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Journal articles on the topic 'Grasp point'

Author: Grafiati

Published: 4 June 2021

Last updated: 8 February 2022

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1

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 (October 30, 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 for wide use. Many grasp detection methods achieve grasp success rates (grasp successes as a fraction of the total number of grasp attempts) between 75% and 95% for novel objects presented in isolation or in light clutter. Not only are these success rates too low for practical grasping applications, but the light clutter scenarios that are evaluated often do not reflect the realities of real-world grasping. This paper proposes a number of innovations that together result in an improvement in grasp detection performance. The specific improvement in performance due to each of our contributions is quantitatively measured either in simulation or on robotic hardware. Ultimately, we report a series of robotic experiments that average a 93% end-to-end grasp success rate for novel objects presented in dense clutter.

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2

Zapata-Impata, Brayan S., Pablo Gil, Jorge Pomares, and Fernando Torres. "Fast geometry-based computation of grasping points on three-dimensional point clouds." International Journal of Advanced Robotic Systems 16, no. 1 (January 1, 2019): 172988141983184. http://dx.doi.org/10.1177/1729881419831846.

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Industrial and service robots deal with the complex task of grasping objects that have different shapes and which are seen from diverse points of view. In order to autonomously perform grasps, the robot must calculate where to place its robotic hand to ensure that the grasp is stable. We propose a method to find the best pair of grasping points given a three-dimensional point cloud with the partial view of an unknown object. We use a set of straightforward geometric rules to explore the cloud and propose grasping points on the surface of the object. We then adapt the pair of contacts to a multi-fingered hand used in experimentation. We prove that, after performing 500 grasps of different objects, our approach is fast, taking an average of 17.5 ms to propose contacts, while attaining a grasp success rate of 85.5%. Moreover, the method is sufficiently flexible and stable to work with objects in changing environments, such as those confronted by industrial or service robots.

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3

Kleinholdermann, U., V. H. Franz, and K. R. Gegenfurtner. "Human grasp point selection." Journal of Vision 13, no. 8 (July 25, 2013): 23. http://dx.doi.org/10.1167/13.8.23.

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4

Pollick, F. E., and J. S. Tittle. "Grasping Stereo and Texture Cue Combinations." Perception 25, no. 1_suppl (August 1996): 121. http://dx.doi.org/10.1068/v96p0205.

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Studies of grasp indicate that the reach-to-grasp movement is essentially preprogrammed and relies heavily on estimates of object geometry provided by vision. Moreover, computational analyses of two-point grasps suggest that the identification of pairs of grasp points requires extensive computation of surface geometry. Thus, one can view subjects' decisions of how to obtain a stable two-point grasp as a good indicator of the perceptuo-motor system's appreciation of surface structure. We probe this perceptuo-motor surface representation by examining grasps to ellipsoidal surfaces defined by the cues of texture and horizontal disparity under independent levels of noise added to both texture and stereo. Subjects viewed the sequential presentation of left and right images on a computer display through liquid-crystal shutter glasses and were instructed to perform either an overhand or underhand grasp to the presented virtual ellipsoid. The virtual ellipsoid was oriented with its long axis in the horizontal plane. Rotation in depth about a vertical axis was varied between trials by a staircase procedure, which obtained the orientation at which overhand and underhand grasps were equally likely as well as the differential threshold. Results showed that the differential thresholds were a few degrees for the zero noise condition and increased with the addition of noise. These results are discussed in terms of theories of cue combination and perception for action.

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5

Wang, Xiaoman, Xin Jiang, Jie Zhao, Shengfan Wang, Tao Yang, and Yunhui Liu. "Picking Towels in Point Clouds." Sensors 19, no. 3 (February 10, 2019): 713. http://dx.doi.org/10.3390/s19030713.

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Picking clothing has always been a great challenge in laundry or textile industry automation, especially when some clothes are of the same colors, material and entangled with each other. In order to solve the problem, we present a grasp pose determination method to pick towels placed in a laundry basket or on a table. In our method, it is not needed to segment towels into independent items and the target towels are not necessarily distinguishable in color. The proposed algorithm firstly segments point clouds into several convex wrinkles, and then selects the appropriate grasp point on the candidate convex wrinkle. Moreover, we plan the grasp orientation with respect to the wrinkle which can effectively reduce the grasp failure caused by the inappropriate grasp direction. We evaluate our method on picking white towels and square towels, respectively, and achieved an average success rate of about 80%.

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6

Kanoulas, Dimitrios, Jinoh Lee, Darwin G. Caldwell, and Nikos G. Tsagarakis. "Visual Grasp Affordance Localization in Point Clouds Using Curved Contact Patches." International Journal of Humanoid Robotics 14, no. 01 (March 2017): 1650028. http://dx.doi.org/10.1142/s0219843616500286.

