Results 301 to 310 of about 365,547 (358)
Targeted nerve stimulation restores single-finger movements in a person with tetraplegia
Micera S +18 more
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Grasp-Anything: Large-scale Grasp Dataset from Foundation Models [PDF]
IEEE International Conference on Robotics and Automation, 2023 Foundation models such as ChatGPT have made significant strides in robotic tasks due to their universal representation of real-world domains. In this paper, we leverage foundation models to tackle grasp detection, a persistent challenge in robotics with ...
An Vuong +7 more
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Efficient Grasp Detection Network With Gaussian-Based Grasp Representation for Robotic Manipulation
IEEE/ASME transactions on mechatronics, 2023Deep learning methods have achieved excellent results in the field of grasp detection. However, deep learning-based models for general object detection lack the proper balance of accuracy and inference speed, resulting in poor performance in real-time ...
Hu Cao +5 more
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Grasping the dice by dicing the grasp
Proceedings 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2003) (Cat. No.03CH37453), 2004Many methods for generating and analyzing grasps have been developed in the recent years. They gave insight and comprehension of grasping with robot hands but many of them are rather complicated to implement and of high computational complexity.
Borst, C., Fischer, M., Hirzinger, G.
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The International Journal of Robotics Research, 2010
This paper introduces a principle to guide the design of finger form: invariance of contact geometry over some continuum of varying shape and/or pose of the grasped object in the plane. Specific applications of this principle include scale-invariant and pose-invariant grasps. Under specific conditions, the principle gives rise to spiral shaped fingers,
Alberto Rodriguez 0003, Matthew T. Mason
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This paper introduces a principle to guide the design of finger form: invariance of contact geometry over some continuum of varying shape and/or pose of the grasped object in the plane. Specific applications of this principle include scale-invariant and pose-invariant grasps. Under specific conditions, the principle gives rise to spiral shaped fingers,
Alberto Rodriguez 0003, Matthew T. Mason
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SKGNet: Robotic Grasp Detection With Selective Kernel Convolution
IEEE Transactions on Automation Science and Engineering, 2023Real-time and accuracy are important evaluation metrics of robotic grasp detection algorithms. To further improve the accuracy on the premise of ensuring real-time performance, in this paper, a new Selective Kernel convolution Grasp detection Network ...
Sheng Yu, Dihua Zhai, Yuanqing Xia
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SE-ResUNet: A Novel Robotic Grasp Detection Method
IEEE Robotics and Automation Letters, 2022In this paper, a novel grasp detection neural network Squeeze-and-Excitation ResUNet (SE-ResUNet) is developed, where the residual block with the channel attention is integrated.
Sheng Yu +4 more
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Knot grasping, folding, and re-grasping
The International Journal of Robotics Research, 2018This paper analyzes the physical resources necessary and sufficient to tie a knot of given structure. We present the first sufficient bound on the number of fingers required to tie a given knot; the bound is linear in the number of crossings appearing in the knot diagram for a given knot. We also present a lower bound on the required number of fingers,
Weifu Wang 0001, Devin J. Balkcom
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