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柔性机器人臂协调操作的协调性 总被引:1,自引:0,他引:1
针对具有柔性臂和柔性关节的机器人协调操作刚性负荷,由载荷分配法分配载荷,以物体实际的质心位置为边界条件并且等于期望的轨迹,建立了具有柔性臂和柔性关节的机器人臂协调操作的逆动力学模型。这种基于绝对坐标的逆动力学模型可使各协调机器人保持很好的协调,并且较准确地实现期望轨迹。通过与通常的方法相比,分析了影响机器人协调操作的协调性的因素,实例验证了有效性。 相似文献
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为了简单、准确的实现对柔性连杆机器人慢子系统的控制,应用了神经模糊动态逆自适应控制原理及其控制器的设计方法,建立了柔性连杆机器人的动力学方程,给出了神经模糊系统的学习算法,并进行了系统的稳定性分析,解决了柔性连杆机器人的慢动力学及机器人慢子系统的逆自适应控制问题. 相似文献
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针对柔性臂机器人协调操作刚性负载这种情况,提出了一种无内力载荷分配法。将此方法和基于绝对坐标并以被操作物体质心的实际位置而不是名义刚性益为边界条件的递动力学模型相结合,可使协调机器人之间具有较小的内力。同时较准确地实现期望轨迹。对两个三柔性臂机器人协调操作刚性负载进行了仿真,验证了本方法的有效性。 相似文献
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为了研究柔性操作臂关节弹性对频率及振型的作用机理,建立了柔性操作臂的弹性约束模型。根据弹性约束模型,得到了弹性关节柔性操作臂的频率方程及振型函数。采用数值方法,对弹性关节柔性操作臂的前三阶频率及振型特性进行了分析。结果表明:关节的弹性对柔性操作臂的频率及振型具有明显的影响,将关节视为理想刚性约束会产生明显的误差;由灵敏度分析可知,线性约束对频率的影响大于扭转约束,且高阶频率段表现较为明显;扭转约束对振型的影响比线性约束更为显著,随着扭转约束的增大,振型发生改变,且高阶振型表现较为明显。通过实验对建立的弹性约束模型进行验证,实验结果表明,所建立的弹性约束模型能够合理地表征关节的弹性约束作用,分析结果更接近实际情况,误差较小。 相似文献
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针对存在参数不确定和外界干扰的柔性臂杆、柔性关节空间机械臂追踪期望运动的问题,设计了基于TS模糊模型的滑模鲁棒控制方案和双柔性振动并行控制方案。首先,设计了关节柔性补偿器以提高系统的等效关节刚度。其次,利用反馈线性化技术建立了系统追踪期望轨迹的误差动力学方程,通过对系统Lyapunov稳定性证明来选择滑模控制参数;简化并改进TS模糊推理规则,提出了模糊滑模鲁棒控制方法,可解决滑模控制的抖振问题并具有计算量少、控制力矩小的优点。再次,提出了柔性臂杆振动模态的直接反馈控制方案,解决了双柔性并行综合控制的问题。最后,运用逐步仿真的方法,对比仿真结果,证实了所设计轨迹跟踪、双柔性并行综合控制方案的有效性和稳定性。 相似文献
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This paper presents the forward and inverse displacement analysis of a quadruped robot MANA as a parallel manipulator in quadruple stance phase, which is used to obtain the workspace and control the motion of the body. The robot MANA designed on the basis of the structure of quadruped mammal is able to not only walk and turn in the uneven terrain, but also accomplish various manipulating tasks as a parallel manipulator in quadruple stance phase. The latter will be the focus of this paper, however. For this purpose, the leg kinematics is primarily analyzed, which lays the foundation on the gait planning in terms of locomotion and body kinematics analysis as a parallel manipulator. When all four feet of the robot contact on the ground, by assuming there is no slipping at the feet, each contacting point is treated as a passive spherical joint and the kinematic model of parallel manipulator is established. The method for choosing six non-redundant actuated joints for the parallel manipulator from all twelve optional joints is elaborated. The inverse and forward displacement analysis of the parallel manipulator is carried out using the method of coordinate transformation. Finally, based on the inverse and forward kinematic model, two issues on obtaining the reachable workspace of parallel manipulator and planning the motion of the body are implemented and verified by ADAMS simulation. 相似文献
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通过关节坐标的转换和旋转坐标系统的引入,给出了CRS机械手逆运动方程求解的一种新解析法,直接推导出各个关节转角变量的反三角公式,为机械手的运动优化和轨迹规划创造了条件.该算法避免大量的矩阵运算以及对计算结果取值范围的讨论,并且通过仿真分析证明了计算结果的正确性.除此之外,还通过真实的机械手验证了算法的优越性和合理性. 相似文献
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提出一种用于机器人臂的带有重力补偿的多项式PD型(PPD)学习控制器,基于多项式神经网络给出了这种控制器的比例系数连续学习算法,由非线性机器人动力学模型与所提出的学习控制器所组成的闭环系统被证明在满足李雅普诺夫直接法和拉萨尔不变集定理时是全局渐近稳定的,除了理论结果,也提供了在两自由度机器人臂位置控制中的仿真实验比较,结果表明PPD学习控制器在系统快速响应性方面优于常规PD控制器。PPD学习控制器为机器人控制系统提供了一种新的途径。 相似文献
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针对某大型激光器装置的装校过程模块化、阵列化及超洁净工作环境等特点,分析了洁净精密装校机器人的轨迹规划和智能化无人装校的实际需求,提出了“轨迹取点→单关节变化PTP口规划→初步轨迹拟合→基于时间和防料动轨迹优化”的轨迹规划思路和方法.根据该机器人结构特征,应用D-H法建立坐标系,完成了运动学正逆解分析.基于运动学位姿方程,按照机器人作业规划流程,完成了洁净精密装校机器人安装一个模块的轨迹规划和优化,并运用MATLAB 2008绘制了具体轨迹曲线.最后运用Pro/E 4.0进行了机构运动学仿真验证,验证表明洁净精密装校机器人在无人工干预及超洁净环境下可实现高洁净、高精密装校. 相似文献
