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VReason Grasp: An Ordered Grasp Based on Physical Intuition in Stacking Objects

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Intelligent Systems Design and Applications (ISDA 2021)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 418))

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Abstract

The supporting semantics plays a vital role in the robotic grasping task. However, it is difficult to identify the spatial relationship of the objects and grasp them orderly without falling. This paper presents a Visual Reasoning Grasp Framework (VRGF) to address the problems mentioned above. The VRGF consists of two parts: 3D semantic segmentation and Supporting Relationship Reasoning (SRR). We adopt the fused projection for 3D semantic segmentation, which can reduce the processing time and promote the performance of the reasoning framework. The SRR can distinguish how objects support each other in the stacking scenarios. We also design a complete robotic system to verify the robustness and generalization of the framework in the real world. The experiment results demonstrate the reliability and robustness of the VRGF’s grasping strategy for stacking objects.

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Author information

Authors and Affiliations

  1. School of Information Science and Technology, Fudan University, Shanghai, China

    Xiang Ji, Qiushu Chen & Tao Xiong

  2. Academy for Engineering and Technology, Fudan University, Shanghai, China

    Tianyu Xiong

  3. Department of Electronic Engineering, School of Information Science and Technology, Research Center of Smart Networks and Systems, Fudan University, Shanghai, China

    Huiliang Shang

Authors
  1. Xiang Ji
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  2. Qiushu Chen
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  3. Tao Xiong
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  4. Tianyu Xiong
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  5. Huiliang Shang
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Corresponding author

Correspondence to Huiliang Shang .

Editor information

Editors and Affiliations

  1. Scientific Network for Innovation and Research Excellence, Machine Intelligence Research Labs (MIR Labs), Auburn, WA, USA

    Ajith Abraham

  2. Scientific Network for Innovation and Research Excellence, Machine Intelligence Research Labs (MIR Labs), Auburn, WA, USA

    Niketa Gandhi

  3. Institut für Wirtschaftsinformatik, Fachhochschule Nordwestschweiz, Olten, Switzerland

    Thomas Hanne

  4. Department of Computer Science and information Engineering, National University of Kaohsiung, Kaohsiung, Taiwan

    Tzung-Pei Hong

  5. Federal University of Bahia, Ondina, Brazil

    Tatiane Nogueira Rios

  6. Nantong University, Nantong Shi, Jiangsu, China

    Weiping Ding

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Ji, X., Chen, Q., Xiong, T., Xiong, T., Shang, H. (2022). VReason Grasp: An Ordered Grasp Based on Physical Intuition in Stacking Objects. In: Abraham, A., Gandhi, N., Hanne, T., Hong, TP., Nogueira Rios, T., Ding, W. (eds) Intelligent Systems Design and Applications. ISDA 2021. Lecture Notes in Networks and Systems, vol 418. Springer, Cham. https://doi.org/10.1007/978-3-030-96308-8_70

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