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Articles de revues sur le sujet « GRASPS model »

Auteur : Grafiati

Publié le 7 juin 2025

Mis à jour le 2 août 2025

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1

Zhang, Jiahao, Miao Li, Ying Feng, and Chenguang Yang. "Robotic grasp detection based on image processing and random forest." Multimedia Tools and Applications 79, no. 3-4 (2019): 2427–46. http://dx.doi.org/10.1007/s11042-019-08302-9.

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AbstractReal-time grasp detection plays a key role in manipulation, and it is also a complex task, especially for detecting how to grasp novel objects. This paper proposes a very quick and accurate approach to detect robotic grasps. The main idea is to perform grasping of novel objects in a typical RGB-D scene view. Our goal is not to find the best grasp for every object but to obtain the local optimal grasps in candidate grasp rectangles. There are three main contributions to our detection work. Firstly, an improved graph segmentation approach is used to do objects detection and it can separa

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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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Kopicki, Marek, Renaud Detry, Maxime Adjigble, Rustam Stolkin, Ales Leonardis, and Jeremy L. Wyatt. "One-shot learning and generation of dexterous grasps for novel objects." International Journal of Robotics Research 35, no. 8 (2015): 959–76. http://dx.doi.org/10.1177/0278364915594244.

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This paper presents a method for one-shot learning of dexterous grasps and grasp generation for novel objects. A model of each grasp type is learned from a single kinesthetic demonstration and several types are taught. These models are used to select and generate grasps for unfamiliar objects. Both the learning and generation stages use an incomplete point cloud from a depth camera, so no prior model of an object shape is used. The learned model is a product of experts, in which experts are of two types. The first type is a contact model and is a density over the pose of a single hand link rel

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Bounab, Belkacem, Abdenour Labed, and Daniel Sidobre. "Stochastic optimization-based approach for multifingered grasps synthesis." Robotica 28, no. 7 (2010): 1021–32. http://dx.doi.org/10.1017/s0263574709990889.

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SUMMARYIn this paper, we propose an approach for computing suboptimal grasps of polyhedral objects. Assuming n hard-finger contact with Coulomb friction model and based on central axes of the grasp wrench, we develop a new necessary and sufficient condition for n-finger grasps to achieve force-closure property. Accordingly, we reformulate the proposed force-closure test as a new linear programming problem, which we solve using an interior point method. Furthermore, we present an approach for finding appropriate stable grasps for a robotic hand on arbitrary objects. We use the simulated anneali

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Kopicki, Marek S., Dominik Belter, and Jeremy L. Wyatt. "Learning better generative models for dexterous, single-view grasping of novel objects." International Journal of Robotics Research 38, no. 10-11 (2019): 1246–67. http://dx.doi.org/10.1177/0278364919865338.

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This paper concerns the problem of how to learn to grasp dexterously, so as to be able to then grasp novel objects seen only from a single viewpoint. Recently, progress has been made in data-efficient learning of generative grasp models that transfer well to novel objects. These generative grasp models are learned from demonstration (LfD). One weakness is that, as this paper shall show, grasp transfer under challenging single-view conditions is unreliable. Second, the number of generative model elements increases linearly in the number of training examples. This, in turn, limits the potential

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Quarona, Davide, Atesh Koul, Caterina Ansuini, Luca Pascolini, Andrea Cavallo, and Cristina Becchio. "A kind of magic: Enhanced detection of pantomimed grasps in professional magicians." Quarterly Journal of Experimental Psychology 73, no. 7 (2020): 1092–100. http://dx.doi.org/10.1177/1747021820918533.

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Professional magicians regularly use pantomimed grasps (i.e., movements towards imagined objects) to deceive audiences. To do so, they learn to shape their hands similarly for real and pantomimed grasps. Here we tested whether this form of motor expertise provides them a significant benefit when processing pantomimed grasps. To this aim, in a one-interval discrimination design, we asked 17 professional magicians and 17 naïve controls to watch video clips of reach-to-grasp movements recorded from naïve participants and judge whether the observed movement was real or pantomimed. All video clips

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Guo, Di, Fuchun Sun, Tao Kong, and Huaping Liu. "Deep vision networks for real-time robotic grasp detection." International Journal of Advanced Robotic Systems 14, no. 1 (2016): 172988141668270. http://dx.doi.org/10.1177/1729881416682706.

