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   Articles with "grasp detection" as a keyword



Research on robotic grasp detection using improved generative convolution neural network with Gaussian representation

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recommendations! Published in 2025 at "Robotica"

DOI: 10.1017/s0263574725102750

Abstract: Grasp detection is a significant research direction in the field of robotics. Traditional analysis methods typically require prior knowledge of the object parameters, limiting grasp detection to structured environments and resulting in suboptimal performance. In… read more here.

Keywords: detection; grasp detection; research; neural network ... See more keywords

A model-free 6-DOF grasp detection method based on point clouds of local sphere area

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recommendations! Published in 2023 at "Advanced Robotics"

DOI: 10.1080/01691864.2023.2197961

Abstract: ABSTRACT Grasping object is one of the basic tasks of robots in many scenarios. The main challenge is how to generate grasping poses for unknown objects in cluttered scenes. This paper proposes a model-free 6-DOF… read more here.

Keywords: point clouds; dof grasp; free dof; grasp detection ... See more keywords

GraspCNN: Real-Time Grasp Detection Using a New Oriented Diameter Circle Representation

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recommendations! Published in 2019 at "IEEE Access"

DOI: 10.1109/access.2019.2950535

Abstract: This paper proposes GraspCNN, an approach to grasp detection where a feasible robotic grasp is detected as an oriented diameter circle in RGB image, using a single convolutional neural network. By detecting robotic grasps as… read more here.

Keywords: oriented diameter; grasp; diameter circle; grasp detection ... See more keywords

SE-ResUNet: A Novel Robotic Grasp Detection Method

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recommendations! Published in 2022 at "IEEE Robotics and Automation Letters"

DOI: 10.1109/lra.2022.3145064

Abstract: In this paper, a novel grasp detection neural network Squeeze-and-Excitation ResUNet (SE-ResUNet) is developed, where the residual block with the channel attention is integrated. The proposed framework can not only generate the grasp pose from… read more here.

Keywords: resunet novel; novel robotic; grasp; grasp detection ... See more keywords

When Transformer Meets Robotic Grasping: Exploits Context for Efficient Grasp Detection

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recommendations! Published in 2022 at "IEEE Robotics and Automation Letters"

DOI: 10.1109/lra.2022.3187261

Abstract: In this letter, we present a transformer-based architecture, namely TF-Grasp, for robotic grasp detection. The developed TF-Grasp framework has two elaborate designs making it well suitable for visual grasping tasks. The first key design is… read more here.

Keywords: transformer meets; meets robotic; grasp; grasp detection ... See more keywords

SymmetryGrasp: Symmetry-Aware Antipodal Grasp Detection From Single-View RGB-D Images

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recommendations! Published in 2022 at "IEEE Robotics and Automation Letters"

DOI: 10.1109/lra.2022.3214785

Abstract: Symmetry is ubiquitous in everyday objects. Humans tend to grasp objects by recognizing the symmetric regions. In this letter, we investigate how symmetry could boost robotic grasp detection. To this end, we present a learning-based… read more here.

Keywords: grasp; grasp detection; symmetry; view rgb ... See more keywords

AAGDN: Attention-Augmented Grasp Detection Network Based on Coordinate Attention and Effective Feature Fusion Method

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recommendations! Published in 2023 at "IEEE Robotics and Automation Letters"

DOI: 10.1109/lra.2023.3268596

Abstract: High-precision robotic grasping is necessary for extensive grasping applications in the future. Most previous grasp detection methods fail to pay enough attention to learn grasp-related features and the detection accuracy is limited. In this letter,… read more here.

Keywords: attention; attention augmented; feature; grasp detection ... See more keywords

DSNet: Double Strand Robotic Grasp Detection Network Based on Cross Attention

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recommendations! Published in 2024 at "IEEE Robotics and Automation Letters"

DOI: 10.1109/lra.2024.3381091

Abstract: In this letter, we propose a Double Strand robotic grasp detection Network (DSNet), that combines a transformer branch and a U-Net branch within an encoder-decoder structure. The DSNet is designed to reconcile differences between these… read more here.

Keywords: detection network; grasp detection; strand robotic; double strand ... See more keywords

Two-Stage Grasp Detection Method for Robotics Using Point Clouds and Deep Hierarchical Feature Learning Network

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recommendations! Published in 2024 at "IEEE Transactions on Cognitive and Developmental Systems"

DOI: 10.1109/tcds.2023.3289987

Abstract: When human beings see different objects, they can quickly make correct grasping strategies through brain decisions. However, grasp, as the first step of most manipulation tasks, is still an open issue in robotics. Although many… read more here.

Keywords: grasp detection; point clouds; robotics; network ... See more keywords

High-Performance Pixel-Level Grasp Detection Based on Adaptive Grasping and Grasp-Aware Network

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recommendations! Published in 2022 at "IEEE Transactions on Industrial Electronics"

DOI: 10.1109/tie.2021.3120474

Abstract: Machine vision-based planar grasping detection is challenging due to uncertainty about object shape, pose, size, etc. Previous methods mostly focus on predicting discrete gripper configurations, and may miss some ground-truth grasp postures. In this article,… read more here.

Keywords: pixel level; network; grasp; grasp detection ... See more keywords

EGNet: Efficient Robotic Grasp Detection Network

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recommendations! Published in 2022 at "IEEE Transactions on Industrial Electronics"

DOI: 10.1109/tie.2022.3174274

Abstract: In this paper, a novel grasp detection network, Efficient Grasp detection Network (EGNet), is proposed to deal with the grasp challenging in stacked scenes, which complete the tasks of the object detection, grasp detection and… read more here.

Keywords: detection network; grasp; egnet; detection ... See more keywords