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Artículos de revistas sobre el tema "Grasping strategies"

Autor: Grafiati

Publicado: 11 de enero de 2025

Última modificación: 31 de julio de 2025

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1

Desanghere, L., and J. Marotta. "Gaze strategies and grasping: Complex shapes." Journal of Vision 9, no. 8 (2010): 1108. http://dx.doi.org/10.1167/9.8.1108.

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2

Huang, Xiaoqian, Mohamad Halwani, Rajkumar Muthusamy, et al. "Real-time grasping strategies using event camera." Journal of Intelligent Manufacturing 33, no. 2 (2022): 593–615. http://dx.doi.org/10.1007/s10845-021-01887-9.

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AbstractRobotic vision plays a key role for perceiving the environment in grasping applications. However, the conventional framed-based robotic vision, suffering from motion blur and low sampling rate, may not meet the automation needs of evolving industrial requirements. This paper, for the first time, proposes an event-based robotic grasping framework for multiple known and unknown objects in a cluttered scene. With advantages of microsecond-level sampling rate and no motion blur of event camera, the model-based and model-free approaches are developed for known and unknown objects’ grasping

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3

Peckre, Louise R., Anne-Claire Fabre, Julien Hambuckers, Christine E. Wall, lluís Socias-Martínez, and Emmanuelle Pouydebat. "Food properties influence grasping strategies in strepsirrhines." Biological Journal of the Linnean Society 127, no. 3 (2019): 583–97. http://dx.doi.org/10.1093/biolinnean/bly215.

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4

Leferink, Charlotte, Hannah Stirton, and Jonathan Marotta. "Visuomotor strategies for grasping a rotating target." Journal of Vision 15, no. 12 (2015): 1151. http://dx.doi.org/10.1167/15.12.1151.

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5

Bulloch, Melissa C., Steven L. Prime, and Jonathan J. Marotta. "Anticipatory gaze strategies when grasping moving objects." Experimental Brain Research 233, no. 12 (2015): 3413–23. http://dx.doi.org/10.1007/s00221-015-4413-7.

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6

Roby-Brami, Agnès, Sylvie Fuchs, Mounir Mokhtari, and Bernard Bussel. "Reaching and Grasping Strategies in Hemiparetic Patients." Motor Control 1, no. 1 (1997): 72–91. http://dx.doi.org/10.1123/mcj.1.1.72.

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7

Yang, Yanxin. "Research of Grasping Strategy of Bionic Manipulator." Applied and Computational Engineering 128, no. 1 (2025): 119–25. https://doi.org/10.54254/2755-2721/2025.20214.

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This article reviews the research progress of bionic manipulator grabbing strategies in recent years, subsequently, the classification of existing bionic manipulator grabbing strategies was sorted out in detail, including crawling strategies based on the principle of biological inspiration, crawling strategies based on mechanical models and crawling strategies based on intelligent algorithms. First, the paper outlines the structural design and control methods of bionic manipulators. Next, the classification and characteristics of existing crawling strategies are summarized. These include strat

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8

Hasegawa, Yasuhisa, Kensaku Kanada, and Toshio Fukuda. "Dexterous manipulation from pinching to power grasping - performance comparison of grasping strategies for different objects." IFAC Proceedings Volumes 36, no. 17 (2003): 335–40. http://dx.doi.org/10.1016/s1474-6670(17)33416-x.

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9

Dzitac, Pavel, and Md Mazid Abdul. "Modeling of an Object Manipulation Motion Planner and Grasping Rules." Applied Mechanics and Materials 278-280 (January 2013): 664–72. http://dx.doi.org/10.4028/www.scientific.net/amm.278-280.664.

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This paper presents the development of a Motion Planning Module for object manipulation, which is a part of previously developed robotic grasping and manipulation controller. The Motion Planning Module consists of a sensing processor, decision making module, instinctive controller, motion planner and a planned motion controller. Details related to the design and modelling of the motion planning module have been offered. Results of experiments on human grasping rule, suitable for the grasping and manipulation controller, have been discussed. The output of this research may be useful to those de

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10

Dong, Chengyu. "Bio-inspired Octopus-mimicking Soft Robotic Grasping System." Applied and Computational Engineering 128, no. 1 (2025): 86–90. https://doi.org/10.54254/2755-2721/2025.20210.