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考虑到黄瓜采摘机械手结构参数的微小偏差可能会对末端定位精度造成较大的影响,因此,利用高精度三坐标测量仪P latinum FaroArm对机械手的结构参数进行了标定,建立了基于修正参数的正运动学模型,在此基础上对理想逆运动学进行误差分析,发现腰关节的角度误差远远大于位置编码器的精度。因此,提出采用LMBP神经网络算法求解修正后的关节角度,并将网络输出与理想逆运动学结合起来,达到补偿机械手定位精度的目的。为了验证算法的可行性,进行了仿真试验,结果表明:LMBP神经网络输出角度误差的最大值约为0.006 rad,能将末端位置误差从10.57mm补偿到3.77mm,大大提高了黄瓜采摘机械手的定位精度。 相似文献
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为解决电力系统绝缘子传统人工清扫中存在的危险性较大、费时费力、清扫效率低等问题,分析了绝缘子不同类型、不同半径、不同安装位置和安装角度对清扫的要求,提出了一种能够打破清扫角度局限性,实现360°全方位清扫的半自动清扫机械手设计方案.该方案通过清扫大臂的伸缩、毛刷的旋转和俯仰摆动,以及清扫手爪的开合调整,实现了各种类型绝缘子的清扫.研究结果表明,该清扫机械手可以很好地代替传统人工清扫,提高了清扫效率,保证了清扫质量,使清扫工作更安全. 相似文献
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柔性机器人的末端运动规划是机器人领域的重要前沿课题之一。利用冗余度机器人的自运动 ,可能使柔性机器人精度提高 ,但目前的研究大多是基于伪逆解的最优规划。本文首次在最小能量意义下对柔性冗余度机器人的最优规划进行了研究 ,以具有两冗余度的平面四柔性臂机器人为例进行了最优规划 ,通过与伪逆解方法比较 ,充分显示了最小能量法在柔性机器人最优规划中的重要作用。 相似文献
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Jeonghoon Yoo Myung Wook Hyun Jun Ho Choi Sungchul Kang Seung-Jong Kim 《Journal of Mechanical Science and Technology》2009,23(8):2236-2243
The response surface method combined with the design of experiment-based design optimization of a variable stiffness joint
(VSJ) is presented in this article. A VSJ used in a manipulator of a robot arm to support 1 kg payload at the end is designed
by considering the minimization of the total weight as the objective function. Owing to the requirement of large rotational
stiffness of the VSJ, over 10 N · m, ring-type permanent magnets are adopted. First, a model composed of two permanent magnets was initially manufactured and
tested for comparison with the analysis results. Then, a three-ring-type permanent magnet-based model is suggested and optimized
to increase the torque of VSJ. The finite element method is used as a magnetic field analysis method to substitute for the
expensive experimental process. Optimization results decrease the weight from 0.899 kg to 0.538 kg, still satisfying the requirement
for the rotational stiffness.
This paper was recommended for publication in revised form by Associate Editor Tae Hee Lee
Jeonghoon Yoo received his B.S. and M.S. degrees in Mechanical Design and Production Engineering from Seoul National University, in 1989
and 1991, respectively. He then received his Ph.D. degrees from the University of Michigan, Ann Arbor, in 1999. Dr. Yoo is
currently a Professor at the School of Mechanical Engineering at Yonsei University in Seoul, Korea. Dr. Yoo’s research interests
include analysis and design of electromagnetic field systems.
Myung Wook Hyun received his B.S. and M.S. degrees in Mechanical Engineering from Yonsei University, Korea, in 1995 and 1997, respectively.
While studying for his M.S. degree, Mr. Hyun also studied variable stiffness unit design. He is now working at Samsung Electronics,
Co. Ltd..
Jun Ho Choi received his B.S. and M.S. degrees in Mechanical Design from Hanyang University, Korea and his Ph.D. degree from the University
of Michigan, Ann Arbor. He is currently a senior research scientist in the Korea Institute of Science and Technology. His
research interests include nonlinear control, manipulator control, and safe-joint design.
Sungchul Kang received his B.S., M.S., and Ph.D. degrees in Mechanical Design and Production Engineering from Seoul National University,
Korea, in 1989, 1991, and 1998 respectively. Dr. Kang is currently a Principal Research Scientist in the Center for Cognitive
Robotics Research, Korea Institute of Science and Technology, in Seoul, Korea. Dr. Kang’s research interests include mobility
and manipulation of field and service robots and haptics.
Seung-Jong Kim received his B.S. degree in Mechanical Engineering from Seoul University, Korea, in 1989, and his M.S. and Ph.D. degrees
from KAIST in 1991 and 1998, respectively. Dr. Kim is currently a Principal Research Scientist at the Korea Institute of Science
and Technology in Seoul, Korea. Dr. Kim’s research interests include the design, control, and dynamic analysis of mechatronic
systems. 相似文献