Foresti, G.L.,
Pellegrino, F.A.,
Automatic Visual Recognition of Deformable Objects for Grasping and
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SMC-C(34), No. 3, August 2004, pp. 325-333.
IEEE Abstract.
0409
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Carrasco, M.[Miguel],
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IVC(30), No. 11, November 2012, pp. 860-874.
Elsevier DOI
1211
Visual system; Grasping movements; Motion analysis; Hand posture; Hand
gesture; Object recognition
BibRef
Sreenivasa, M.,
Soueres, P.,
Laumond, J.P.,
Walking to Grasp: Modeling of Human Movements as Invariants and an
Application to Humanoid Robotics,
SMC-A(42), No. 4, July 2012, pp. 880-893.
IEEE DOI
1206
BibRef
Colasanto, L.,
Suarez, R.,
Rosell, J.,
Hybrid Mapping for the Assistance of Teleoperated Grasping Tasks,
SMCS(43), No. 2, March 2013, pp. 390-401.
IEEE DOI
1303
BibRef
Zhou, K.[Kai],
Richtsfeld, A.[Andreas],
Varadarajan, K.M.[Karthik Mahesh],
Zillich, M.[Michael],
Vincze, M.[Markus],
Combining Plane Estimation with Shape Detection for Holistic Scene
Understanding,
ACIVS11(736-747).
Springer DOI
1108
BibRef
Varadarajan, K.M.[Karthik Mahesh],
Vincze, M.[Markus],
AfNet: The Affordance Network,
ACCV12(I:512-523).
Springer DOI
1304
BibRef
Earlier:
Knowledge Representation and Inference for Grasp Affordances,
CVS11(173-182).
Springer DOI
1109
BibRef
And:
Surface reconstruction for RGB-D data using real-time depth propagation,
Dense11(723-724).
IEEE DOI
1201
BibRef
Earlier:
Real-time depth diffusion for 3D surface reconstruction,
ICIP10(4149-4152).
IEEE DOI
1009
BibRef
Olufs, S.[Sven],
Vincze, M.[Markus],
Room-structure estimation in Manhattan-like environments from dense 2˝D
range data using minumum entropy and histograms,
WACV11(118-124).
IEEE DOI
1101
BibRef
Richtsfeld, M.[Mario],
Vincze, M.[Markus],
Point Cloud Segmentation Based on Radial Reflection,
CAIP09(955-962).
Springer DOI
0909
BibRef
Lee, C.S.[Chan-Su],
Chun, S.[Sung_Yong],
Park, S.W.[Shin Won],
Tracking hand rotation and various grasping gestures from an IR
camera using extended cylindrical manifold embedding,
CVIU(117), No. 12, 2013, pp. 1711-1723.
Elsevier DOI
1310
BibRef
Earlier: A1, A3, Only:
Tracking Hand Rotation and Grasping from an IR Camera Using Cylindrical
Manifold Embedding,
ICPR10(2612-2615).
IEEE DOI
1008
Tracking
BibRef
Song, K.T.,
Jiang, S.Y.,
Lin, M.H.,
Interactive Teleoperation of a Mobile Manipulator Using a
Shared-Control Approach,
HMS(46), No. 6, December 2016, pp. 834-845.
IEEE DOI
1612
Grasping
BibRef
Cotugno, G.,
Althoefer, K.,
Nanayakkara, T.,
The Role of the Thumb: Study of Finger Motion in Grasping and
Reachability Space in Human and Robotic Hands,
SMCS(47), No. 7, July 2017, pp. 1061-1070.
IEEE DOI
1706
Grasping, Grippers, Kinematics, Robot kinematics, Standards, Thumb,
Dexterous manipulation, grasping, humanoid robots, kinematics,
multifingered, hands
BibRef
Cai, M.,
Kitani, K.M.,
Sato, Y.,
An Ego-Vision System for Hand Grasp Analysis,
HMS(47), No. 4, August 2017, pp. 524-535.
IEEE DOI
1708
Cameras, Feature extraction, Image segmentation, Robots, Sensors,
Taxonomy, Visualization, Egocentric vision, hand grasp, recognition,
wearable, system
BibRef
Song, P.[Peng],
Fu, Z.Q.[Zhong-Qi],
Liu, L.G.[Li-Gang],
Grasp planning via hand-object geometric fitting,
VC(34), No. 2, February 2018, pp. 257-270.
WWW Link.
