Dexterous robotic grasping of delicate fruits aided with a multi-sensory e-glove and manual grasping analysis for damage-free manipulation

Zheng, Wei; Xie, Yuanxin; Zhang, Baohua; Zhou, Jun; Zhang, Jintao

doi:10.1016/j.compag.2021.106472

Cited by 17 publications

(4 citation statements)

References 25 publications

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“…Despite substantial advancements in manipulator gripping research, attaining an equivalent degree of robustness and adaptability to that found in the human hand remains a challenging endeavour [ 29 ]. Existing R-Hs vary from simple single-DOF parallel grippers to high-DOF anthropomorphic hands.…”

Section: Human-hand-like Grippersmentioning

confidence: 99%

Bioinspiration and Biomimetic Art in Robotic Grippers

Nguyen,

Dhyan,

Mai

et al. 2023

Micromachines

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The autonomous manipulation of objects by robotic grippers has made significant strides in enhancing both human daily life and various industries. Within a brief span, a multitude of research endeavours and gripper designs have emerged, drawing inspiration primarily from biological mechanisms. It is within this context that our study takes centre stage, with the aim of conducting a meticulous review of bioinspired grippers. This exploration involved a nuanced classification framework encompassing a range of parameters, including operating principles, material compositions, actuation methods, design intricacies, fabrication techniques, and the multifaceted applications into which these grippers seamlessly integrate. Our comprehensive investigation unveiled gripper designs that brim with a depth of intricacy, rendering them indispensable across a spectrum of real-world scenarios. These bioinspired grippers with a predominant emphasis on animal-inspired solutions have become pivotal tools that not only mirror nature’s genius but also significantly enrich various domains through their versatility.

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Section: Human-hand-like Grippersmentioning

confidence: 99%

Bioinspiration and Biomimetic Art in Robotic Grippers

Nguyen,

Dhyan,

Mai

et al. 2023

Micromachines

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“…Second, all of these steps are based on the combination of real-time visual and tactile data processing and the highly precise motion of the end-effector for a single block extraction. According to this, it can be surely compared to real-world industrial [ 11 ], surgical [ 24 ], and agricultural [ 25 , 26 ] manipulation tasks.…”

Section: Introductionmentioning

confidence: 99%

Deep Instance Segmentation and Visual Servoing to Play Jenga with a Cost-Effective Robotic System

Marchionna

Pugliese

Martini

et al. 2023

Sensors

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The game of Jenga is a benchmark used for developing innovative manipulation solutions for complex tasks. Indeed, it encourages the study of novel robotics methods to successfully extract blocks from a tower. A Jenga game involves many traits of complex industrial and surgical manipulation tasks, requiring a multi-step strategy, the combination of visual and tactile data, and the highly precise motion of a robotic arm to perform a single block extraction. In this work, we propose a novel, cost-effective architecture for playing Jenga with e.Do, a 6DOF anthropomorphic manipulator manufactured by Comau, a standard depth camera, and an inexpensive monodirectional force sensor. Our solution focuses on a visual-based control strategy to accurately align the end-effector with the desired block, enabling block extraction by pushing. To this aim, we trained an instance segmentation deep learning model on a synthetic custom dataset to segment each piece of the Jenga tower, allowing for visual tracking of the desired block’s pose during the motion of the manipulator. We integrated the visual-based strategy with a 1D force sensor to detect whether the block could be safely removed by identifying a force threshold value. Our experimentation shows that our low-cost solution allows e.DO to precisely reach removable blocks and perform up to 14 consecutive extractions in a row.

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“…Due to the lack of flexibility and adaptability of the traditional grippers in grasping soft and deformable fruits [5] the performance of the robotic system in practical application is limited [6]. Since the nature of the soft fruits, such as shape and size vary from one another, the development of various sensors and control strategies is needed.…”

Section: Introductionmentioning

confidence: 99%

Review on human‐like robot manipulation using dexterous hands

Sampath

Wang

Wu³

et al. 2023

Cognitive Comp and Systems

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In recent years, human hand‐based robotic hands or dexterous hands have gained attention due to their enormous capabilities of handling soft materials compared to traditional grippers. Back in the earlier days, the development of a hand model close to that of a human was an impossible task but with the advancements made in technology, dexterous hands with three, four or five‐fingered robotic hands have been developed to mimic human hand nature. However, human‐like manipulation of dexterous hands to this date remains a challenge. Thus, this review focuses on (a) the history and motivation behind the development of dexterous hands, (b) a brief overview of the available multi‐fingered hands, and (c) learning‐based methods such as traditional and data‐driven learning methods for manipulating dexterous hands. Additionally, it discusses the challenges faced in terms of the manipulation of multi‐fingered or dexterous hands.

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Dexterous robotic grasping of delicate fruits aided with a multi-sensory e-glove and manual grasping analysis for damage-free manipulation

Cited by 17 publications

References 25 publications

Bioinspiration and Biomimetic Art in Robotic Grippers

Bioinspiration and Biomimetic Art in Robotic Grippers

Deep Instance Segmentation and Visual Servoing to Play Jenga with a Cost-Effective Robotic System

Review on human‐like robot manipulation using dexterous hands

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