自主工业移动机械手的对象处理

Hongtai Cheng, Heping Chen, Yong Liu
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引用次数: 11

摘要

自主工业移动机械手(AIMMs)结合了移动机器人和工业机械手的优点;因此,它们具有很强的移动性、灵活性和功能性。然而,aim带来的不仅是更大的作战范围,还有更低的操纵精度。在传感、校准和协调问题上出现了巨大的挑战。提出了一种具有有限操作距离传感器和机械臂的目标处理任务协调问题的解决方案。与现有的单手摄像机配置的基于图像的视觉伺服系统(IBVS)不同,采用了单手摄像机配置的RGB-D摄像机。通过匹配目标物体上的颜色特征来检测目标,通过将深度图像与RGB图像进行校准和匹配来测量目标。传感器和机械手之间的手眼校准是使用位于两个设备范围内的特定选择的物体位置进行的。此外,设计了一个基于位置的视觉伺服控制器来引导机器人走向目标,而不是沿着预定的轨迹引导移动基座。实验结果验证了所提协调控制算法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Object handling using Autonomous Industrial Mobile Manipulator
Autonomous Industrial Mobile Manipulators (AIMMs) combine the advantages of both mobile robots and industrial manipulators; therefore they have great mobility, flexibility and functionality. However, what the AIMM brings not only bigger operational range, but also lower manipulation accuracy. Great challenges arise in the sensing, calibration and coordination problems. This paper proposes a solution for the coordination problems of an object handling task for AIMM with limited operational range sensors and manipulators. Different from the existing Image Based Visual Servo(IBVS) with single camera-in-hand configuration, a RGB-D camera with camera-to-hand configuration is utilized. The object is detected by matching the color feature on the target object and measured by calibrating and matching the depth image with the RGB image. The hand-eye calibration between the sensor and the manipulator is performed using the specifically chosen object locations which lie in both the range of the two devices. Furthermore, instead of steering the mobile base along a preplanned trajectory, a position based visual servo controller is designed to guide the robot towards the object. The methods are implemented using an AIMM and the experimental results verify the effectiveness of the proposed coordination and control algorithm.
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