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Grasping has always been a great challenge for robots due to its lack of the ability to well understand the perceived sensing data. In this work, we propose an end-to-end deep vision network model to predict possible good grasps from real-world images in real time. In order to accelerate the speed of the grasp detection, reference rectangles are designed to suggest potential grasp locations and then refined to indicate robotic grasps in the image. With the proposed model, the graspable scores for each location in the image and the corresponding predicted grasp rectangles can be obtained in rea

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Liu, Ziqi, Li Jiang, and Ming Cheng. "A Fast Grasp Planning Algorithm for Humanoid Robot Hands." Biomimetics 9, no. 10 (2024): 599. http://dx.doi.org/10.3390/biomimetics9100599.

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Grasp planning is crucial for robots to perform precision grasping tasks, where determining the grasp points significantly impacts the performance of the robotic hand. Currently, the majority of grasp planning methods based on analytic approaches solve the problem by transforming it into a nonlinear constrained planning problem. This method often requires performing convex hull computations, which tend to have high computational complexity. This paper proposes a new algorithm for calculating multi-finger force-closure grasps of three-dimensional objects based on humanoid multi-fingered hands.

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Kumra, Sulabh, Shirin Joshi, and Ferat Sahin. "GR-ConvNet v2: A Real-Time Multi-Grasp Detection Network for Robotic Grasping." Sensors 22, no. 16 (2022): 6208. http://dx.doi.org/10.3390/s22166208.

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We propose a dual-module robotic system to tackle the problem of generating and performing antipodal robotic grasps for unknown objects from the n-channel image of the scene. We present an improved version of the Generative Residual Convolutional Neural Network (GR-ConvNet v2) model that can generate robust antipodal grasps from n-channel image input at real-time speeds (20 ms). We evaluated the proposed model architecture on three standard datasets and achieved a new state-of-the-art accuracy of 98.8%, 95.1%, and 97.4% on Cornell, Jacquard and Graspnet grasping datasets, respectively. Empiric

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Starke, Julia, Christian Eichmann, Simon Ottenhaus, and Tamim Asfour. "Human-Inspired Representation of Object-Specific Grasps for Anthropomorphic Hands." International Journal of Humanoid Robotics 17, no. 02 (2020): 2050008. http://dx.doi.org/10.1142/s0219843620500085.

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The human hand is a complex, highly-articulated system, which has been the source of inspiration in designing humanoid robotic and prosthetic hands. Understanding the functionality of the human hand is crucial for the design, efficient control and transfer of human versatility and dexterity to such anthropomorphic robotic hands. Although research in this area has made significant advances, the synthesis of grasp configurations, based on observed human grasping data, is still an unsolved and challenging task. In this work we derive a novel, constrained autoencoder model, that encodes human gras

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Sauvet, Bruno, François Lévesque, SeungJae Park, Philippe Cardou, and Clément Gosselin. "Model-Based Grasping of Unknown Objects from a Random Pile." Robotics 8, no. 3 (2019): 79. http://dx.doi.org/10.3390/robotics8030079.

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Grasping an unknown object in a pile is no easy task for a robot—it is often difficult to distinguish different objects; objects occlude one another; object proximity limits the number of feasible grasps available; and so forth. In this paper, we propose a simple approach to grasping unknown objects one by one from a random pile. The proposed method is divided into three main actions—over-segmentation of the images, a decision algorithm and ranking according to a grasp robustness index. Thus, the robot is able to distinguish the objects from the pile, choose the best candidate for grasping amo

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Lenin Alvarez Llerena, Carlos. "Students’ Perceptions of Applying the GRASPS Framework from the Backward Design Model in Learning English as a Foreign Language." Language Teaching Research Quarterly 40 (April 2024): 129–46. http://dx.doi.org/10.32038/ltrq.2024.40.08.

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The present study investigates the students’ perceptions of applying performance tasks based on the GRASPS framework, exploring and seeking to explain the relationships between these tasks and English language learning. Data was collected over one semester in 14 public secondary schools in Ecuador, and it consisted of a questionnaire applied to 283 EFL students and two focus-group interviews with 12 EFL learners. After receiving a two-week workshop, sixteen Ecuadorian EFL teachers planned three units following the three stages based on the Backward Desing Model (Wiggings & McTigue, 2005);

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Bonaiuto, James, and Michael A. Arbib. "Learning to grasp and extract affordances: the Integrated Learning of Grasps and Affordances (ILGA) model." Biological Cybernetics 109, no. 6 (2015): 639–69. http://dx.doi.org/10.1007/s00422-015-0666-2.