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Octopus-inspired soft robots have emerged as a promising field of research, drawing inspiration from the remarkable dexterity and adaptability of this marine creature. Their ability to manipulate objects in complex environments, coupled with their soft, compliant bodies, offers significant advantages over traditional rigid robots. This paper provides a comprehensive overview of recent advancements in the design and development of octopus-inspired soft robots, focusing on shape control, grasping strategies, and potential applications. This paper presents a comprehensive review of recent advance

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11

Zhang, Haojun, Sheng Zeng, Yaokun Hou, Haojie Huang, and Zhezhuang Xu. "Improved QT-Opt Algorithm for Robotic Arm Grasping Based on Offline Reinforcement Learning." Machines 13, no. 6 (2025): 451. https://doi.org/10.3390/machines13060451.

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Reinforcement learning plays a crucial role in the field of robotic arm grasping, providing a promising approach for the development of intelligent and adaptive grasping strategies. Due to distribution shift and local optimum in action, traditional online reinforcement learning is difficult to use existing grasping datasets, leading to low sample efficiency. This study proposes an improved QT-Opt algorithm for robotic arm grasping based on offline reinforcement learning. This improved algorithm proposes the Particle Swarm Optimization (PSO) to identify the action with the highest value within

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12

Touillet, Amélie, Adrienne Gouzien, Marina Badin, et al. "Kinematic analysis of impairments and compensatory motor behavior during prosthetic grasping in below-elbow amputees." PLOS ONE 17, no. 11 (2022): e0277917. http://dx.doi.org/10.1371/journal.pone.0277917.

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After a major upper limb amputation, the use of myoelectric prosthesis as assistive devices is possible. However, these prostheses remain quite difficult to control for grasping and manipulation of daily life objects. The aim of the present observational case study is to document the kinematics of grasping in a group of 10 below-elbow amputated patients fitted with a myoelectric prosthesis in order to describe and better understand their compensatory strategies. They performed a grasping to lift task toward 3 objects (a mug, a cylinder and a cone) placed at two distances within the reaching ar

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13

Prime, S. L., and J. J. Marotta. "Gaze strategies during visually-guided and memory-guided grasping." Journal of Vision 11, no. 11 (2011): 967. http://dx.doi.org/10.1167/11.11.967.

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14

Leferink, Charlotte, Neil Bruce, and Jonathan Marotta. "Visualization of viewing strategies for grasping a rotating target." Journal of Vision 17, no. 10 (2017): 464. http://dx.doi.org/10.1167/17.10.464.

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15

Desanghere, L., and J. Marotta. "Gaze strategies while grasping: What are you looking at?!" Journal of Vision 8, no. 6 (2010): 299. http://dx.doi.org/10.1167/8.6.299.

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16

Prime, Steven L., and Jonathan J. Marotta. "Gaze strategies during visually-guided versus memory-guided grasping." Experimental Brain Research 225, no. 2 (2012): 291–305. http://dx.doi.org/10.1007/s00221-012-3358-3.

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17

McCarty, Michael, and Rachel Clifton. "Infant's and toddler's strategies for grasping and using tools." Infant Behavior and Development 21 (April 1998): 211. http://dx.doi.org/10.1016/s0163-6383(98)91426-6.

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18

Kyberd, Peter. "Slip Detection Strategies for Automatic Grasping in Prosthetic Hands." Sensors 23, no. 9 (2023): 4433. http://dx.doi.org/10.3390/s23094433.

