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首页> 外文期刊>Mechanism and Machine Theory: Dynamics of Machine Systems Gears and Power Trandmissions Robots and Manipulator Systems Computer-Aided Design Methods >Full-mobility 3-(C)under-barCC parallel-kinematics machines: Forward kinematics, singularity, workspace and dexterity analyses
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Full-mobility 3-(C)under-barCC parallel-kinematics machines: Forward kinematics, singularity, workspace and dexterity analyses

机译:全移动3-(c)Barcc Parallic-Kinematics机器:前进运动,奇点,工作区和灵活分析

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摘要

The 3-(C) under bar CC class of parallel-kinematics machines (PKMs) bears many interesting features, as found in a previous paper on its optimum design. In this paper, its forward-kinematics (FK), singularity, workspace and dexterity analyses are studied. FK reveals that the rotation and translation of the moving platform (MP) are decoupled at the displacement level; moreover, a simple formulation is derived for the orientation subproblem that admits up to eight solutions, which is minimal; a quartic resolvent polynomial for the FK is then derived. All solutions thus can be found simultaneously in closed-form, while the computational cost is reduced; this brings robustness, especially when the robot operates near a singular configuration. Next, the translation problem is solved from a linear-equation system. These features, rare in six-dof PKMs, greatly simplify its simulation and control. Next, the singularity in question is shown to be determined solely by the orientation of the MP, thereby simplifying dramatically its evaluation and representation. Furthermore, the robot is shown to bear position and orientation workspaces of reasonable size, together with high dexterity. These features make the proposed PKM class quite promising in a variety of applications. (C) 2018 Elsevier Ltd. All rights reserved.
机译:3-(c)在Bar CC类平行 - 运动学机器(PKMS)下具有许多有趣的功能,如前一个关于其最佳设计的纸张中发现。本文研究了其前瞻性运动(FK),奇点,工作区和灵活分析。 FK揭示了移动平台(MP)的旋转和翻译在位移水平下耦合;此外,导出了一种简单的配方,用于方向子问题,该方向占八种解决方案,这是最小的;然后衍生出FK的四静脉分辨率多项式。因此,所有解决方案都可以在闭合形式同时发现,而计算成本降低;这带来了鲁棒性,特别是当机器人在奇异配置附近运行时。接下来,从线性方程系统解决翻译问题。这些特征,罕见的六分行PKMS,大大简化了其仿真和控制。接下来,示出了所讨论的奇点,仅通过MP的取向来确定,从而显着地简化了其评估和表示。此外,机器人被示出为承受合理尺寸的位置和取向工作区,以及高灵敏度。这些功能使提议的PKM类在各种应用中具有非常有前途的。 (c)2018年elestvier有限公司保留所有权利。

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