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Ruiz, Jon Ander, Ander Iriondo, Elena Lazkano, Ander Ansuategi, and Iñaki Maurtua. "Physics-Based Self-Supervised Grasp Pose Detection." Machines 13, no. 1 (2024): 12. https://doi.org/10.3390/machines13010012.

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Current industrial robotic manipulators have made their lack of flexibility evident. The systems must know beforehand the piece and its position. To address this issue, contemporary approaches typically employ learning-based techniques, which rely on extensive amounts of data. To obtain vast data, an often sought tool is an extensive grasp dataset. This work introduces our Physics-Based Self-Supervised Grasp Pose Detection (PBSS-GPD) pipeline for model-based grasping point detection, which is useful for generating grasp pose datasets. Given a gripper-object pair, it samples grasping pose candi

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Omata, Toru. "An Algorithm for Computing Grasp Force Solutions in Power Grasps Considering Errors in Elastic Contact Model." Journal of the Robotics Society of Japan 21, no. 7 (2003): 794–801. http://dx.doi.org/10.7210/jrsj.21.794.

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Sinha, P. R., and J. M. Abel. "A contact stress model for multifingered grasps of rough objects." IEEE Transactions on Robotics and Automation 8, no. 1 (1992): 7–22. http://dx.doi.org/10.1109/70.127235.

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Shiferaw, Birhanemeskel Alamir, Tayachew F. Agidew, Ali Saeed Alzahrani, and Ramasamy Srinivasagan. "Synergistic Pushing and Grasping for Enhanced Robotic Manipulation Using Deep Reinforcement Learning." Actuators 13, no. 8 (2024): 316. http://dx.doi.org/10.3390/act13080316.

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In robotic manipulation, achieving efficient and reliable grasping in cluttered environments remains a significant challenge. This study presents a novel approach that integrates pushing and grasping actions using deep reinforcement learning. The proposed model employs two fully convolutional neural networks—Push-Net and Grasp-Net—that predict pixel-wise Q-values for potential pushing and grasping actions from heightmap images of the scene. The training process utilizes deep Q-learning with a reward structure that incentivizes both successful pushes and grasps, encouraging the robot to create

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Du, Yonghui, and Gary M. Bone. "OBJECT SHAPE EXPLORATION AND RECOGNITION IN 2D USING A TWO-FINGERED ROBOTIC HAND." Transactions of the Canadian Society for Mechanical Engineering 27, no. 4 (2004): 375–87. http://dx.doi.org/10.1139/tcsme-2003-0021.

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Exploration with a robotic hand is a method for measuring the shape and location of objects. This information may be used to recognize the object from a given set, or to generate a model of the object. A novel two-dimensional exploration method employing multiple wrapping grasps without tactile sensors is presented. An object shape model is produced from the finger position information. An efficient procedure for recognizing the object from a given reference set is presented. Experiments are conducted with a two-fingered robotic hand with five degrees-of-freedom. Objects with circular, square

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SAHA, Sushanta kumar, Takayoshi YAMADA, Nobuharu MIMURA, and Yasuyuki FUNAHASHI. "Stability Analysis of Frictionless Grasps with a Two-Dimensional Spring Model." JSME International Journal Series C 42, no. 4 (1999): 974–81. http://dx.doi.org/10.1299/jsmec.42.974.

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Hang, Jinglue, Xiangbo Lin, Tianqiang Zhu, et al. "DexFuncGrasp: A Robotic Dexterous Functional Grasp Dataset Constructed from a Cost-Effective Real-Simulation Annotation System." Proceedings of the AAAI Conference on Artificial Intelligence 38, no. 9 (2024): 10306–13. http://dx.doi.org/10.1609/aaai.v38i9.28897.

