C]//Robotics and Automation,2001.Proceedings 2001 ICRA.IEEE International Conference on,2011:325-330.
[9]Rabenorosoa K,Clévy C,Lutz P.Active force control for robotic micro-assembly:Application to guiding tasks[C]//Robotics and Automation 2010 IEEE International Conference on.IEEE,2010:2137-2142.
[10]Huang S,Liu Yuchi,Hsiang S.Robotic end-effector impedance control without expensive torque/force sensor[J].World Academy of Science,Engineering and Technology,International Journal of Mechanical,Aerospace,Industrial and Mechatronics Engineering,2013,7(7):516-523.
[11]Hogan N.Impedance control:An approach to manipulator:Part I-III[J].Transactions of American Society of Mechanical Engineers,Journal of Dynamic System,Measure Control,1985,107(1):1-24.
[12]杨振.机器人阻抗控制算法的参数调整研究[J].枣庄学院学报,2008,25(2):89-93.Yang Zhen.An research on the adjustment of parameters of robot based on the impedance control[J].Journal of Zaozhuang Univerisity,2008,25(2):89-93.(in Chinese with English abstract)
[13]Fan Xinjian,Wang Xuelin,Xiao Yongfei.A combined2D-3D vision system for automatic robot picking[C]//Proceedings of the 2014 International Conference on Advanced Mechatronic Systems,Kumamoto,Japan,2014:513-516.