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A tolerance constrained G2 continuous path smoothing and interpolation method for industrial SCARA robots

机译:工业SCARA机器人的公差约束G2连续路径平滑和插补方法。

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摘要

Piecewise-linear robot paths lack G~1 and G~2 continuity. The discontinuity results in feedrate reduction and fluctuation during real-time execution. State-of-art linear path smoothing methods have issues such as lack of data or chord tolerance constraints, numerical instability, and lack of synchronized position and orientation parameterization. This study proposes a robot path smoothing method for SCARA (Selective Compliance Assembly Robot Arm) robots. The smoothing method simultaneously satisfies requirements of G~2 continuity, tolerance constraints (target point interpolation and chord tolerance constrained), shape-preserving (free of self-intersection), unified parameterization, and real-time performance. A global geometric iteration method combined with local corner transition scheme is used to generate smooth path. A convex combination presentation is proposed to simplify the formulation, which also makes it possible to unify various smoothing schemes into one extensible framework. Simulations with data analysis and actual experiments are performed for the verification of quality and efficiency. Comparisons with other solutions are included to evaluate the advantages of the proposed robot path smoothing method.
机译:分段线性机器人路径缺少G〜1和G〜2连续性。不连续性导致实时执行期间进给率降低和波动。现有技术的线性路径平滑方法存在诸如缺少数据或弦公差约束,数值不稳定以及缺乏同步的位置和方向参数化的问题。这项研究提出了一种用于SCARA(选择性依从性装配机器人手臂)机器人的机器人路径平滑方法。平滑方法同时满足G〜2连续性,公差约束(目标点插值和弦公差受约束),形状保持(无自交),统一参数化和实时性能的要求。结合局部转角过渡方案的全局几何迭代方法生成平滑路径。提出了一种凸组合表示法来简化公式,这也使得将各种平滑方案统一到一个可扩展框架中成为可能。通过数据分析和实际实验进行仿真,以验证质量和效率。包括与其他解决方案的比较,以评估所提出的机器人路径平滑方法的优势。

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