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Robot grasp dataset is the basis of designing the robot's grasp generation model. Compared with the building grasp dataset for Low-DOF grippers, it is harder for High-DOF dexterous robot hand. Most current datasets meet the needs of generating stable grasps, but they are not suitable for dexterous hands to complete human-like functional grasp, such as grasp the handle of a cup or pressing the button of a flashlight, so as to enable robots to complete subsequent functional manipulation action autonomously, and there is no dataset with functional grasp pose annotations at present. This paper dev

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Lázaro, Raquel, Margarita Vergara, Antonio Morales, and Ramón A. Mollineda. "Multimodal Deep Learning Model for Cylindrical Grasp Prediction Using Surface Electromyography and Contextual Data During Reaching." Biomimetics 10, no. 3 (2025): 145. https://doi.org/10.3390/biomimetics10030145.

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Grasping objects, from simple tasks to complex fine motor skills, is a key component of our daily activities. Our approach to facilitate the development of advanced prosthetics, robotic hands and human–machine interaction systems consists of collecting and combining surface electromyography (EMG) signals and contextual data of individuals performing manipulation tasks. In this context, the identification of patterns and prediction of hand grasp types is crucial, with cylindrical grasp being one of the most common and functional. Traditional approaches to grasp prediction often rely on unimodal

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Yoshikawa, T. "Virtual truss model for characterization of internal forces for multiple finger grasps." IEEE Transactions on Robotics and Automation 15, no. 5 (1999): 941–47. http://dx.doi.org/10.1109/70.795797.

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Schwan, Constanze, and Wolfram Schenck. "A three-step model for the detection of stable grasp points with machine learning." Integrated Computer-Aided Engineering 28, no. 4 (2021): 349–67. http://dx.doi.org/10.3233/ica-210659.

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Robotic grasping in dynamic environments is still one of the main challenges in automation tasks. Advances in deep learning methods and computational power suggest that the problem of robotic grasping can be solved by using a huge amount of training data and deep networks. Despite these huge accomplishments, the acceptance and usage in real-world scenarios is still limited. This is mainly due to the fact that the collection of the training data is expensive, and that the trained network is a black box. While the collection of the training data can sometimes be facilitated by carrying it out in

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Niu, Xun, Mark L. Latash, and Vladimir M. Zatsiorsky. "Prehension Synergies in the Grasps With Complex Friction Patterns: Local Versus Synergic Effects and the Template Control." Journal of Neurophysiology 98, no. 1 (2007): 16–28. http://dx.doi.org/10.1152/jn.00058.2007.

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We studied adjustments of digit forces to changes in the friction. The subjects held a handle statically in a three-digit grasp. The friction under each digit was either high or low, resulting in eight three-element friction sets (such grasps were coined the grasps with complex friction pattern). The total load was also manipulated. It was found that digit forces were adjusted not only to the supported load and local friction, but also to friction at other digits (synergic effects). When friction under a digit was low, its tangential force decreased and the normal force increased (local effect

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Bircher, Walter G., Andrew S. Morgan, and Aaron M. Dollar. "Complex manipulation with a simple robotic hand through contact breaking and caging." Science Robotics 6, no. 54 (2021): eabd2666. http://dx.doi.org/10.1126/scirobotics.abd2666.

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Humans use all surfaces of the hand for contact-rich manipulation. Robot hands, in contrast, typically use only the fingertips, which can limit dexterity. In this work, we leveraged a potential energy–based whole-hand manipulation model, which does not depend on contact wrench modeling like traditional approaches, to design a robotic manipulator. Inspired by robotic caging grasps and the high levels of dexterity observed in human manipulation, a metric was developed and used in conjunction with the manipulation model to design a two-fingered dexterous hand, the Model W. This was accomplished b

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ten Pas, Andreas, Marcus Gualtieri, Kate Saenko, and Robert Platt. "Grasp Pose Detection in Point Clouds." International Journal of Robotics Research 36, no. 13-14 (2017): 1455–73. http://dx.doi.org/10.1177/0278364917735594.

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Recently, a number of grasp detection methods have been proposed that can be used to localize robotic grasp configurations directly from sensor data without estimating object pose. The underlying idea is to treat grasp perception analogously to object detection in computer vision. These methods take as input a noisy and partially occluded RGBD image or point cloud and produce as output pose estimates of viable grasps, without assuming a known CAD model of the object. Although these methods generalize grasp knowledge to new objects well, they have not yet been demonstrated to be reliable enough

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Qiao, Shangling, Hongwei Guo, Rongqiang Liu, Yong Huang, and Zongquan Deng. "Self-adaptive grasp analysis of a novel under-actuated cable-truss robotic finger." Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science 233, no. 6 (2018): 2121–34. http://dx.doi.org/10.1177/0954406218779612.