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Detecting affordances on objects is one of the main open problems in robotic manipulation. This paper presents a new method to represent and localize grasp affordances as bounded curved contact patches (paraboloids) of the size of the robotic hand. In particular, given a three-dimensional (3D) point cloud from a range sensor, a set of potential grasps is localized on a detected object by a fast contact patch fitting and validation process. For the object detection, three standard methods from the literature are used and compared. The potential grasps on the object are then refined to a single affordance using their shape (size and curvature) and pose (reachability and minimum torque effort) properties, with respect to the robot and the manipulation task. We apply the proposed method to a circular valve turning task, verifying the ability to accurately and rapidly localize grasp affordances, under significant uncertainty in the environment. We experimentally validate the method with the humanoid robot COMAN on 10 circular control valves fixed on a wall, from five different viewpoints and robot poses for each valve. We compare the reliability of the introduced local grasp affordances method to the baseline that relies only on object detection, illustrating the superiority of ours for the valve turning task.

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7

Funahashi, Yasuyuki, and Masahiro Tate. "Contact Point Identification in Enveloping Grasp." Transactions of the Japan Society of Mechanical Engineers Series C 61, no. 583 (1995): 1015–20. http://dx.doi.org/10.1299/kikaic.61.1015.

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8

Watcharawisetkul, Watcharapol, Mana Borwornpadungkitti, Nattee Niparnan, and Attawith Sudsang. "A Randomized Approach in Identifying High Quality Force Closure Grasp from Contact Points in Real Time." Applied Mechanics and Materials 781 (August 2015): 483–86. http://dx.doi.org/10.4028/www.scientific.net/amm.781.483.

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We proposed a randomized algorithm that can effectively identify a large number of high quality force closure grasps in short time. This task is very important when we consider grasping in real time where a large number of force closure grasps are needed as a candidate for planning in higher level. The key idea of our method is that a concurrent grasp is usually a high quality grasp and a concurrent grasp can be quickly identified by providing heuristic in choosing a concurrent point. A comparison of our method with other methods was performed and the result indicates that our method outperforms other methods.

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9

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 (August 27, 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 simulation, the trained networks, however, remain a black box. In this study, a three-step model is presented that profits both from the advantages of using a simulation approach and deep neural networks to identify and evaluate grasp points. In addition, it even offers an explanation for failed grasp attempts. The first step is to find all grasp points where the gripper can be lowered onto the table without colliding with the object. The second step is to determine, for the grasp points and gripper parameters from the first step, how the object moves while the gripper is closed. Finally, in the third step, for all grasp points from the second step, it is predicted whether the object slips out of the gripper during lifting. By this simplification, it is possible to understand for each grasp point why it is stable and – just as important – why others are unstable or not feasible. All of the models employed in each of the three steps and the resulting Overall Model are evaluated. The predicted grasp points from the Overall Model are compared to the grasp points determined analytically by a force-closure algorithm, to validate the stability of the predicted grasps.

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10

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 (September 18, 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 relative to the local object surface. The second type is the hand-configuration model and is a density over the whole-hand configuration. Grasp generation for an unfamiliar object optimizes the product of these two model types, generating thousands of grasp candidates in under 30 seconds. The method is robust to incomplete data at both training and testing stages. When several grasp types are considered the method selects the highest-likelihood grasp across all the types. In an experiment, the training set consisted of five different grasps and the test set of 45 previously unseen objects. The success rate of the first-choice grasp is 84.4% or 77.7% if seven views or a single view of the test object are taken, respectively.

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11

Kleinholdermann, U., K. R. Gegenfurtner, and V. H. Franz. "A model on human grasp point selection." Journal of Vision 9, no. 8 (March 21, 2010): 1100. http://dx.doi.org/10.1167/9.8.1100.

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12

Endo, Satoshi, Alan M. Wing, and R. Martyn Bracewell. "Haptic and Visual Influences on Grasp Point Selection." Journal of Motor Behavior 43, no. 6 (November 2011): 427–31. http://dx.doi.org/10.1080/00222895.2011.621996.

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13

Lederman, Susan J., and Alan M. Wing. "Perceptual judgement, grasp point selection and object symmetry." Experimental Brain Research 152, no. 2 (September 1, 2003): 156–65. http://dx.doi.org/10.1007/s00221-003-1522-5.

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14

Zheng, Yu. "Computing the best grasp in a discrete point set with wrench-oriented grasp quality measures." Autonomous Robots 43, no. 4 (July 19, 2018): 1041–62. http://dx.doi.org/10.1007/s10514-018-9788-4.

