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An identification and localization approach of different labware for mobile robot transportation in life science laboratories

机译:不同实验室的识别与本地化方法,用于移动机器人运输在生命科学实验室

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The accurate detection and position estimation of objects is vital to perform transportation tasks safely with mobile robots. This work presents an approach to identify and localize multiple labware which contains chemical and biological components to be manipulated and transported in life science laboratories using H20 mobile robots. The H20 robot has dual arms where each arm consists of 6 revolute joints with 6-DOF and 2-DOF grippers. The Kinect sensor is used to detect the required labware on a wide workstation to be manipulated wherever it is located. Polarization and intensity filters are used with the Kinect to eliminate the effects of strong and glossy light on the identification process. The local features recognition based on SURF algorithm (Speeded-Up Robust Features) is used to differentiate multiple labware which are defined by some marks. Some preprocessing steps are applied to the image to improve the recognition process. A localization procedure is performed for the target using the Kinect depth frame with a mapping process. The implemented approach approves an efficient performance with a high success rate under different lighting conditions.
机译:对象的准确检测和位置估计对于安全机器人安全地执行运输任务至关重要。这项工作提出了一种方法来识别和本地化多个实验室软件,其中包含使用H20移动机器人在生活科学实验室中操纵和运输的化学和生物分量。 H20机器人具有双臂,其中每个臂由6个旋转接头组成,具有6- DOF和2-DOF夹具。 Kinect传感器用于在其定位的位置进行操纵宽工作站上的所需实验室软件。偏振和强度过滤器与Kinect一起使用,以消除强烈和光泽灯对识别过程的影响。基于SURF算法(加速强大功能)的本地特征识别用于区分由某些标记定义的多个实验室软件。将一些预处理步骤应用于图像以改善识别过程。使用具有映射过程的Kinect深度帧对目标执行定位过程。实施方法在不同的照明条件下批准了高成功率的高效性能。

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