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This paper presents the self-adaptive grasp of a novel cable-driven finger, which is an underactuated finger comprising cable-truss units. The underactuated cable-truss finger uses tendon-pulley transmission and parallel four-linkage mechanism to realize grasps. The working principle of the underactuated cable-truss finger and the self-adaptation at the grasp-closing stage are introduced. A self-adaptive grasping model is constructed to analyze the self-adaptation, and a new analysis method that considers the position and posture of grasping point in distal phalange is proposed. A new generali

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Huang, Xiaoqian, Rajkumar Muthusamy, Eman Hassan, et al. "Neuromorphic Vision Based Contact-Level Classification in Robotic Grasping Applications." Sensors 20, no. 17 (2020): 4724. http://dx.doi.org/10.3390/s20174724.

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In recent years, robotic sorting is widely used in the industry, which is driven by necessity and opportunity. In this paper, a novel neuromorphic vision-based tactile sensing approach for robotic sorting application is proposed. This approach has low latency and low power consumption when compared to conventional vision-based tactile sensing techniques. Two Machine Learning (ML) methods, namely, Support Vector Machine (SVM) and Dynamic Time Warping-K Nearest Neighbor (DTW-KNN), are developed to classify material hardness, object size, and grasping force. An Event-Based Object Grasping (EBOG)

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Astaño, Jereme Ll., and Ma. Lourdes M. Macasinag. "The use of engineering design process-oriented activities with GRASPS model integration in grade 11 Genetics." International Research Journal of Science, Technology, Education, and Management 5, no. 1 (2025): 1–22. https://doi.org/10.5281/zenodo.15192704.

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This study aimed to develop engineering design process (EDP)-oriented activities integrated with the GRASPS model and to evaluate their effects on students’ conceptual understanding and cognitive process skills. Likewise, this investigation documented the students' meaningful learning experiences during the implementation of EDP. Moreover, this study employed a mixed-methods approach and a one-group pretest-posttest design, with 36 Grade 11 STEM students as participants. The engineering design process-oriented activities were implemented over a six-week period, and data were gathered thr

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Wei, Cheng, Yue Zhang, Hongliu Wang, Yang Zhao, and Lei Zhang. "Inertia parameter identification of space floating target during robotic exploratory grasping." Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering 233, no. 11 (2019): 4247–60. http://dx.doi.org/10.1177/0954410018819567.

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When the space robot grasps an unknown floating target on orbit, it has many advantages of knowing the inertial parameters of the target during the exploratory grasping process, since, instead of grasping blindly the better control schema can be made in the meantime to increase the safety and performance of the grasping operation. The three-finger gripper is used as the grasp mechanism for which the grasping and contact models are presented to describe the grasping procedure. Then based on the momentum conservation of the robot–target system, the linear identification model of the target inert

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Kitamura, Koji, Yoshifumi Nishida, Naoaki Matsumoto, Yoichi Motomura, Tatsuhiro Yamanaka, and Hiroshi Mizoguchi. "Development of Infant Behavior Simulator: Modeling Grasping Achievement Based on Developmental Behavior Model and Environmental Interest Induction Model." Journal of Robotics and Mechatronics 17, no. 6 (2005): 705–16. http://dx.doi.org/10.20965/jrm.2005.p0705.

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Comprehensive understanding of infant behavior is required to prevent infant accidents in the home. We are developing a system to simulate infant behavior and accidents in virtual space to comprehensively understand infant behavior and accidents. We model infant grasping achievement in daily life, focusing on interaction with objects as a basic function of the infant behavior simulator we are developing. Grasping achievement refers to behavior in which an infant sees an object, approaches it, and grasps it. We classified elements related to infant behavior into developmental behavior, which is

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Ghafoor, Abdul, Jian S. Dai, and Joseph Duffy. "Stiffness Modeling of the Soft-Finger Contact in Robotic Grasping." Journal of Mechanical Design 126, no. 4 (2004): 646–56. http://dx.doi.org/10.1115/1.1758255.