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15

Li, Tong, Fei Wang, Changlei Ru, Yong Jiang, and Jinghong Li. "Keypoint-Based Robotic Grasp Detection Scheme in Multi-Object Scenes." Sensors 21, no. 6 (March 18, 2021): 2132. http://dx.doi.org/10.3390/s21062132.

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Robot grasping is an important direction in intelligent robots. However, how to help robots grasp specific objects in multi-object scenes is still a challenging problem. In recent years, due to the powerful feature extraction capabilities of convolutional neural networks (CNN), various algorithms based on convolutional neural networks have been proposed to solve the problem of grasp detection. Different from anchor-based grasp detection algorithms, in this paper, we propose a keypoint-based scheme to solve this problem. We model an object or a grasp as a single point—the center point of its bounding box. The detector uses keypoint estimation to find the center point and regress to all other object attributes such as size, direction, etc. Experimental results demonstrate that the accuracy of this method is 74.3% in the multi-object grasp dataset VMRD, and the performance on the single-object scene Cornell dataset is competitive with the current state-of-the-art grasp detection algorithm. Robot experiments demonstrate that this method can help robots grasp the target in single-object and multi-object scenes with overall success rates of 94% and 87%, respectively.

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16

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 (July 1, 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 helps create a screw representation of a six-dimensional soft-finger contact and produce an approach of analyzing and synthesizing a robotic grasp without resorting to the point contact representation. The correlation between the rotational stiffness, the number of equivalent point contacts and the number of equivalent contours is given and the stiffness synthesis is presented with both modular and direct approaches. The grasp thus achieved from the stiffness analysis contributes to both translational and rotational restraint and the stiffness matrix so developed is proven to be symmetric and positive definite. Case studies are presented with a two-soft-finger grasp and a three-soft-finger grasp. The grasps are analyzed with a general stiffness matrix which is used to control the fine displacements of a grasped object by changing the preload on the contact.

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17

Liu, H. W., and C. Q. Cao. "Grasp Pose Detection Based On Point Cloud Shape Simplification." IOP Conference Series: Materials Science and Engineering 717 (January 3, 2020): 012007. http://dx.doi.org/10.1088/1757-899x/717/1/012007.

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18

Monica, Riccardo, and Jacopo Aleotti. "Point Cloud Projective Analysis for Part-Based Grasp Planning." IEEE Robotics and Automation Letters 5, no. 3 (July 2020): 4695–702. http://dx.doi.org/10.1109/lra.2020.3003883.

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19

Funahashi, Yasuyuki, and Masahiro Tate. "Contact Point Identification by Active Sensing in Enveloping Grasp." Transactions of the Japan Society of Mechanical Engineers Series C 61, no. 589 (1995): 3607–13. http://dx.doi.org/10.1299/kikaic.61.3607.

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20

Ghafoor, A., and D. R. Kerr. "In-Grasp Robotic Fine Motion with Frictionless Elastic Point Contacts." Proceedings of the Institution of Mechanical Engineers, Part C: Mechanical Engineering Science 206, no. 1 (January 1992): 41–47. http://dx.doi.org/10.1243/pime_proc_1992_206_093_02.

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This paper discusses the form-closure robotic grasping of a rigid object and shows how fine motion of the grasped object may be induced. Preloads are applied along point contacts, a knowledge of whose elastic properties are necessary to overcome statical indeterminacy in the grasp, and whose properties can be exploited to allow the induced fine motion. Appropriate values of these preloads can be derived so as to maintain the grasp against external loads and to induce predefined fine motion to the object. Where a defined fine motion cannot be exactly induced, a best approximation can be found. The analytical approach is supported with examples.

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21

Weiss, P., and M. Jeannerod. "Getting a Grasp on Coordination." Physiology 13, no. 2 (April 1998): 70–75. http://dx.doi.org/10.1152/physiologyonline.1998.13.2.70.

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Motor coordination is realized by the nervous system at different levels. Concepts about the coordination within a limb define the controlled parameter in cartesian or joint space, whereas concepts about the coordination between limbs stress the temporal control of schemas. Motor deficits of neurological patients point to the role of the different motor areas in motor coordination.

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22

Guo, Ning, Baohua Zhang, Jun Zhou, Ketian Zhan, and Shuang Lai. "Pose estimation and adaptable grasp configuration with point cloud registration and geometry understanding for fruit grasp planning." Computers and Electronics in Agriculture 179 (December 2020): 105818. http://dx.doi.org/10.1016/j.compag.2020.105818.

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23

Wang, Xixun, Sajid Nisar, and Fumitoshi Matsuno. "Robust grasp detection with incomplete point cloud and complex background." Advanced Robotics 35, no. 10 (March 10, 2021): 619–34. http://dx.doi.org/10.1080/01691864.2021.1897674.

