Chinese Journal of Intelligent Science and Technology ›› 2022, Vol. 4 ›› Issue (2): 233-245.doi: 10.11959/j.issn.2096-6652.202226

• Special Topic: Autonomous Agent Learning for Dexterous and Accurate Manipulations • Previous Articles     Next Articles

3D edge reconstruction method based on tactile sensing and servo

Jingyi HU1,2, Shaowei CUI1,2, Chaofan ZHANG1, Boyue ZHANG1, Shuo WANG1,3,4   

  1. 1 The State Key Laboratory for Management and Control of Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
    2 School of Future Technology, University of Chinese Academy of Sciences, Beijing 100049, China
    3 School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China
    4 Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai 200031, China
  • Online:2022-06-15 Published:2022-06-01
  • Supported by:
    The National Key Research and Development Program of China(2018AAA0103003);The National Natural Science Foundation of China(U1913201)

Abstract:

The dexterous manipulation of robots has always been a hot topic in the field of robotics.In many dexterous manipulation tasks, robots need not only visual feedback, but also tactile feedback at the fingertips, especially in poor lighting conditions.Currently, 3D shape sensing of objects using tactile servo is still very challenging.The flat GelSight tactile sensors are not suitable for 3D shape sensing of objects.Therefore, the design of GelSight tactile sensor was improved to make it more suitable for the acquisition of edge information of 3D objects.At the same time, an object edge tracking control strategy based on tactile servo and a 3D object edge reconstruction method based on tactile point cloud were proposed to support the generation of dexterous manipulation strategies for robots.For a variety of complex 3D edge models, the effectiveness of the proposed method was verified by the tactile servo tracking and 3D edge reconstruction experiments.

Key words: tactile servo, tactile sensing, 3D reconstruction

CLC Number: 

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