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This paper investigates the soft-finger contact by presenting the contact with a set of line springs based on screw theory, reveals the rotational effects, and identifies the stiffness properties of the contact. An elastic model of a soft-finger contact is proposed and a generalized contact stiffness matrix is developed by applying the congruence transformation and by introducing stiffness mapping of the line springs in translational directions and rotational axes. The effective stiffnesses along these directions and axes are hence obtained and the rotational stiffnesses are revealed. This hel

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Baygin, Mehmet, Prabal Datta Barua, Sengul Dogan, et al. "A Hand-Modeled Feature Extraction-Based Learning Network to Detect Grasps Using sEMG Signal." Sensors 22, no. 5 (2022): 2007. http://dx.doi.org/10.3390/s22052007.

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Recently, deep models have been very popular because they achieve excellent performance with many classification problems. Deep networks have high computational complexities and require specific hardware. To overcome this problem (without decreasing classification ability), a hand-modeled feature selection method is proposed in this paper. A new shape-based local feature extractor is presented which uses the geometric shape of the frustum. By using a frustum pattern, textural features are generated. Moreover, statistical features have been extracted in this model. Textures and statistics featu

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Bazina, Tomislav, Goran Mauša, Saša Zelenika, and Ervin Kamenar. "Reducing Hand Kinematics by Introducing Grasp-Oriented Intra-Finger Dependencies." Robotics 13, no. 6 (2024): 82. http://dx.doi.org/10.3390/robotics13060082.

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Loss of hand functions, often manifesting in the form of weakness or spasticity from conditions like stroke or multiple sclerosis, poses challenges in performing activities of daily living (ADLs). The broad area of rehabilitation robotics provides the tools and knowledge necessary for implementing efficient restorative therapies. These therapies aim to improve hand functionality with minimal therapist intervention. However, the human hand evolved for various precision and power gripping tasks, with its intricate anatomy featuring a large number of degrees of freedom—up to 31—which hinder its m

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Jarque-Bou, Néstor J., Margarita Vergara, and Joaquín L. Sancho-Bru. "Estimation of the Abduction/Adduction Movement of the Metacarpophalangeal Joint of the Thumb." Applied Sciences 11, no. 7 (2021): 3158. http://dx.doi.org/10.3390/app11073158.

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Thumb opposition is essential for grasping, and involves the flexion and abduction of the carpometacarpal and metacarpophalangeal joints of the thumb. The high number of degrees of freedom of the thumb in a fairly small space makes the in vivo recording of its kinematics a challenging task. For this reason, along with the very limited independence of the abduction movement of the metacarpophalangeal joint, many devices do not implement sensors to measure such movement, which may lead to important implications in terms of the accuracy of thumb models. The aims of this work are to examine the co

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Hailperin-Lausch, Rebecca Elisabeth. "A proposed EEG study: the role of object affordance during action observation." IU Journal of Undergraduate Research 3, no. 1 (2017): 44–47. http://dx.doi.org/10.14434/iujur.v3i1.23356.

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Over the past two decades, research on the human mirror neuron system (MNS) has flourished. According to this model, there is substantial evidence that both action execution and action observation activate the motor system. However, to date, few studies have attempted to examine the role that object affordance may have during action observation. The proposed study attempts to assess this and other issues by having participants watch videos of an actor making goal-directed reaches to a common household object. In the congruent condition, the actor makes a reach and grasps the handle of a mug. I

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Strzelecki, Ryszard. "Model badania podmiotowej sfery kultury współczesnej." Dydaktyka Polonistyczna 16, no. 7 (2021): 7–29. http://dx.doi.org/10.15584/dyd.pol.16.2021.1.

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The aim of this paper is to establish a model for researching the subjective sphere of contemporary culture. In order to establish the methodological foundations of the model, some of the most important theories of man (biologistic, liberal and relationalistic personalism, Thomistic and metaphysical personalism, as well as Wojtyla within the so-called ”adequate anthropology” and Trinitarian personalism) have been used, presented, compared, and even critically evaluated. The aim of this confrontation is to choose a theory that fully grasps the ontological and axiological depth of man, a theory

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Zhu, Xiaofeng, Tiebin Guo, Xuesong Qi, Jia Sun, Xiaozhuo Guan, and Zhenxin Li. "Analysis and Optimization of the Impact of Distributed Generation Integration on Distribution Network Loss." Journal of Physics: Conference Series 2503, no. 1 (2023): 012084. http://dx.doi.org/10.1088/1742-6596/2503/1/012084.

