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High-performance robotic contour tracking based on the dynamic compensation concept

机译:基于动态补偿概念的高性能机器人轮廓跟踪

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This paper focuses on high-performance robotic contour tracking under the uncertainties that commonly exist in actual robotic applications. These uncertainties can be attributed to the robot itself (such as modeling errors or mechanical defects like backlash) or to environmental issues (such as calibration errors or misalignment of the workpiece). We propose a non-model-based dynamic compensation approach based on the coarse-to-fine philosophy, which enables contour tracking with both high speed and good accuracy. This is achieved by adopting a methodology in which a main robot performs fast but coarse motion, while an add-on module conducts accurate compensation for the overall uncertainties using a high-speed camera and high-speed compensation actuator. An algorithm called pre-compensated proportionalderivative sliding mode control (pre-compensated PD-SMC) is proposed to control the compensation actuator. The effectiveness of the proposed contour tracking approach and control algorithm are experimentally verified using two typical planar-contour shapes: a random smooth-curvature and rectangle.
机译:本文重点介绍在实际机器人应用中通常存在的不确定性下的高性能机器人轮廓跟踪。这些不确定性可归因于机器人本身(例如建模错误或机械缺陷(例如反冲))或环境问题(例如校准错误或工件未对准)。我们提出了一种基于粗到精原理的非基于模型的动态补偿方法,该方法可以实现高速,高精度的轮廓跟踪。这是通过采用以下方法实现的:主机器人执行快速但粗略的运动,而附加模块使用高速摄像机和高速补偿执行器对整体不确定性进行精确补偿。提出了一种称为预补偿比例微分滑模控制的算法(预补偿PD-SMC)来控制补偿执行器。使用两种典型的平面轮廓形状:随机平滑曲率和矩形,通过实验验证了所提出的轮廓跟踪方法和控制算法的有效性。

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