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Multimodal Bin Picking System with Compliant Tactile Sensor Arrays for Flexible Part Handling*

机译:具有兼容触觉传感器阵列的多模式垃圾箱拣选系统,用于灵活的零件处理*

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This paper presents a robot control architecture comprised of tactile and vision sensors incorporated into an off-the-shelf bin picking system. The proposed architecture facilitates flexible and reliable handling of objects and materials by employing a tactile grasp validation system and in-hand object monitoring. Two industrial grippers, specifically a magnetic gripper and a flexible vacuum gripper, are equipped with a compliant custom tactile sensor array. The algorithms used are for each specific gripper and respective sensor, however are transferrable to other grippers as well. The tactile sensing augments vision-based picking approaches, thus supporting in-hand object recognition [1] that is particularly useful for hard-to-recognize objects such as objects with transparent or shiny surfaces. Algorithms for tactile-based object pose estimation in the gripper and for grasp monitoring, including grasp validation, complete the approach.
机译:本文提出了一种机器人控制架构,该架构由触觉和视觉传感器组成,并集成到了现成的垃圾箱拣选系统中。所提出的体系结构通过采用触觉抓握验证系统和现场物体监控,有助于灵活,可靠地处理物体和材料。两个工业抓具,特别是电磁抓具和柔性真空抓具,均配备了符合要求的定制触觉传感器阵列。所使用的算法用于每个特定的抓具和相应的传感器,但是也可以转移到其他抓具。触觉增强了基于视觉的拾取方法,从而支持了手部物体识别[1],这对于难以识别的物体(例如具有透明或发光表面的物体)特别有用。用于在抓取器中基于触觉的物体姿态估计以及用于抓握监控(包括抓握验证)的算法完善了该方法。

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