1802
BibRef
Asif, U.[Umar],
Bennamoun, M.[Mohammed],
Sohel, F.A.[Ferdous A.],
A Multi-Modal, Discriminative and Spatially Invariant CNN for RGB-D
Object Labeling,
PAMI(40), No. 9, September 2018, pp. 2051-2065.
IEEE DOI
1808
BibRef
Earlier:
Model-Free Segmentation and Grasp Selection of Unknown Stacked Objects,
ECCV14(V: 659-674).
Springer DOI
1408
Labeling, Solid modeling, Proposals,
Semantics, Image reconstruction, Computational modeling,
semantic segmentation
BibRef
González-Díaz, I.[Iván],
Benois-Pineau, J.[Jenny],
Domenger, J.P.[Jean-Philippe],
Cattaert, D.[Daniel],
de Rugy, A.[Aymar],
Perceptually-guided deep neural networks for ego-action prediction:
Object grasping,
PR(88), 2019, pp. 223-235.
Elsevier DOI
1901
Human perception, Grasping action prediction,
Weakly supervised active object detection
BibRef
Chauhan, R.,
Sebastian, B.,
Ben-Tzvi, P.,
Grasp Prediction Toward Naturalistic Exoskeleton Glove Control,
HMS(50), No. 1, February 2020, pp. 22-31.
IEEE DOI
2001
Prediction algorithms, Exoskeletons,
Principal component analysis, Sensors, Electromyography,
upper limb
BibRef
Irmak, E.C.[Erdem Can],
Sahillioglu, Y.[Yusuf],
3D indirect shape retrieval based on hand interaction,
VC(36), No. 1, January 2020, pp. 5-17.
WWW Link.
2001
BibRef
Zhang, H.,
Zhou, X.,
Lan, X.,
Li, J.,
Tian, Z.,
Zheng, N.,
A Real-Time Robotic Grasping Approach With Oriented Anchor Box,
SMCS(51), No. 5, May 2021, pp. 3014-3025.
IEEE DOI
2104
Robot kinematics, Grasping, Feature extraction, Training,
Real-time systems, Prediction algorithms, Angle matching,
real-time robotic grasping
BibRef
Yu, Y.Y.[Ying-Ying],
Cao, Z.Q.[Zhi-Qiang],
Liu, Z.C.[Zhi-Cheng],
Geng, W.J.[Wen-Jie],
Yu, J.Z.[Jun-Zhi],
Zhang, W.M.[Wei-Min],
A Two-Stream CNN With Simultaneous Detection and Segmentation for
Robotic Grasping,
SMCS(52), No. 2, February 2022, pp. 1167-1181.
IEEE DOI
2201
Grasping, Robot kinematics, Manipulators, Image segmentation,
Deconvolution, Machine learning,
two-stream grasping convolutional neural network (CNN)
BibRef
Shang, W.W.[Wei-Wei],
Song, F.J.[Fang-Jing],
Zhao, Z.Z.[Zeng-Zhi],
Gao, H.B.[Hong-Bo],
Cong, S.[Shuang],
Li, Z.J.[Zhi-Jun],
Deep Learning Method for Grasping Novel Objects Using Dexterous Hands,
Cyber(52), No. 5, May 2022, pp. 2750-2762.
IEEE DOI
2206
Grasping, Indexes, Robots, Grippers, Force, Machine learning,
Task analysis, Deep learning, dexterous hand, grasp posture,
robotic grasp
BibRef
Pattar, S.P.[Suraj Prakash],
Hirakawa, T.[Tsubasa],
Yamashita, T.[Takayoshi],
Sawanobori, T.[Tetsuya],
Fujiyoshi, H.[Hironobu],
Single Suction Grasp Detection for Symmetric Objects Using Shallow
Networks Trained with Synthetic Data,
IEICE(E105-D), No. 9, September 2022, pp. 1600-1609.
WWW Link.
2209
BibRef
Cong, Y.[Yang],
Chen, R.[Ronghan],
Ma, B.[Bingtao],
Liu, H.[Hongsen],
Hou, D.D.[Dong-Dong],
Yang, C.G.[Chen-Guang],
A Comprehensive Study of 3-D Vision-Based Robot Manipulation,
Cyber(53), No. 3, March 2023, pp. 1682-1698.
IEEE DOI
2302
Robots, Service robots, Grasping, Data acquisition, Pose estimation, Force,
Cameras, 3-D object recognition, grasping estimation, robot manipulation
BibRef
Jeddi, M.[Mahmoud],
Khoogar, A.R.[Ahmad Reza],
A modified eye-in-hand stereo visual control for grasping unknown
objects via Scara robot,
IET-IPR(17), No. 7, 2023, pp. 2015-2031.
