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Current Research Trends in Robot Grasping and Bin Picking

  • Marcos Alonso
  • Alberto Izaguirre
  • Manuel Graña
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 771)

Abstract

We provide a view of current research issues in Robotic Grasping and Bin Picking focused on the perception aspects of the problem, mainly related to computer vision algorithms. After recalling the evolution of the topics in the last decades, we focus on the modern use of Deep Learning Algorithms. Two main trends are followed in the approaches to innovative grasping techniques. First, Convolutional Neural Networks are used for grasping perceptual aspects. We discuss the different degrees of success of several published approaches. Second, Deep Reinforcement Learning is being extensively tested in order to develop integrated eye-hand coordination systems not requiring delicate calibration. We provide also a discussion of possible future lines of research.

Keywords

Robot grasping Bin Picking Deep Learning Convolutional Neural Networks Robot gripper Robot planning 

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2019

Authors and Affiliations

  • Marcos Alonso
    • 1
  • Alberto Izaguirre
    • 2
  • Manuel Graña
    • 1
  1. 1.Computational Intelligence Group, CCIA DepartmentUPV/EHUSan SebastianSpain
  2. 2.CIS and Electronics DepartmentUniversity of MondragonMondragonSpain

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