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The detection of an object slipping within the grasp of a prosthetic hand enables the hand to react to ensure the grasp is stable. The computer controller of a prosthetic hand needs to be able to unambiguously detect the slide from other signals. Slip can be detected from the surface vibrations made as the contact between object and terminal device shifts. A second method measures the changes in the normal and tangential forces between the object and the digits. After a review of the principles of how the signals are generated and the detection technologies are employed, this paper details the

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19

Blanco, Kai, Eduardo Navas, Daniel Rodríguez-Nieto, Luis Emmi, and Roemi Fernández. "Design and Experimental Assessment of 3D-Printed Soft Grasping Interfaces for Robotic Harvesting." Agronomy 15, no. 4 (2025): 804. https://doi.org/10.3390/agronomy15040804.

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Robotic harvesters and grippers have been widely developed for fruit-picking tasks. However, existing approaches often fail to account for the fruit’s post-harvest condition, leading to premature decay due to excessive grasping forces. This study addresses this gap by designing and evaluating passive soft grasping interfaces for rigid robotic grippers, aiming to handle delicate fruits and vegetables while minimizing bruising. Using hyperelastic materials and 3D printing, four different interface designs, including Gyroid, Grid, Cubic, and Cross 3D patterns, were developed and tested. Experimen

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20

GREENWALD, HAL S., and DAVID C. KNILL. "A comparison of visuomotor cue integration strategies for object placement and prehension." Visual Neuroscience 26, no. 1 (2009): 63–72. http://dx.doi.org/10.1017/s0952523808080668.

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AbstractVisual cue integration strategies are known to depend on cue reliability and how rapidly the visual system processes incoming information. We investigated whether these strategies also depend on differences in the information demands for different natural tasks. Using two common goal-oriented tasks, prehension and object placement, we determined whether monocular and binocular information influence estimates of three-dimensional (3D) orientation differently depending on task demands. Both tasks rely on accurate 3D orientation estimates, but 3D position is potentially more important for

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21

Dong, Xiaoxiao, Chen Wang, Haoxin Song, et al. "Advancement in Soft Hydrogel Grippers: Comprehensive Insights into Materials, Fabrication Strategies, Grasping Mechanism, and Applications." Biomimetics 9, no. 10 (2024): 585. http://dx.doi.org/10.3390/biomimetics9100585.

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Soft hydrogel grippers have attracted considerable attention due to their flexible/elastic bodies, stimuli-responsive grasping and releasing capacity, and novel applications in specific task fields. To create soft hydrogel grippers with robust grasping of various types of objects, high load capability, fast grab response, and long-time service life, researchers delve deeper into hydrogel materials, fabrication strategies, and underlying actuation mechanisms. This article provides a systematic overview of hydrogel materials used in soft grippers, focusing on materials composition, chemical func

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22

Michalland, Arthur-Henri, Guillaume Thébault, Johan Briglia, Philippe Fraisse, and Denis Brouillet. "Grasping a Chestnut Burr." Experimental Psychology 66, no. 4 (2019): 310–17. http://dx.doi.org/10.1027/1618-3169/a000449.

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Abstract. This work aimed to assess the role of manual laterality in action coding strategies and, subsequently, in environmental features relevant for each hand’s action. Relying on Eder and Hommel’s (2013) proposal, we distinguished stimulus-related and end state-related consequences in a Simon paradigm where right-handed participants were divided into two groups, one responding with gloves and one without. Two objects were presented pictorially: one for which sensory consequences of grasping were negatively valenced (a chestnut burr), and one for which they were positively valenced (an apri

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23

Fontana, Gianmauro, Serena Ruggeri, Irene Fassi, and Giovanni Legnani. "A mini work-cell for handling and assembling microcomponents." Assembly Automation 34, no. 1 (2014): 27–33. http://dx.doi.org/10.1108/aa-11-2012-087.