DOI Link
2305
calibration, cameras, computer vision, decision making, estimation theory,
feedback, image matching, Kalman filters, motion estimation
BibRef
Chumbley, L.[Lachlan],
Gu, M.[Morris],
Newbury, R.[Rhys],
Leitner, J.[Jürgen],
Cosgun, A.[Akansel],
Integrating High-Resolution Tactile Sensing into Grasp Stability
Prediction,
CRV22(98-105)
IEEE DOI
2301
Neural networks, Tactile sensors, Grasping, Data collection,
Benchmark testing, Robot sensing systems, Stability analysis, Sensor Fusion
BibRef
Gohil, P.[Priteshkumar],
Thoduka, S.[Santosh],
Plöger, P.G.[Paul G.],
Sensor Fusion and Multimodal Learning for Robotic Grasp Verification
Using Neural Networks,
ICPR22(5111-5117)
IEEE DOI
2212
Visualization, Fuses, Neural networks,
Sensor fusion, Robot sensing systems, Minimization
BibRef
Wu, Y.[Yan],
Wang, J.H.[Jia-Hao],
Zhang, Y.[Yan],
Zhang, S.W.[Si-Wei],
Hilliges, O.[Otmar],
Yu, F.[Fisher],
Tang, S.[Siyu],
SAGA: Stochastic Whole-Body Grasping with Contact,
ECCV22(VI:257-274).
Springer DOI
2211
BibRef
Wang, K.[Kai],
Guerrero, P.[Paul],
Kim, V.G.[Vladimir G.],
Chaudhuri, S.[Siddhartha],
Sung, M.[Minhyuk],
Ritchie, D.[Daniel],
The Shape Part Slot Machine:
Contact-Based Reasoning for Generating 3D Shapes from Parts,
ECCV22(III:610-626).
Springer DOI
2211
BibRef
Turpin, D.[Dylan],
Wang, L.Q.[Li-Quan],
Heiden, E.[Eric],
Chen, Y.C.[Yun-Chun],
Macklin, M.[Miles],
Tsogkas, S.[Stavros],
Dickinson, S.[Sven],
Garg, A.[Animesh],
Grasp'D: Differentiable Contact-Rich Grasp Synthesis for Multi-Fingered
Hands,
ECCV22(VI:201-221).
Springer DOI
2211
BibRef
Wen, H.T.[Hong-Tao],
Yan, J.H.[Jian-Hang],
Peng, W.L.[Wan-Li],
Sun, Y.[Yi],
TransGrasp: Grasp Pose Estimation of a Category of Objects by
Transferring Grasps from Only One Labeled Instance,
ECCV22(XXIX:445-461).
Springer DOI
2211
BibRef
Tse, T.H.E.[Tze Ho Elden],
Kim, K.I.[Kwang In],
Leonardis, A.[Ale],
Chang, H.J.[Hyung Jin],
Collaborative Learning for Hand and Object Reconstruction with
Attention-guided Graph Convolution,
CVPR22(1654-1664)
IEEE DOI
2210
Training, Representation learning, Solid modeling, Shape,
Convolution, Pose estimation, 3D from single images,
Representation learning
BibRef
Yang, L.X.[Li-Xin],
Li, K.[Kailin],
Zhan, X.Y.[Xin-Yu],
Lv, J.[Jun],
Xu, W.Q.[Wen-Qiang],
Li, J.[Jiefeng],
Lu, C.[Cewu],
ArtiBoost: Boosting Articulated 3D Hand-Object Pose Estimation via
Online Exploration and Synthesis,
CVPR22(2740-2750)
IEEE DOI
2210
Training, Codes, Computational modeling, Pose estimation, Pipelines,
3D from single images, Pose estimation and tracking
BibRef
Taheri, O.[Omid],
Choutas, V.[Vasileios],
Black, M.J.[Michael J.],
Tzionas, D.[Dimitrios],
GOAL: Generating 4D Whole-Body Motion for Hand-Object Grasping,
CVPR22(13253-13263)
IEEE DOI
2210
Solid modeling, Codes, Tracking, Shape, Avatars,
Pose estimation and tracking, Motion and tracking
BibRef
Christen, S.[Sammy],
