首页> 外文会议>8th Biennial Conference on Engineering Systems Design and Analysis 2006 vol.1 >A GENETIC ALGORITHM AS SUPPORT IN THE MOVEMENT OPTIMISATION OF A REDUNDANT SERIAL ROBOT
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A GENETIC ALGORITHM AS SUPPORT IN THE MOVEMENT OPTIMISATION OF A REDUNDANT SERIAL ROBOT

机译:遗传算法在冗余串行机器人运动优化中的支持

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The paper illustrates the application of a genetic algorithm as a methodology to choose and improve the motion law governing the movement of a redundant robot. The subject of this research is an innovative system developed to introduce the laser ray technology in the on-line tube cutting. This technique allows a quality improvement in the pipe-cutting sector, thanks to the various goals. Firstly we underline the improvement of the working environment due to the elimination of cutting noise taking off the tool changing and the steel shaving creation. Secondarily there is a drastic reduction of the cutting cycle time and an improvement of the productivity accomplished by the use of brushless drives and linear motors.rnIn the robot design, particular attention was dedicated to the masses distributions allowing a good natural machine dynamics.rnThe ability of the robot to avoid the cutting object, the demand to maintain the laser torch orthogonal to the cutting surfaces, as well the necessity to impose a velocity behaviour as constant as possible during the cutting operation, suggested the introduction of a redundant degree of freedom. This aspect gives a lot of opportunities in the choose of movements because there are thousands motion profiles for the joints whichever satisfying the conditions imposed to the end-effector path.rnIn this context, we have proposed the idea to combine the procedure to solve the inverse kinematics problem with the contemporaneous optimization of the trajectory.rnLiterature offers a series of algorithms to solve well-known inverse kinematics problem of redundant robot. These are based on the inversion of the matrix representing the link between the end-effector co-ordinates and the joints. The presence of redundancy makes this matrix rectangular andrnrequires the use of the pseudo-inverse matrix to solve the problem in several points of the trajectory. The introduction of some weights, one for each joint co-ordinate, allows to obtain a different distribution of the joint movements computing the pseudo-inverse matrix. If we change these weights in a continuous way in time domain, we can supervise the dynamic behaviors of the machine.rnThe new idea we propose here is the use of an adapted multi-objective genetic algorithm to define a several of particular motion laws reducing vibrations and realizing "special harmonies" in the robot motion. The procedure, that will be completely discussed in the full paper, is actually working on a laser pipe cutting machine.rnThis robot awarded the first prize between two thousand competitor at the EMO MILANO 2003 exhibition.
机译:本文说明了遗传算法作为选择和改进支配冗余机器人运动的运动定律的方法的应用。本研究的主题是一种创新的系统,旨在将激光技术引入在线管切割中。由于各种目标,该技术可提高切管行业的质量。首先,我们强调由于消除了切削噪音,消除了换刀和刮削产生的噪音,从而改善了工作环境。其次,通过使用无刷驱动器和线性电动机,可大大减少切割周期时间并提高生产率.rn在机器人设计中,特别注意质量分布,从而实现了良好的自然机械动力学。为了避免切割对象的机器人的出现,要求保持激光割炬与切割表面正交,以及在切割操作期间必须使速度行为尽可能恒定的要求,建议引入冗余的自由度。这方面为运动的选择提供了很多机会,因为关节有成千上万的运动曲线,而这些运动曲线都满足了施加到末端执行器路径上的条件。在这种情况下,我们提出了一种将过程结合起来以求逆的想法。同时优化轨迹的运动学问题。rnLiterature提供了一系列算法来解决众所周知的冗余机器人逆运动学问题。这些基于表示终端执行器坐标和关节之间的链接的矩阵的求逆。冗余的存在使该矩阵变为矩形,并且需要使用伪逆矩阵来解决轨迹的多个点中的问题。引入一些权重(每个关节坐标对应一个权重)允许获得计算伪逆矩阵的关节运动的不同分布。如果我们在时域中以连续的方式更改这些权重,则可以监督机器的动态行为。rn我们在此提出的新想法是使用自适应的多目标遗传算法来定义一些减少振动的特定运动定律。并实现了机器人运动中的“特殊和谐”。该过程将在全文中进行完全讨论,实际上是在激光切割机上进行的。该机器人在2003年EMO MILANO展览会上获得了2000名竞争对手的一等奖。

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