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24

HASEGAWA, Tomoki, and Nobuharu MIMURA. "Study of Stable Grasp Contact Point Slip Using Internal Stiffness." Proceedings of the Symposium on sports and human dynamics 2020 (2020): C—1–1. http://dx.doi.org/10.1299/jsmeshd.2020.c-1-1.

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25

Duemmler, Thomas, Petra Schoeberl, and Gudrun Schwarzer. "Development of visual center of mass localization for grasp point selection." Cognitive Development 23, no. 3 (July 2008): 370–84. http://dx.doi.org/10.1016/j.cogdev.2008.06.002.

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26

Volcic, R., and F. Domini. "Adaptation of reach-to-point movements changes reach-to-grasp actions." Journal of Vision 13, no. 9 (July 25, 2013): 338. http://dx.doi.org/10.1167/13.9.338.

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27

Posy, Carl. "Intuition and Infinity: A Kantian Theme with Echoes in the Foundations of Mathematics." Royal Institute of Philosophy Supplement 63 (October 2008): 165–93. http://dx.doi.org/10.1017/s135824610800009x.

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Kant says patently conflicting things about infinity and our grasp of it. Infinite space is a good case in point. In his solution to the First Antinomy, he denies that we can grasp the spatial universe as infinite, and therefore that this universe can be infinite; while in the Aesthetic he says just the opposite: ‘Space is represented as a given infinite magnitude’(A25/B39). And he rests these upon consistently opposite grounds. In the Antinomy we are told that we can have no intuitive grasp of an infinite space, and in the Aesthetic he says that our grasp of infinite space is precisely intuitive.

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28

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 (June 27, 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 generalized coordinate, which directly shows the contacting position and the relative angular displacement in the distal phalange, is established. The expression of general static grasping force is established by using the virtual work principle, which reveals the relationship among the driving force, the equivalent torques on joints and the grasping forces. The workspace of the underactuated cable-truss finger and distributions of grasping force in new generalized coordinate are assessed through numerical analysis. The balance conditions of the self-adaptive grasp and the corresponding statuses are theoretically illustrated. Valid and adequate self-adaptive grasping experiments are conducted to verify the accuracy of self-adaptive grasping analysis.

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29

Campanella, Francesco, Giulio Sandini, and Maria Concetta Morrone. "Visual information gleaned by observing grasping movement in allocentric and egocentric perspectives." Proceedings of the Royal Society B: Biological Sciences 278, no. 1715 (December 8, 2010): 2142–49. http://dx.doi.org/10.1098/rspb.2010.2270.

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One of the major functions of vision is to allow for an efficient and active interaction with the environment. In this study, we investigate the capacity of human observers to extract visual information from observation of their own actions, and those of others, from different viewpoints. Subjects discriminated the size of objects by observing a point-light movie of a hand reaching for an invisible object. We recorded real reach-and-grasp actions in three-dimensional space towards objects of different shape and size, to produce two-dimensional ‘point-light display’ movies, which were used to measure size discrimination for reach-and-grasp motion sequences, release-and-withdraw sequences and still frames, all in egocentric and allocentric perspectives. Visual size discrimination from action was significantly better in egocentric than in allocentric view, but only for reach-and-grasp motion sequences: release-and-withdraw sequences or still frames derived no advantage from egocentric viewing. The results suggest that the system may have access to an internal model of action that contributes to calibrate visual sense of size for an accurate grasp.

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30

Bounab, Belkacem, Abdenour Labed, and Daniel Sidobre. "Stochastic optimization-based approach for multifingered grasps synthesis." Robotica 28, no. 7 (January 18, 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 annealing technique for synthesizing suboptimal grasps of 3D objects. Through numerical simulations on arbitrary shaped objects, we show that the proposed approach is able to compute good grasps for multifingered hands within a reasonable computational time.

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31

Xiong, Youlun, Han Ding, and Michael Yu Wang. "Quantitative Analysis of Inner Force Distribution and Load Capacity of Grasps and Fixtures." Journal of Manufacturing Science and Engineering 124, no. 2 (April 29, 2002): 444–55. http://dx.doi.org/10.1115/1.1459089.