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Abstract The distribution loss of the distribution network has changed greatly because of the access of distributed generation, which has a certain impact on the power quality of the distribution network. In order to solve the above problems, this paper constructs a 10 kV grid model containing distributed generation, studies the impact of distributed generation on the distribution of network loss, and grasps the characteristics of network loss changes under different scales of distributed generation and different grid-connected conditions. Finally, this paper constructs a mathematical model co

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Imran, Ali Khan, Naseem Muhammad, Ahmad Mubashir, Khan Azhar, Ali Khan Fahad, and Hassan Faisal. "Predicting Currency Moves (A Techno retrospective analysis)." International Journal of Case Studies 8, no. 3 (2019): 01–14. https://doi.org/10.5281/zenodo.3546924.

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The variation in the value of currency of any country with respect to foreign currencies like US $ is called Currency Fluctuation/Move. This study grasps the perception in regards to the Spot rates and forward rates relationship in different time dimensions and further the productivity with the Foreign exchange markets of Pakistan. The daily based information has been retrieved from State Bank of Pakistan, Business recorder, Yahoo finance and World Bank websites for the period 2001 to 2018 and additionally forward rates are utilized for various time measurements. During the research work the p

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Szécsi, Gábor. "Context, Intention and Historical Understanding." Belvedere Meridionale 31, no. 4 (2019): 5–12. http://dx.doi.org/10.14232/belv.2019.4.1.

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The aim of this article is to indicate how a version of intentionalist theory of linguistic communication can be adapted as a part of a contextualist methodology of the history of ideas. In other words, we attempt to clear up the way of harmonizing the theory that communication takes place when a hearer/reader grasps an utterer’s intention with the methodological conception according to which a historian of ideas must concentrate his attention on the context in which in his past author was writing. This article argues that a plausible solution to this problem is suggested in some influential m

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Alò, Roberta, and Giacomo Mantriota. "Optimal Grip Points with Human Hand." International Journal of Humanoid Robotics 13, no. 02 (2016): 1550036. http://dx.doi.org/10.1142/s021984361550036x.

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The aim of this work was to determine how an object of given shape should be grasped to maximize the grasping capacity of the human hand. To do that the model searches the optimal grip points on the object with the aim of maximizing the weight of the object lifted without slipping. The model solves both the equilibrium of the grasped object and the biomechanical constraints of the human hand, such as the stress limit of each muscle. To give some examples, grasps of three-dimensional (3D) objects of different shape and size were optimized. The results of the simulations done also allowed the id

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Xiong, Cai-Hua, Michael Yu Wang, Yong Tang, and You-Lun Xiong. "On the prediction of passive contact forces of workpiece-fixture systems." Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture 219, no. 3 (2005): 309–24. http://dx.doi.org/10.1243/095440505x30159.

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The prediction of passive forces in a frictional workpiece-fixture system is an important problem, since the contact forces have a strong influence on clamp design and on workpiece accuracy during machining. This paper presents a general method for the computation of passive contact forces. Firstly, an indeterminate system of static equilibrium is defined, in which the passive, frictional contact forces cannot be determined arbitrarily as in an actively controlled robotic multifinger grasp. Then, a locally elastic contact model is used to describe the non-linear coupling between the contact fo

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Molin, Jonas, and Lars-Johan Åge. "Business streamlining – an integrated model of service sourcing." Journal of Business & Industrial Marketing 32, no. 2 (2017): 194–205. http://dx.doi.org/10.1108/jbim-01-2015-0011.

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Purpose The purchasing of services is a significantly under-researched area. The purpose of this study is to suggest a conceptual model of service sourcing relationships, including the post-contract phase. Design/methodology/approach A qualitative methodology involving two longitudinal case studies that were analyzed with a grounded theory approach to build a conceptual model was applied. Findings The proposed model consists of a core process that is termed “business streamlining” and denotes the process by which four interrelated dimensions are managed to making the business processes of the

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Zhuang, Chungang, Haowen Wang, Wanhao Niu, and Han Ding. "A parallel graph network for generating 7-DoF model-free grasps in unstructured scenes using point cloud." Robotics and Computer-Integrated Manufacturing 92 (April 2025): 102879. http://dx.doi.org/10.1016/j.rcim.2024.102879.