Kocabas, M.[Muhammed],
Aksan, E.[Emre],
Hwangbo, J.[Jemin],
Song, J.[Jie],
Hilliges, O.[Otmar],
D-Grasp: Physically Plausible Dynamic Grasp Synthesis for Hand-Object
Interactions,
CVPR22(20545-20554)
IEEE DOI
2210
Codes, Dynamics, Reinforcement learning, Grasping, Cognition,
Pattern recognition, Face and gestures, Others
BibRef
Jiang, H.W.[Han-Wen],
Liu, S.W.[Shao-Wei],
Wang, J.S.[Jia-Shun],
Wang, X.L.[Xiao-Long],
Hand-Object Contact Consistency Reasoning for Human Grasps Generation,
ICCV21(11087-11096)
IEEE DOI
2203
Training, Cognition, Task analysis, Grippers, Gestures and body pose,
Transfer/Low-shot/Semi/Unsupervised Learning
BibRef
Landgraf, Z.[Zoe],
Scona, R.[Raluca],
Laidlow, T.[Tristan],
James, S.[Stephen],
Leutenegger, S.[Stefan],
Davison, A.J.[Andrew J.],
SIMstack: A Generative Shape and Instance Model for Unordered Object
Stacks,
ICCV21(12992-13002)
IEEE DOI
2203
Solid modeling, Shape, Grasping, Predictive models,
Probabilistic logic, 3D from a single image and shape-from-x,
Vision for robotics and autonomous vehicles
BibRef
Zhu, T.Q.[Tian-Qiang],
Wu, R.[Rina],
Lin, X.B.[Xiang-Bo],
Sun, Y.[Yi],
Toward Human-Like Grasp: Dexterous Grasping via Semantic
Representation of Object-Hand,
ICCV21(15721-15731)
IEEE DOI
2203
Codes, Annotations, Computational modeling, Semantics, Grasping,
Data models, Vision for robotics and autonomous vehicles,
BibRef
Wang, C.X.[Chen-Xi],
Fang, H.S.[Hao-Shu],
Gou, M.H.[Ming-Hao],
Fang, H.J.[Hong-Jie],
Gao, J.[Jin],
Lu, C.[Cewu],
Graspness Discovery in Clutters for Fast and Accurate Grasp Detection,
ICCV21(15944-15953)
IEEE DOI
2203
Geometry, Filtering, Computational modeling, Current measurement,
Neural networks, Grasping,
BibRef
Wu, Y.M.[Yan-Min],
Zhang, Y.Z.[Yun-Zhou],
Zhu, D.L.[De-Long],
Chen, X.[Xin],
Coleman, S.[Sonya],
Sun, W.K.[Wen-Kai],
Hu, X.G.[Xing-Gang],
Deng, Z.Q.[Zhi-Qiang],
Object SLAM-Based Active Mapping and Robotic Grasping,
3DV21(1372-1381)
IEEE DOI
2201
Solid modeling, Simultaneous localization and mapping,
Uncertainty, Shape, Pose estimation, Grasping, Object SLAM, Robotic Grasping
BibRef
Yin, Y.[Yue],
McCarthy, C.[Chris],
Rezazadegan, D.[Dana],
Real-Time 3D Hand-Object Pose Estimation for Mobile Devices,
ICIP21(3288-3292)
IEEE DOI
2201
Performance evaluation, Solid modeling, Image recognition,
Computational modeling, Pose estimation, Memory management,
augmented reality
BibRef
Cheng, Z.[Zida],
Chen, S.[Siheng],
Zhang, Y.[Ya],
Semi-Supervised 3D Hand-Object Pose Estimation Via Pose Dictionary
Learning,
ICIP21(3632-3636)
IEEE DOI
2201
Estimation error, Pose estimation, Machine learning,
Data collection, Cameras, Hand-object pose estimation,
pose dictionary learning
BibRef
Xu, S.X.[Si-Xiong],
Gong, P.[Pei],
Dong, Y.C.[Yan-Chao],
Gi, L.L.[Ling-Ling],
Huang, C.[Cheng],
Wang, S.B.[Si-Biao],
Pose Estimation of Texture-Less Targets for Unconstrained Grasping,
ISVC21(I:466-477).