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This paper focuses on a quantitative analysis for grasp planning and fixture design based on an analytical description of point contact restraint. In the framework, the analysis deals with the fundamental concepts of restraint cone, freedom cone, force-determinacy and relative form closure. A method is presented to quantify the performance of a fixture (or grasp) with two major characteristics of inner force distribution and load capacity. Two different fixturing (or grasp) models of simplex grasp and elastic grasp are presented. It is shown that the performance of these two types of grasp (or fixturing) could be measured with different performance indices. A minimax index (MMI) and a volume measure are defined for evaluating a simplex grasp, while a measure using the tolerable range of differential motion in the twist space or the allowable load polyhedron in the wrench space would be suitable for quantifying robustness and load capability of an elastic fixture system. Furthermore, for fixture system design a geometric analysis and reasoning procedure is described for the design of locators, clamps and supplementary supports. The aim of these proposed analysis and design techniques is to provide a scientific foundation for automated grasping/fixturing system design in the engineering practice.

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32

Wroblewski, Dariusz, Brian A. Francis, Alfredo Sadun, Ghazal Vakili, and Vikas Chopra. "Testing of Visual Field with Virtual Reality Goggles in Manual and Visual Grasp Modes." BioMed Research International 2014 (2014): 1–10. http://dx.doi.org/10.1155/2014/206082.

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Automated perimetry is used for the assessment of visual function in a variety of ophthalmic and neurologic diseases. We report development and clinical testing of a compact, head-mounted, and eye-tracking perimeter (VirtualEye) that provides a more comfortable test environment than the standard instrumentation. VirtualEye performs the equivalent of a full threshold 24-2 visual field in two modes: (1) manual, with patient response registered with a mouse click, and (2) visual grasp, where the eye tracker senses change in gaze direction as evidence of target acquisition. 59 patients successfully completed the test in manual mode and 40 in visual grasp mode, with 59 undergoing the standard Humphrey field analyzer (HFA) testing. Large visual field defects were reliably detected by VirtualEye. Point-by-point comparison between the results obtained with the different modalities indicates: (1) minimal systematic differences between measurements taken in visual grasp and manual modes, (2) the average standard deviation of the difference distributions of about 5 dB, and (3) a systematic shift (of 4–6 dB) to lower sensitivities for VirtualEye device, observed mostly in high dB range. The usability survey suggested patients’ acceptance of the head-mounted device. The study appears to validate the concepts of a head-mounted perimeter and the visual grasp mode.

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33

Liu, Gaoxuan, Jiaoyan Ai, Jun Xu, Jianwu Zheng, and Dongyi Yao. "Monitoring point optimization in lake waters." Water Supply 20, no. 6 (July 3, 2020): 2348–58. http://dx.doi.org/10.2166/ws.2020.147.

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Abstract In order to grasp the distribution of water quality index in lake water, taking Jinghu Lake of Guangxi University as the experimental object, an radial basis function (RBF) neural network was combined with a genetic algorithm on the basis of an unmanned ship to study the optimal selection of monitoring points. The single-objective and multi-objective optimization of water quality parameters were tested respectively and used to make the fitting distribution map. The results show that the genetic neural network has obvious advantages over the traditional isometric monitoring in the distribution error of water quality parameters, and the data reflected by the results are still accurate and effective at least six weeks after optimization. The results show that a genetic neural network can significantly improve the efficiency of water quality monitoring.

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34

Golubev, Yu F., and E. V. Melkumova. "Transfer by a Manipulator with a Three-finger Grasp of a Brittle Cylinder." Multiphase Systems 14, no. 3 (2019): 202–7. http://dx.doi.org/10.21662/mfs2019.3.026.

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We consider the problem of the brittle cylinder grasping by the n fingers of the robot-manipulator. Each finger contacts the cylinder in a single supporting point with Amontons-Coulomb or for two footholds spinning friction. Using numerical simulations and analytically, possible locations of contact points on the cylinder, for which there is a kinetostatics problem solution when the cylinder is moved by three fingers, are received. By the analogy of the equilibrium of a three-legged robot on a cylinder for the problems of transfer by a manipulator with a three-finger grasp of a cylinder or for a robot on a surface which legs suspension points are on a cylinder surface. Two supporting points can be on one diameter in the cylinder base. Or because of friction on the opposite sides of the robot center of mass or giving in the dynamics, it is point C. The analogy of the problem is oscillations in the vicinity of the stable equilibrium one cylinder on another. The cylinder lies on one finger rectangular to it, of the hand of a hu-manoid robot, adheres to the end of the other finger. Similarly holds the glass. Robot can hold the horizontal cylinder by three fingers. Let one of the points is in vertical plane containing cylinder axis and another are in the plane orthogonal to the axis. The supporting points are on the external surface of the lower semi-cylinder and the cylinder center mass is in the footholds triangle. The supporting set is divided into two subsets.

