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首页> 外文期刊>IEEE Transactions on Robotics >SCADE: Simultaneous Sensor Calibration and Deformation Estimation of FBG-Equipped Unmodeled Continuum Manipulators
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SCADE: Simultaneous Sensor Calibration and Deformation Estimation of FBG-Equipped Unmodeled Continuum Manipulators

机译:SCADE:FBG配备的未建模连续机械手同时进行传感器校准和变形估计

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摘要

In this article, we present a novel stochastic algorithm called simultaneous sensor calibration and deformation estimation (SCADE) to address the problem of modeling deformation behavior of a generic continuum manipulator (CM) in free and obstructed environments. In SCADE, using a novel mathematical formulation, we introduce a priori model-independent filtering algorithm to fuse the continuous and inaccurate measurements of an embedded sensor (e.g., magnetic or piezoelectric sensors) with an intermittent but accurate data of an external imaging system (e.g., optical trackers or cameras). The main motivation of this article is the crucial need of obtaining an accurate shape/position estimation of a CM utilized in a surgical intervention. In these robotic procedures, the CM is typically equipped with an embedded sensing unit (ESU) while an external imaging modality (e.g., ultrasound or a fluoroscopy machine) is also available in the surgical site. The results of two different set of prior experiments in free and obstructed environments were used to evaluate the efficacy of SCADE algorithm. The experiments were performed with a CM specifically designed for orthopaedic interventions equipped with an inaccurate Fiber Bragg Grating (FBG) ESU and overhead camera. The results demonstrated the successful performance of the SCADE algorithm in simultaneous estimation of unknown deformation behavior of the utilized unmodeled CM together with realizing the time-varying drift of the poor-calibrated FBG sensing unit. Moreover, the results showed the phenomenal out-performance of the SCADE algorithm in estimation of the CM's tip position as compared to FBG-based position estimations.
机译:在本文中,我们提出了一种新颖的随机算法,称为同时传感器校准和变形估计(SCADE),以解决在自由和受阻环境中对通用连续性操纵器(CM)的变形行为进行建模的问题。在SCADE中,使用新颖的数学公式,我们引入了与先验模型无关的滤波算法,以将嵌入式传感器(例如,磁性或压电传感器)的连续和不准确的测量结果与外部成像系统(例如, ,光学跟踪器或照相机)。本文的主要动机是获得在外科手术中使用的CM的准确形状/位置估计的迫切需求。在这些机器人程序中,CM通常配备有嵌入式传感单元(ESU),而在手术部位也可以使用外部成像装置(例如,超声或荧光检查仪)。在自由和受阻的环境中使用两组不同的先验实验的结果来评估SCADE算法的有效性。实验是使用专为矫形外科手术而设计的CM进行的,该CM配备了不精确的光纤布拉格光栅(FBG)ESU和高架摄像机。结果表明,SCADE算法在同时估计利用的未建模CM的未知变形行为的同时,还实现了标定较差的FBG传感单元的时变漂移,具有成功的性能。此外,结果表明,与基于FBG的位置估计相比,SCADE算法在估计CM尖端位置方面表现出惊人的性能。

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