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Sapaty, P. S. "Holistic spatial analysis of distributed worlds." Mathematical machines and systems 2 (2022): 3–18. http://dx.doi.org/10.34121/1028-9763-2022-2-3-18.

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The paper investigates extended applications of the developed spatial grasp model and technology for analyzing large distributed systems and environments, as well as some examples of solving typical problems in them in the Spatial Grasp Language (SGL). The Spatial Grasp (SG) paradigm allows solving complex problems in a holistic and fully distributed way. It develops in distributed spaces as active ubiquitous waves or even viruses and grasps solutions to spatial problems in parallel pattern-matching mode, fundamentally differing from traditional representations of systems and their solutions a

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Feng, Peiyuan. "Stranger Online Social Media Operation and Strategy: Case Study of Tantan App." Advances in Economics, Management and Political Sciences 4, no. 1 (2023): 331–37. http://dx.doi.org/10.54254/2754-1169/4/20221089.

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With the advancement of the Internet and technology, the types of social media software are constantly expanding. Recently, a new kind of social software has gradually emerged in the market. This is stranger dating software. Unlike Facebook, Instagram and WeChat, which are more used to communicate with familiar people, dating social software mainly aims to make friends with strangers. Its emergence is a change in the market. This article will analyze Tantan, the most popular dating software for strangers in the Chinese market, explore its development background, understand its business model,

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Saito, Naoki, Toshiyuki Satoh, Yoshinao Suzuki, and Hideharu Okano. "Placing Motion of an Object by a Robot Hand with a Flexible Sensor." Journal of Robotics and Mechatronics 24, no. 1 (2012): 28–36. http://dx.doi.org/10.20965/jrm.2012.p0028.

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We examine a placing motion of a grasped object by a robot hand equipped with a flexible sensor on the finger. The aim of this study is to realize a quick placing motion with a small impulse force between the object and the floor. To derive a dynamic model of the motion, we consider the deformation of the flexible sensor occurring when the hand grasps the object. The dynamic model represents the relation between the impulse force and an approaching trajectory of the robot hand to the floor. From this model, we can obtain the trajectory of the hand that ensures that the impact force is less tha

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Jang, Jaeyoung, and Jong Hyeon Park. "A Method of Estimating an Object’s Parameters Based on Simplication with Momentum for a Manipulator." Applied Sciences 15, no. 7 (2025): 3989. https://doi.org/10.3390/app15073989.

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For a manipulator to estimate an object’s inertial parameters—such as mass, center of mass position, and elements of the inertia tensor—it must grasp one side of the object and generate motion while utilizing the resulting forces and torques at its end-effector for estimation. In most previous studies, the estimation motion has involved high acceleration, resulting in larger motion trajectories and increased inertial forces. A larger trajectory raises the risk of collisions, while greater inertial forces could potentially damage the object. This paper introduces an innovative approach that sim

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Yin, Fulian, Xinyi Tang, Tongyu Liang, Yanjing Huang, and Jianhong Wu. "External intervention model with direct and indirect propagation behaviors on social media platforms." Mathematical Biosciences and Engineering 19, no. 11 (2022): 11380–98. http://dx.doi.org/10.3934/mbe.2022530.

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<abstract> <p>A significant distinction between the COVID-19 pandemic and previous pandemics is the significant role of social media platforms in shaping public adherence to non-pharmaceutical interventions and vaccine acceptance. However, with the recurrence of the epidemic, the conflict between epidemic prevention and production recovery has become increasingly prominent on social media. To help design effective communication strategies to guide public opinion, we propose a susceptible-forwarding-immune pseudo-environment (SFI-PE) dynamic model for understanding the environment w

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Lv, Jie. "Digital Economy and Urban Carbon Emissions in China: An Empirical Study Based on The Spatial Dubin Model." Frontiers in Business, Economics and Management 8, no. 1 (2023): 243–48. http://dx.doi.org/10.54097/fbem.v8i1.6221.

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Starting from the Chinese city level, combined with the panel data of 281 cities in China from 2011 to 2019, this paper empirically examines the spatial impact of digital economy development on urban carbon emissions, and the results show that there is a significant spatial dependence and spatial spillover effect between digital economy and urban carbon emissions, and the region-wide inspection finds that the digital economy shows a significant promotion effect on local carbon emission levels, while the adjacent effect of digital economy shows "U" shaped characteristics. There is a "U" shaped

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