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Purpose – The purpose of this paper was the design, development, and test of a flexible and reconfigurable experimental setup for the automatic manipulation of microcomponents, enhanced by an accurately developed vision-based control. Design/methodology/approach – To achieve a flexible and reconfigurable system, an experimental setup based on 4 degrees of freedom robot and a two-camera vision system was designed. Vision-based strategies were adopted to suitably support the motion system in easily performing precise manipulation operations. A portable and flexible program, incorporating the mac

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24

Cao, Chuqing, and Hanwei Liu. "Grasp Pose Detection Based on Shape Simplification." International Journal of Humanoid Robotics 18, no. 03 (2021): 2150006. http://dx.doi.org/10.1142/s0219843621500067.

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For robots in an unstructured work environment, grasping unknown objects that have neither model data nor RGB data is very important. The key to robotic autonomous grasping is not only in the judgment of object type but also in the shape of the object. We present a new grasping approach based on the basic compositions of objects. The simplification of complex objects is conducive to the description of object shape and provides effective ideas for the selection of grasping strategies. First, the depth camera is used to obtain partial 3D data of the target object. Then the 3D data are segmented

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25

Osa, T., Jan Peters, and G. Neumann. "Hierarchical reinforcement learning of multiple grasping strategies with human instructions." Advanced Robotics 32, no. 18 (2018): 955–68. http://dx.doi.org/10.1080/01691864.2018.1509018.

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26

Chen, Dong, Ziyuan Liu, and Georg von Wichert. "Uncertainty-Aware Arm-Base Coordinated Grasping Strategies for Mobile Manipulation." Journal of Intelligent & Robotic Systems 80, S1 (2015): 205–23. http://dx.doi.org/10.1007/s10846-015-0234-y.

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27

Christopoulos, Vassilios N., and Paul R. Schrater. "An Optimal Feedback Control Framework for Grasping Objects with Position Uncertainty." Neural Computation 23, no. 10 (2011): 2511–36. http://dx.doi.org/10.1162/neco_a_00180.

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As we move, the relative location between our hands and objects changes in uncertain ways due to noisy motor commands and imprecise and ambiguous sensory information. The impressive capabilities humans display for interacting and manipulating objects with position uncertainty suggest that our brain maintains representations of location uncertainty and builds compensation for uncertainty into its motor control strategies. Our previous work demonstrated that specific control strategies are used to compensate for location uncertainty. However, it is an open question whether compensation for posit

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28

Hu, Jie, Qin Li, and Qiang Bai. "Research on Robot Grasping Based on Deep Learning for Real-Life Scenarios." Micromachines 14, no. 7 (2023): 1392. http://dx.doi.org/10.3390/mi14071392.

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The application of robots, especially robotic arms, has been primarily focused on the industrial sector due to their relatively low level of intelligence. However, the rapid development of deep learning has provided a powerful tool for conducting research on highly intelligent robots, thereby offering tremendous potential for the application of robotic arms in daily life scenarios. This paper investigates multi-object grasping in real-life scenarios. We first analyzed and improved the structural advantages and disadvantages of convolutional neural networks and residual networks from a theoreti

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29

Bensmail, Djamel, Johanna Robertson, Christophe Fermanian, and Agnès Roby-Brami. "Botulinum Toxin to Treat Upper-Limb Spasticity in Hemiparetic Patients: Grasp Strategies and Kinematics of Reach-to-Grasp Movements." Neurorehabilitation and Neural Repair 24, no. 2 (2009): 141–51. http://dx.doi.org/10.1177/1545968309347683.

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Background. Poor control of grasping in spastic, hemiparetic patients could be because of a combination of poor individuation of joints, weakness, spasticity, and sensory loss. Objective. To investigate the effect of botulinum toxin injections (BTIs) on grasping objects of different shapes and to assess the effect on upper-limb function, reach-to-grasp kinematics, and hand position and orientation at the time of grasp. Methods. We included 15 patients with spastic hemiparesis and 9 healthy controls in this open labeled study, in which the patients were assessed before (M0), 1 month after a fir

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30

Ji, Yi Guo, Zhi Huan Lan, Cui Chen, Chun Yan Tian, and Dong Yang. "The Study on Strategies of Winning Information Dominance in Modern Battlefield." Advanced Materials Research 926-930 (May 2014): 2194–97. http://dx.doi.org/10.4028/www.scientific.net/amr.926-930.2194.

