多传感器融合获取曲面轮廓

J. Fonseca, J. Mendes, J. Martins, C. Couto
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引用次数: 0

摘要

提出了一种多传感器融合技术,利用低成本的超声传感器以最小的误差获取表面轮廓。这些表面由不同深度、角落和镜面的区域组成。为了最大限度地减少声纳传感器的约束,开发了专用的软件和硬件,并从实际数据中获得了经验模型。该模型基于两个提出的概念:恒定深度点(PCD)和恒定深度区域(ACD)。针对这种声纳模型,分别采用了四种多传感器融合技术:平均和方差、模糊控制器和基于规则的启发式方法来验证声纳模型的PCDs并确定ACDs。在这项工作中,PUMA 560机械手配备了一个CCD摄像机和四个超声波传感器在手腕上,以获取零件表面几何形状的内部表示数据,利用机器人的机动性。CCD相机视图定义了工作区域,而超声波传感器能够获取表面轮廓。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multisensor fusion for acquisition of the profile of surfaces
This paper presents multisensor fusion techniques for the acquisition of the profile of surfaces with minimum error using low cost sensors ultrasonic sensors. These surfaces are composed by areas with different depths, corners and specular surfaces. To minimize the constraints of sonar sensors, it was developed dedicated software and hardware, as well as an empirical model was obtained from real data. This model is based in two proposed concepts: points of constant depth (PCD) and areas of constant depth (ACD). Having this sonar model in mind, four multisensor fusion techniques are used separately to validate the PCDs and decide the ACDs: average and variance, fuzzy controller and heuristic method based in rules. In this work a PUMA 560 manipulator was equipped with a CCD video camera and four ultrasonic sensors on the wrist, to acquire data for internally representation of the geometry of the part's surface, exploiting the mobility of the robot. The CCD camera view defines the working area while the ultrasonic sensors enable the acquisition of the surface profile.
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