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Deep learning approaches to grasp synthesis: A review
Gras** is the process of picking up an object by applying forces and torques at a set of
contacts. Recent advances in deep learning methods have allowed rapid progress in robotic …
contacts. Recent advances in deep learning methods have allowed rapid progress in robotic …
Vision-based holistic scene understanding towards proactive human–robot collaboration
Recently human–robot collaboration (HRC) has emerged as a promising paradigm for mass
personalization in manufacturing owing to the potential to fully exploit the strength of human …
personalization in manufacturing owing to the potential to fully exploit the strength of human …
Trends and challenges in robot manipulation
BACKGROUND Humans have a fantastic ability to manipulate objects of various shapes,
sizes, and materials and can control the objects' position in confined spaces with the …
sizes, and materials and can control the objects' position in confined spaces with the …
Dex-net 2.0: Deep learning to plan robust grasps with synthetic point clouds and analytic grasp metrics
Grounded human-object interaction hotspots from video
Learning how to interact with objects is an important step towards embodied visual
intelligence, but existing techniques suffer from heavy supervision or sensing requirements …
intelligence, but existing techniques suffer from heavy supervision or sensing requirements …
Grounding 3d object affordance from 2d interactions in images
Grounding 3D object affordance seeks to locate objects'" action possibilities" regions in the
3D space, which serves as a link between perception and operation for embodied agents …
3D space, which serves as a link between perception and operation for embodied agents …
Object-based affordances detection with convolutional neural networks and dense conditional random fields
We present a new method to detect object affordances in real-world scenes using deep
Convolutional Neural Networks (CNN), an object detector and dense Conditional Random …
Convolutional Neural Networks (CNN), an object detector and dense Conditional Random …