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The recent local wars appeared a lot of information characteristics. In future wars, one who master information dominance in battlefield will become more active. In a sense, one who controls the information in the battlefield will grasp the whole initiatives in the war. In the paper, we have researched the methods of grasping the information dominance.

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31

Prime, Steven L., and Jonathan J. Marotta. "Erratum to: Gaze strategies during visually-guided versus memory-guided grasping." Experimental Brain Research 225, no. 2 (2013): 307. http://dx.doi.org/10.1007/s00221-013-3432-5.

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32

Hu, Yingbai, Xinyu Wu, Peng Geng, and Zhijun Li. "Evolution Strategies Learning With Variable Impedance Control for Grasping Under Uncertainty." IEEE Transactions on Industrial Electronics 66, no. 10 (2019): 7788–99. http://dx.doi.org/10.1109/tie.2018.2884240.

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33

Teich, Paul F. "Are Lawyers Truly Greedy? An Analysis of Relevant Empirical Evidence." Texas Wesleyan Law Review 19, no. 4 (2013): 837–97. http://dx.doi.org/10.37419/twlr.v19.i4.1.

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This Article addresses a single question: Have lawyers exploited the increase in demand for their services by adopting increasingly grasping practices such as price gauging, overbilling, and aggressive collection strategies?

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34

Li, Shaobo, Qiang Bai, Jing Yang, and Liya Yu. "Research on Grasping Strategy Based on Residual Network." Journal of Physics: Conference Series 2203, no. 1 (2022): 012066. http://dx.doi.org/10.1088/1742-6596/2203/1/012066.

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Abstract At present, the research on rectangular grasp strategy is generally based on object detection algorithm, which limits the improvement of model accuracy and generalization performance. This paper studies the semantic segmentation model based on residual network, and uses it to generate grasp strategies. The improved algorithm model not only achieves excellent rectangular grasping strategy prediction, but also has good generalization performance.

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35

Ma, Yanqin, Kai Du, Dongfeng Zhou, Juan Zhang, Xilong Liu, and De Xu. "Automatic precision robot assembly system with microscopic vision and force sensor." International Journal of Advanced Robotic Systems 16, no. 3 (2019): 172988141985161. http://dx.doi.org/10.1177/1729881419851619.

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An automatic precision robot assembly system is established. The robot assembly system mainly consists of an industrial robot, three cameras, a micro force sensor, and a specific gripper. The industrial robot is a six-axis serial manipulator, which is used to conduct grasping and assembly subtasks. Two microscopic cameras are fixed on two high accuracy translational platforms to provide visual information in aligning stage for assembly. While one conventional camera is installed on the robotic end effector to guide the gripper to grasp component. The micro force sensor is installed on the robo

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36

Chen, Nutan, Keng Peng Tee, and Chee-Meng Chew. "Teleoperation grasp assistance using infra-red sensor array." Robotica 33, no. 4 (2014): 986–1002. http://dx.doi.org/10.1017/s0263574714000733.

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SUMMARYTeleoperated grasping requires the abilities to follow the intended trajectory from the user and autonomously search for a suitable pre-grasp pose relative to the object of interest. Challenges include dealing with uncertainty due to the noise of the teleoperator, human elements and calibration errors in the sensors. To address these challenges, an effective and robust algorithm is introduced to assist grasping during teleoperation. Although without premature object contact or regrasping strategies, the algorithm enables the robot to perform online adjustments to reach a pre-grasp pose

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37

Cong, Qingzheng, Wen Fan, and Dandan Zhang. "TacFR-Gripper: A Reconfigurable Fin-Ray-Based Gripper with Tactile Skin for In-Hand Manipulation." Actuators 13, no. 12 (2024): 521. https://doi.org/10.3390/act13120521.