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35

Jiang, Ping, Yoshiyuki Ishihara, Nobukatsu Sugiyama, Junji Oaki, Seiji Tokura, Atsushi Sugahara, and Akihito Ogawa. "Depth Image–Based Deep Learning of Grasp Planning for Textureless Planar-Faced Objects in Vision-Guided Robotic Bin-Picking." Sensors 20, no. 3 (January 28, 2020): 706. http://dx.doi.org/10.3390/s20030706.

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Bin-picking of small parcels and other textureless planar-faced objects is a common task at warehouses. A general color image–based vision-guided robot picking system requires feature extraction and goal image preparation of various objects. However, feature extraction for goal image matching is difficult for textureless objects. Further, prior preparation of huge numbers of goal images is impractical at a warehouse. In this paper, we propose a novel depth image–based vision-guided robot bin-picking system for textureless planar-faced objects. Our method uses a deep convolutional neural network (DCNN) model that is trained on 15,000 annotated depth images synthetically generated in a physics simulator to directly predict grasp points without object segmentation. Unlike previous studies that predicted grasp points for a robot suction hand with only one vacuum cup, our DCNN also predicts optimal grasp patterns for a hand with two vacuum cups (left cup on, right cup on, or both cups on). Further, we propose a surface feature descriptor to extract surface features (center position and normal) and refine the predicted grasp point position, removing the need for texture features for vision-guided robot control and sim-to-real modification for DCNN model training. Experimental results demonstrate the efficiency of our system, namely that a robot with 7 degrees of freedom can pick randomly posed textureless boxes in a cluttered environment with a 97.5% success rate at speeds exceeding 1000 pieces per hour.

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Zhang, Jiu Mei. "Analysis of Human-Machine Design of Hand-Grasp Apparatus." Advanced Materials Research 823 (October 2013): 96–99. http://dx.doi.org/10.4028/www.scientific.net/amr.823.96.

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Hand-held tools for the main object of study, start with the classification of the analysis of hand tools, specifically talking about the hand-held tools, human-machine design factors, including the two major aspects:1.Starting from the perspective of the"human" and point out that the hand structure of the human body, including muscle and bone structure is hand tools most closely the human-machine design factors. 2.From the "Tools" point of view, pointed out that product-related factors include the size and shape is the most important human-machine design factors of hand-held tool. Finally, hand tools must be designed to transfer to the center of the design and products of common concern, human-centered design will bring new design ideas and methods to hand-held tool designed. So ergonomics in the design of handheld products have broad application prospects.

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Marotta, Jonathan J., Gerald P. Keith, and J. Douglas Crawford. "Task-Specific Sensorimotor Adaptation to Reversing Prisms." Journal of Neurophysiology 93, no. 2 (February 2005): 1104–10. http://dx.doi.org/10.1152/jn.00859.2004.

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We tested between three levels of visuospatial adaptation (global map, parallel feature modules, and parallel sensorimotor transformations) by training subjects to reach and grasp virtual objects viewed through a left-right reversing prism, with either visual location or orientation feedback. Even though spatial information about the global left-right reversal was present in every training session, subjects trained with location feedback reached to the correct location but with the wrong (reversed) grasp orientation. Subjects trained with orientation feedback showed the opposite pattern. These errors were task-specific and not feature-specific; subjects trained to correctly grasp visually reversed–oriented bars failed to show knowledge of the reversal when asked to point to the end locations of these bars. These results show that adaptation to visuospatial distortion—even global reversals—is implemented through learning rules that operate on parallel sensorimotor transformations (e.g., reach vs. grasp).

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Hunt, K. H., and L. E. Torfason. "A Three-Fingered Pantograph Manipulator—A Kinematic Study." Journal of Mechanisms, Transmissions, and Automation in Design 109, no. 2 (June 1, 1987): 171–77. http://dx.doi.org/10.1115/1.3267432.

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General kinematic principles are set down for an algorithmically-simple three-fingered robot-attachment intended to grasp and manipulate objects. After proposing a design for a finger-tip that determines precisely a grasping-point, the geometry of a swivelling pantograph-arrangement is pursued in some detail. Forward and inverse relations are developed, and a means for maintaining grasp during manipulation is outlined. Force-sensing and driving-means are touched upon. Certain alternative schematic designs are presented and compared.

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Fulvi, Daniele. "The Ontological Nature of Intuition in Schelling." Idealistic Studies 50, no. 1 (2020): 1–17. http://dx.doi.org/10.5840/idstudies202039111.

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In this paper, I focus on the concept of intuition (Anschauung) in Schelling’s philosophy. More specifically, I show how Schelling attributes to intuition an ontological value by essentially relating it to freedom and primal Being (Ursein). Indeed, for Schelling intuition is both the main instrument of philosophy and the highest product of freedom, by which we attain the so-called “God’s-eye point of view” and concretely grasp things in their immediate existence. That is, through intuition it is possible to grasp the absolute and original unity of the principles, namely of being and thought, subject and object and freedom and necessity. Accordingly, I argue that Schelling’s conception of intuition, rather being a merely theoretical speculation, is aimed at demonstrating the immanent nature of Being, which is one of the key points in Schelling’s philosophy.