Springer DOI
2112
BibRef
Grady, P.[Patrick],
Tang, C.C.[Cheng-Cheng],
Twigg, C.D.[Christopher D.],
Vo, M.[Minh],
Brahmbhatt, S.[Samarth],
Kemp, C.C.[Charles C.],
ContactOpt: Optimizing Contact to Improve Grasps,
CVPR21(1471-1481)
IEEE DOI
2111
Deformable models, Codes, Pose estimation,
Biological tissues, Kinematics, Data models
BibRef
Liu, H.B.[Hong-Bin],
Jia, J.Y.[Jin-Yuan],
Gong, N.Z.Q.[Neil Zhen-Qiang],
PointGuard: Provably Robust 3D Point Cloud Classification,
CVPR21(6182-6191)
IEEE DOI
2111
Smoothing methods,
Computational modeling, Grasping, Benchmark testing, Prediction algorithms
BibRef
Prew, W.[William],
Breckon, T.[Toby],
Bordewich, M.[Magnus],
Beierholm, U.[Ulrik],
Improving Robotic Grasping on Monocular Images Via Multi-Task
Learning and Positional Loss,
ICPR21(9843-9850)
IEEE DOI
2105
Training, Image color analysis, Grasping, Real-time systems,
Pattern recognition, Task analysis, Grippers
BibRef
de Gregorio, D.[Daniele],
Zanella, R.[Riccardo],
Palli, G.[Gianluca],
di Stefano, L.[Luigi],
Effective Deployment of CNNs for 3DoF Pose Estimation and Grasping in
Industrial Settings,
ICPR21(7419-7426)
IEEE DOI
2105
Deep learning, Training, Automation, Service robots, Pose estimation,
Training data, Grasping
BibRef
Arora, P.[Prateek],
Papachristos, C.[Christos],
Mobile Manipulator Robot Visual Servoing and Guidance for Dynamic
Target Grasping,
ISVC20(II:223-235).
Springer DOI
2103
BibRef
Karunratanakul, K.,
Tang, S.[Siyu],
Zhang, Y.,
Black, M.J.,
Muandet, K.[Krikamol],
Tang, S.,
Grasping Field: Learning Implicit Representations for Human Grasps,
3DV20(333-344)
IEEE DOI
2102
Grasping, Solid modeling,
Image reconstruction, Neural networks, Task analysis, Data models,
grasp generation
BibRef
Taheri, O.[Omid],
Ghorbani, N.[Nima],
Black, M.J.[Michael J.],
Tzionas, D.[Dimitrios],
Grab: A Dataset of Whole-body Human Grasping of Objects,
ECCV20(IV:581-600).
Springer DOI
2011
BibRef
Gong, S.,
Bahri, M.,
Bronstein, M.M.,
Zafeiriou, S.P.[Stefanos P.],
Geometrically Principled Connections in Graph Neural Networks,
CVPR20(11412-11421)
IEEE DOI
2008
Convolution, Neural networks, Machine learning, Kernel,
Interpolation, Task analysis, Shape
BibRef
Fang, H.,
Wang, C.,
Gou, M.,
Lu, C.,
GraspNet-1Billion: A Large-Scale Benchmark for General Object
Grasping,
CVPR20(11441-11450)
IEEE DOI
2008
Grasping, Cameras,
Robot vision systems, Benchmark testing, Machine learning, Robustness
BibRef
Shan, D.,
Geng, J.,
Shu, M.,
Fouhey, D.F.,
Understanding Human Hands in Contact at Internet Scale,
CVPR20(9866-9875)
IEEE DOI
2008
Videos, Internet, Image reconstruction, YouTube,
Data mining
BibRef
James, S.[Stephen],
Wohlhart, P.[Paul],
Kalakrishnan, M.[Mrinal],
Kalashnikov, D.[Dmitry],
Irpan, A.[Alex],
Ibarz, J.[Julian],
Levine, S.[Sergey],
Hadsell, R.[Raia],
Bousmalis, K.[Konstantinos],
Sim-To-Real via Sim-To-Sim: Data-Efficient Robotic Grasping via
Randomized-To-Canonical Adaptation Networks,
CVPR19(12619-12629).
IEEE DOI
2002
BibRef
Brahmbhatt, S.[Samarth],
Ham, C.[Cusuh],
Kemp, C.C.[Charles C.],
Hays, J.[James],
ContactDB: Analyzing and Predicting Grasp Contact via Thermal Imaging,
CVPR19(8701-8711).
IEEE DOI
2002
BibRef
Tang, Q.[Qirong],
Hu, X.[Xue],
Chu, Z.[Zhugang],
Wu, S.[Shun],
6d Gripper Pose Estimation from RGB-D Image,
CVS19(120-125).
Springer DOI
1912
BibRef
Kiatos, M.[Marios],
Malassiotis, S.[Sotiris],
Grasping Unknown Objects by Exploiting Complementarity with Robot Hand
Geometry,
CVS19(88-97).