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This paper introduces the TacFR-Gripper, a novel reconfigurable soft robotic gripper inspired by the Fin-Ray effect and equipped with tactile skin. The gripper incorporates a four-bar mechanism for accurate finger bending and a reconfigurable design to change the relative positions between the fingers and palm, enabling precise and adaptable object grasping. This 5-Degree-of-Freedom (DOF) soft gripper can facilitate dexterous manipulation of objects with diverse shapes and stiffness and is beneficial to the safe and efficient grasping of delicate objects. An array of Force Sensitive Resistor (

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38

Rong, Jiacheng, Pengbo Wang, Tianjian Wang, Ling Hu, and Ting Yuan. "Fruit pose recognition and directional orderly grasping strategies for tomato harvesting robots." Computers and Electronics in Agriculture 202 (November 2022): 107430. http://dx.doi.org/10.1016/j.compag.2022.107430.

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39

Vitrani, Giuseppe, Simone Cortinovis, Luca Fiorio, Marco Maggiali, and Rocco Antonio Romeo. "Improving the Grasping Force Behavior of a Robotic Gripper: Model, Simulations, and Experiments." Robotics 12, no. 6 (2023): 148. http://dx.doi.org/10.3390/robotics12060148.

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Robotic grippers allow industrial robots to interact with the surrounding environment. However, control architectures of the grasping force are still rare in common industrial grippers. In this context, one or more sensors (e.g., force or torque sensors) are necessary. However, the incorporation of such sensors might heavily affect the cost of the gripper, regardless of its type (e.g., pneumatic or electric). An alternative approach could be open-loop force control strategies. Hence, this work proposes an approach for optimizing the open-loop grasping force behavior of a robotic gripper. For t

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40

Donepudi, Praveen Kumar. "Reinforcement Learning for Robotic Grasping and Manipulation: A Review." Asia Pacific Journal of Energy and Environment 7, no. 2 (2020): 69–78. http://dx.doi.org/10.18034/apjee.v7i2.526.

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A century of robots is the 21st century. The robots have long been able to cross the divide between the virtual universe and the real world. Robotics, as the most successful contender in the upcoming great technological revolution, will play an ever more important role in society because of the impact it has in every field of life, including medicine, healthcare, architecture, manufacturing and food supplies, logistics and transport. This document introduces a modern approach to the grasp of robots, which draws grasp techniques from the human demonstration and combines these strategies into a

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41

Guo, Hongshuang, Hao Zeng, and Arri Priimagi. "Optically controlled grasping-slipping robot moving on tubular surfaces." Multifunctional Materials 5, no. 2 (2022): 024001. http://dx.doi.org/10.1088/2399-7532/ac55fd.

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Abstract Stimuli-responsive polymers provide unmatched opportunities for remotely controlled soft robots navigating in complex environments. Many of the responsive-material-based soft robots can walk on open surfaces, with movement directionality dictated by the friction anisotropy at the robot-substrate interface. Translocation in one-dimensional space such as on a tubular surface is much more challenging due to the lack of efficient friction control strategies. Such strategies could in long term provide novel application prospects in, e.g. overhaul at high altitudes and robotic operation wit

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42

Shukla, Ashwini, and Aude Billard. "Coupled dynamical system based arm–hand grasping model for learning fast adaptation strategies." Robotics and Autonomous Systems 60, no. 3 (2012): 424–40. http://dx.doi.org/10.1016/j.robot.2011.07.023.

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43

Jarrassé, N., S. Martin, and A. Roby-Brami. "Instrumented objects for the study and quantitative evaluation of grasping and manipulation strategies." Annals of Physical and Rehabilitation Medicine 57 (May 2014): e179-e180. http://dx.doi.org/10.1016/j.rehab.2014.03.651.

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44

Van Waelvelde, Hilde, Willy De Weerdt, Paul De Cock, Bouwien C. M. Smits-Engelsman, and Wim Peersman. "Ball Catching Performance in Children with Developmental Coordination Disorder." Adapted Physical Activity Quarterly 21, no. 4 (2004): 348–63. http://dx.doi.org/10.1123/apaq.21.4.348.