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Durouchoux, Ph, G. Bignami, A. Dean, N. Lund, B. McBreen, V. Schonfelder, B. Swanenburg, G. Vedrenne, and C. Winkler. "Mapping the Galactic Center Region with GRASP." Symposium - International Astronomical Union 136 (1989): 633–37. http://dx.doi.org/10.1017/s0074180900187133.

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The GRASP mission (Gamma-ray Astronomy with Spectroscopy and Positioning) is currently under study as an ESA space astronomy mission to be launched in the mid 90's. GRASP is designed as a high quality spectral imager (E/ΔE ≈ 500 at 1 Mev) with positioning to the arc minute level within a large field of view (≈7°) which operates over a wide spectral range (30 Kev-100 Mev) with a 3σ sensitivity of typically 10 mcrab or better over the entire operational range within an observational period of ≈105 seconds. In this paper, we will mainly discuss the capability of the instrument with respect to the study of both point source and diffuse source measurements of the galactic center region.

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Semasinghe, C. L., R. K. P. S. Ranaweera, J. L. B. Prasanna, H. M. Kandamby, D. G. K. Madusanka, and R. A. R. C. Gopura. "HyPro: A Multi-DoF Hybrid-Powered Transradial Robotic Prosthesis." Journal of Robotics 2018 (2018): 1–15. http://dx.doi.org/10.1155/2018/8491073.

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This paper proposes a multi-DoF hybrid-powered transradial robotic prosthesis, named HyPro. The HyPro consists of two prosthetic units: hand and wrist that can achieve five grasping patterns such as power grasp, tip grasp, lateral grasp, hook grasp, and index point. It is an underactuated device with 15 degrees of freedom. A hybrid powering concept is proposed and implemented on hand unit of HyPro where the key focus is on restoration of grasp functions of biological hand. A novel underactuated mechanism is introduced to achieve the required hand preshaping for a given grasping pattern using electric power in the pregrasp stage and body power is used in grasp stage to execute the final grasping action with the selected fingers. Unlike existing hybrid prostheses where each of the joints is separately controlled by either electric or body power, the proposed prosthesis is capable of delivering grasping power in combination. The wrist unit of HyPro is designed and developed to achieve flexion-extension and supination-pronation using electric power. Experiments were carried out to evaluate the functionality and performance of the proposed hybrid-powered robotic prosthesis. The results verified the potential of HyPro to perform intended grasping patterns effectively and efficiently.

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Santamaría, José, Oscar Cordón, Sergio Damas, Rafael Martí, and Ricardo J. Palma. "GRASP and path relinking hybridizations for the point matching-based image registration problem." Journal of Heuristics 18, no. 1 (April 9, 2011): 169–92. http://dx.doi.org/10.1007/s10732-011-9166-2.

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Herrero, S., T. Mannheim, I. Prause, Ch Pinto, B. Corves, and O. Altuzarra. "Enhancing the useful workspace of a reconfigurable parallel manipulator by grasp point optimization." Robotics and Computer-Integrated Manufacturing 31 (February 2015): 51–60. http://dx.doi.org/10.1016/j.rcim.2014.07.003.

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Gabriel, Felix, Susanna Baars, Martin Römer, and Klaus Dröder. "Grasp Point Optimization and Leakage-Compliant Dimensioning of Energy-Efficient Vacuum-Based Gripping Systems." Machines 9, no. 8 (July 29, 2021): 149. http://dx.doi.org/10.3390/machines9080149.

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Vacuum-based handling, used in many applications and industries, offers great flexibility and fast handling processes. However, due to significant energy conversion losses from electrical energy to the useable suction flow, vacuum-based handling is highly energy-inefficient. In preliminary work, we showed that our grasp optimization method offers the potential to save at least 50% of energy by a targeted placement of individual suction cups on the part to be handled. By considering the leakage between gripper and object, this paper aims to extend the grasp optimization method by predicting the effective compressed air consumption depending on object surface roughness, gripper diameter and gripper count. Through balancing of the target pressure difference and the leakage tolerance in combination with the gripper count and gripper diameter, significant reductions of the compressed air, use and therefore the overall energy consumption, can be achieved. With knowledge about the gripper-specific leakage behavior, in the future it will be straightforward for system integrators to minimize the need for oversizing due to process-related uncertainties and therefore to provide application-specific and energy-optimized handling solutions to their customers.

