2022
DOI: 10.1109/lra.2022.3202633
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Scalable Learned Geometric Feasibility for Cooperative Grasp and Motion Planning

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Cited by 4 publications
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“…The work [31] learns a separating manifold between a start and a goal using radial basis function kernel SVM. To deal with image inputs, the work [38]- [41] designs convolutional neural network-based feasibility classifiers.…”
Section: Related Workmentioning
confidence: 99%
“…The work [31] learns a separating manifold between a start and a goal using radial basis function kernel SVM. To deal with image inputs, the work [38]- [41] designs convolutional neural network-based feasibility classifiers.…”
Section: Related Workmentioning
confidence: 99%