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The aim of this study was to compare the quality of ball catching performance of children with DCD to the performance of younger typically developing children. The outcome measures used were a modified ball catching item of the Test of Gross Motor Development and the number of grasping errors in a ball catching test. In the study, children with DCD were matched with younger typically developing children according to gender and the number of caught balls in the ball catching test. Children with DCD made significantly more grasping errors and scored significantly lower on the modified TGMD-item.

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45

Zhang, Rui, Meng Ning, Yuqian Wang, and Jun Yang. "Design and Dimension Optimization of Rigid–Soft Hand Function Rehabilitation Robots." Machines 13, no. 4 (2025): 311. https://doi.org/10.3390/machines13040311.

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The growing population of hand dysfunction patients necessitates advanced rehabilitation technologies. Current robotic solutions face limitations in motion compatibility and systematic design frameworks. This study develops a rigid–soft coupling rehabilitation robot integrating linkage mechanisms with soft components. A machine vision system captures natural grasping trajectories, analyzed through polynomial regression. Hierarchical constraint modeling and an improved artificial bee colony algorithm optimize linkage dimensions and control strategies, achieving enhanced human–robot kinematic ma

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46

Huang, Chih-Yung, Guan-Wen Su, Yu-Hsiang Shao, Ying-Chung Wang, and Shang-Kuo Yang. "Rapid-Learning Collaborative Pushing and Grasping via Deep Reinforcement Learning and Image Masking." Applied Sciences 14, no. 19 (2024): 9018. http://dx.doi.org/10.3390/app14199018.

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When multiple objects are positioned close together or stacked, pre-grasp operations such as pushing objects can be used to create space for the grasp, thereby improving the grasping success rate. This study develops a model based on a deep Q-learning network architecture and introduces a fully convolutional network to accurately identify pixels in the workspace image that correspond to target locations for exploration. In addition, this study incorporates image masking to limit the exploration area of the robotic arm, ensuring that the agent consistently explores regions containing objects. T

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47

Pozzi, Maria, Sara Marullo, Gionata Salvietti, Joao Bimbo, Monica Malvezzi, and Domenico Prattichizzo. "Hand closure model for planning top grasps with soft robotic hands." International Journal of Robotics Research 39, no. 14 (2020): 1706–23. http://dx.doi.org/10.1177/0278364920947469.

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Automating the act of grasping is one of the most compelling challenges in robotics. In recent times, a major trend has gained the attention of the robotic grasping community: soft manipulation. Along with the design of intrinsically soft robotic hands, it is important to devise grasp planning strategies that can take into account the hand characteristics, but are general enough to be applied to different robotic systems. In this article, we investigate how to perform top grasps with soft hands according to a model-based approach, using both power and precision grasps. The so-called closure si

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Seo, N. J., and T. J. Armstrong. "Effect of elliptic handle shape on grasping strategies, grip force distribution, and twisting ability." Ergonomics 54, no. 10 (2011): 961–70. http://dx.doi.org/10.1080/00140139.2011.606923.

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Christopoulos, V., and P. Schrater. "Identifying strategies for grasping objects with position uncertainty using empirical cost-to-go functions." Journal of Vision 8, no. 6 (2010): 296. http://dx.doi.org/10.1167/8.6.296.

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Metz, Stephen, Brian Isle, Sandra Dermo, and James Odom. "Thermostats for Individuals with Movement Disabilities: Design Options and Manipulation Strategies." Proceedings of the Human Factors Society Annual Meeting 36, no. 2 (1992): 180–84. http://dx.doi.org/10.1177/154193129203600209.

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Using common household products is often difficult for people with neuromuscular disorders, spinal cord injury, or arthritis. We need to better understand their capabilities when designing and adapting products that are easier for them to use. In this study, individuals with movement impairments used two experimental home control thermostats with features that allowed easier positioning and viewing. The participants employed a variety of grasping and manipulation strategies, including some that were not anticipated by the designers. Participants' preferences indicated that the appearance of th

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