Springer DOI
1912
BibRef
Gritsenko, P.[Pavel],
Gritsenko, I.[Igor],
Seidakhmet, A.[Askar],
Kwolek, B.[Bogdan],
Plane-Based Humanoid Robot Navigation and Object Model Construction for
Grasping,
4DPose18(I:649-664).
Springer DOI
1905
BibRef
Ghazaei, G.[Ghazal],
Laina, I.[Iro],
Rupprecht, C.[Christian],
Tombari, F.[Federico],
Navab, N.[Nassir],
Nazarpour, K.[Kianoush],
Dealing with Ambiguity in Robotic Grasping via Multiple Predictions,
ACCV18(IV:38-55).
Springer DOI
1906
BibRef
Gupta, K.,
Burschka, D.,
Bhavsar, A.,
Effectiveness of Grasp Attributes and Motion-Constraints for
Fine-Grained Recognition of Object Manipulation Actions,
Hands16(1232-1239)
IEEE DOI
1612
BibRef
de Gregorio, D.[Daniele],
Tombari, F.[Federico],
di Stefano, L.[Luigi],
RobotFusion: Grasping with a Robotic Manipulator via Multi-view
Reconstruction,
6DPose16(III: 634-647).
Springer DOI
1611
BibRef
Lakani, S.R.[Safoura Rezapour],
Rodríguez-Sánchez, A.J.[Antonio J.],
Piater, J.H.[Justus H.],
Can Affordances Guide Object Decomposition into Semantically
Meaningful Parts?,
WACV17(82-90)
IEEE DOI
1609
Grasping, Histograms, Semantics, Shape, Visualization
BibRef
Yang, Y.Z.[Ye-Zhou],
Fermuller, C.[Cornelia],
Li, Y.[Yi],
Aloimonos, Y.F.[Yi-Fannis],
Grasp type revisited:
A modern perspective on a classical feature for vision,
CVPR15(400-408)
IEEE DOI
1510
BibRef
Huang, D.A.[De-An],
Ma, M.H.[Ming-Huang],
Ma, W.C.[Wei-Chiu],
Kitani, K.M.[Kris M.],
How do we use our hands? Discovering a diverse set of common grasps,
CVPR15(666-675)
IEEE DOI
1510
BibRef
Lakani, S.R.[Safoura Rezapour],
Popa, M.[Mirela],
Rodriguez-Sanchez, A.J.[Antonio J.],
Piater, J.H.[Justus H.],
CPS: 3D Compositional Part Segmentation through Grasping,
CRV15(117-124)
IEEE DOI
1507
Feature extraction
BibRef
Kim, J.W.,
You, S.,
Ji, S.H.,
Kim, H.S.,
Real-Time Hand Grasp Recognition Using Weakly Supervised Two-Stage
Convolutional Neural Networks for Understanding Manipulation Actions,
DeepLearnRV17(481-483)
IEEE DOI
1709
Feature extraction, Grasping, Image recognition,
Network architecture, Pattern recognition, Real-time, systems
BibRef
Thonnagith, P.,
Sudsang, A.,
New hand posture classification strategy for finding
kinematically-feasible precision grasps,
ICARCV10(1583-1588).
IEEE DOI
1109
BibRef
Wörsdörfer, F.[Florian],
Stock, F.[Florian],
Bayro-Corrochano, E.[Eduardo],
Hildenbrand, D.[Dietmar],
Optimizations and Performance of a Robotics Grasping Algorithm
Described in Geometric Algebra,
CIARP09(263-271).
Springer DOI
0911
BibRef
Yasumuro, Y.[Yoshihiro],
Yamazaki, M.[Masayuki],
Imura, M.[Masataka],
Manabe, Y.[Yoshitsugu],
Chihara, K.[Kunihiro],
Grasp Motion Synthesis Based on Object Features,
AMDO06(305-314).
Springer DOI
0607
BibRef
Taylor, M.J.,
Blake, A.,
Grasping the Apparent Contour,
ECCV94(B:25-34).
Springer DOI
BibRef
9400
Blake, A.,
Taylor, M.J., and
Cox, A.,
Grasping Visual Symmetry,
ICCV93(724-733).
IEEE DOI Symmetry as the locus of bi-tangent circles.
BibRef
9300
Gatrell, L.B.[Lance B.],
CAD-Based Grasp Synthesis Utilizing Polygons, Edges, and Vertices,
CRA89(184-189).
BibRef
8900
Chapter on Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities continues in
Carried Objects, Carrying Objects .