• Title/Summary/Keyword: PTP motion

Search Result 8, Processing Time 0.033 seconds

Implementation of LabVIEW®-based Joint-Linear Motion Blending on a Lab-manufactured 6-Axis Articulated Robot (RS2) (LabVIEW® 기반 6축 수직 다관절 로봇(RS2)의 이종 모션 블랜딩 연구)

  • Lee, D.S.;Chung, W.J.;Jang, J.H.;Kim, M.S.
    • Journal of the Korean Society of Manufacturing Technology Engineers
    • /
    • v.22 no.2
    • /
    • pp.318-323
    • /
    • 2013
  • For fast and accurate motion of 6-axis articulated robot, more noble motion control strategy is needed. In general, the movement strategy of industrial robots can be divided into two kinds, PTP (Point to Point) and CP (Continuous Path). Recently, industrial robots which should be co-worked with machine tools are increasingly needed for performing various jobs, as well as simple handling or welding. Therefore, in order to cope with high-speed handling of the cooperation of industrial robots with machine tools or other devices, CP should be implemented so as to reduce vibration and noise, as well as decreasing operation time. This paper will realize CP motion (especially joint-linear) blending in 3-dimensional space for a 6-axis articulated (lab-manufactured) robot (called as "RS2") by using LabVIEW$^{(R)}$ (6) programming, based on a parametric interpolation. Another small contribution of this paper is the proposal of motion blending simulation technique based on Recurdyn$^{(R)}$ V7 and Solidworks$^{(R)}$, in order to figure out whether the joint-linear blending motion can generate the stable motion of robot in the sense of velocity magnitude at the end-effector of robot or not. In order to evaluate the performance of joint-linear motion blending, simple PTP (i.e., linear-linear) is also physically implemented on RS2. The implementation results of joint-linear motion blending and PTP are compared in terms of vibration magnitude and travel time by using the vibration testing equipment of Medallion of Zonic$^{(R)}$. It can be confirmed verified that the vibration peak of joint-linear motion blending has been reduced to 1/10, compared to that of PTP.

A Study on the PTP Motion of Robot Manipulators by Neural Networks (신경 회로망에 의한 로보트 매니퓰레이터의 PTP 운동에 관한 연구)

  • Kyung, Kye-Hyun;Ko, Myoung-Sam;Lee, Bum-Hee
    • Proceedings of the KIEE Conference
    • /
    • 1989.07a
    • /
    • pp.679-684
    • /
    • 1989
  • In this paper, we describe the PTP notion of robot manipulators by neural networks. The PTP motion requires the inverse kinematic redline and the joint trajectory generation algorithm. We use the multi-layered Perceptron neural networks and the Error Back Propagation(EBP) learning rule for inverse kinematic problems. Varying the number of hidden layers and the neurons of each hidden layer, we investigate the performance of the neural networks. Increasing the number of learning sweeps, we also discuss the performance of the neural networks. We propose a method for solving the inverse kinematic problems by adding the error compensation neural networks(ECNN). And, we implement the neural networks proposed by Grossberg et al. for automatic trajectory generation and discuss the problems in detail. Applying the neural networks to the current trajectory generation problems, we can refute the computation time for trajectory generation.

  • PDF

Hybrid Motion Blending Algorithm of 3-Axis SCARA Robot based on $Labview^{(R)}$ using Parametric Interpolation (매개변수를 이용한 $Labview^{(R)}$ 기반의 3축 SCARA로봇의 이종모션 제어 알고리즘)

  • Chung, Won-Jee;Ju, Ji-Hun;Lee, Kee-Sang
    • Transactions of the Korean Society of Machine Tool Engineers
    • /
    • v.18 no.2
    • /
    • pp.154-161
    • /
    • 2009
  • In order to implement continuous-path motion on a robot, it is necessary to blend one joint motion to another joint motion near a via point in a trapezoidal form of joint velocity. First, the velocity superposition using parametric interpolation is proposed. Hybrid motion blending is defined as the blending of different two type's motions such as blending of joint motion with linear motion, in the neighborhood of a via point. Second, hybrid motion blending algorithm is proposed based on velocity superposition using parametric interpolation. By using a 3-axis SCARA (Selective Compliance Assembly Robot Arm) robot with $LabVIEW^{(R)}$ $controller^{(1)}$, the velocity superposition algorithm using parametric interpolation is shown to result in less vibration, compared with PTP(Point- To-Point) motion and Kim's algorithm. Moreover, the hybrid motion $algorithm^{(2)}$ is implemented on the robot using $LabVIEW^{(R)(1)}$ programming, which is confirmed by showing the end-effector path of joint-linear hybrid motion.

Position Control of a Redundant Flexible Manipulator (여유자유도 유연 매니퓰레이터의 위치제어)

  • 김진수
    • Transactions of the Korean Society of Machine Tool Engineers
    • /
    • v.10 no.3
    • /
    • pp.83-89
    • /
    • 2001
  • In this paper, we discuss the vibration suppression control of spatial redundant flexible manipulators through pseudo-inversed of Jacobian. In order to verify our method, the experiments are performed for PTP(Point To Point) motion of spa-tial flexible manipulators(1) with no redundancy(2) with one redundant DOF(degree of freedom). Finally, a comparison between these results is presented to show the performance of out approach.

  • PDF

A study on kinematics and dynamics of robot arms by simulation (로봇 팔의 운동해석에 관한 연구)

  • 조선휘;김영일;임태홍
    • Transactions of the Korean Society of Mechanical Engineers
    • /
    • v.10 no.5
    • /
    • pp.611-617
    • /
    • 1986
  • In this paper, it is attempted to derive the minimum torque as the optimal value on each joint, which is applied during a PTP-motion in the range of working area of a supposed industrial robot. The rupposed industrial robot consits of 3-R joints prepared on three links, The optimizational analysis is performed by the formulation of a variational calculus process due to Rayleigh-Ritz method. That is, the torques of the inverse dynamic problem on joints in a arbitrary positions are computed by a generalized inertia matrix method.