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Maia, Camila Loiola Brito, Rafael Augusto Ferreira do Carmo, Fabrício Gomes de Freitas, Gustavo Augusto Lima de Campos, and Jerffeson Teixeira de Souza. "Automated Test Case Prioritization with Reactive GRASP." Advances in Software Engineering 2010 (January 18, 2010): 1–18. http://dx.doi.org/10.1155/2010/428521.

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Modifications in software can affect some functionality that had been working until that point. In order to detect such a problem, the ideal solution would be testing the whole system once again, but there may be insufficient time or resources for this approach. An alternative solution is to order the test cases so that the most beneficial tests are executed first, in such a way only a subset of the test cases can be executed with little lost of effectiveness. Such a technique is known as regression test case prioritization. In this paper, we propose the use of the Reactive GRASP metaheuristic to prioritize test cases. We also compare this metaheuristic with other search-based algorithms previously described in literature. Five programs were used in the experiments. The experimental results demonstrated good coverage performance with some time overhead for the proposed technique. It also demonstrated a high stability of the results generated by the proposed approach.

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Baud-Bovy, Gabriel, and John F. Soechting. "Two Virtual Fingers in the Control of the Tripod Grasp." Journal of Neurophysiology 86, no. 2 (August 1, 2001): 604–15. http://dx.doi.org/10.1152/jn.2001.86.2.604.

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To investigate the organization of multi-fingered grasping, we asked subjects to grasp an object using three digits: the thumb, the index finger, and the middle or ring finger. The object had three coarse flat contact surfaces, whose locations and orientations were varied systematically. Subjects were asked to grasp and lift the object and then to hold it statically. We analyzed the grasp forces in the horizontal plane that were recorded during the static hold period. Static equilibrium requires that the forces exerted by the three digits intersect at a common point, the force focus. The directions of the forces exerted by the two fingers opposing the thumb depended on the orientation of the contact surfaces of both fingers but not on the orientation of the contact surface of the thumb. The direction of the thumb's force did not depend on the orientation of the contact surfaces of the two fingers and depended only weakly on the orientation of the thumb's contact surface. In general, the thumb's force was directed to a point midway between the two fingers. The results are consistent with a hierarchical model of the control of a tripod grasp. At the first level, an opposition space is created between the thumb and a virtual finger located approximately midway between the two actual fingers. The directions of the forces exerted by the two fingers are constrained to be mirror symmetric about the opposition axis. The actual directions of finger force are elaborated at the next level on the basis of stability considerations.

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Katayama, Masazumi, and Masaya Sakai. "Grasp Point of an Object is Switched between Central and Peripheral Visual Field Conditions." Procedia - Social and Behavioral Sciences 97 (November 2013): 258–65. http://dx.doi.org/10.1016/j.sbspro.2013.10.231.

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48

Myung Hwan Yun, D. Cannon, A. Freivalds, and G. Thomas. "An instrumented glove for grasp specification in virtual-reality-based point-and-direct telerobotics." IEEE Transactions on Systems, Man and Cybernetics, Part B (Cybernetics) 27, no. 5 (1997): 835–46. http://dx.doi.org/10.1109/3477.623236.

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Dehghani, Mohammad, and S. Ali A. Moosavian. "Dynamics Modeling of a Continuum Robotic Arm with a Contact Point in Planar Grasp." Journal of Robotics 2014 (2014): 1–13. http://dx.doi.org/10.1155/2014/308283.

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Grasping objects by continuum arms or fingers is a new field of interest in robotics. Continuum manipulators have the advantages of high adaptation and compatibility with respect to the object shape. However, due to their extremely nonlinear behavior and infinite degrees of freedom, continuum arms cannot be easily modeled. In fact, dynamics modeling of continuum robotic manipulators is state-of-the-art. Using the exact modeling approaches, such as theory of Cosserat rod, the resulting models are either too much time-taking for computation or numerically unstable. Thus, such models are not suitable for applications such as real-time control. However, based on realistic assumptions and using some approximations, these systems can be modeled with reasonable computational efforts. In this paper, a planar continuum robotic arm is modeled, considering its backbone as two circular arcs. In order to simulate finger grasping, the continuum arm experiences a point-force along its body. Finally, the results are validated using obtained experimental data.

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Qian, Kun, Xingshuo Jing, Yanhui Duan, Bo Zhou, Fang Fang, Jing Xia, and Xudong Ma. "Grasp Pose Detection with Affordance-based Task Constraint Learning in Single-view Point Clouds." Journal of Intelligent & Robotic Systems 100, no. 1 (May 23, 2020): 145–63. http://dx.doi.org/10.1007/s10846-020-01202-3.

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