Deep learning approaches to grasp synthesis: A review

R Newbury, M Gu, L Chumbley… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
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 …

Vision-based holistic scene understanding towards proactive human–robot collaboration

J Fan, P Zheng, S Li - Robotics and Computer-Integrated Manufacturing, 2022 - Elsevier
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 …

Trends and challenges in robot manipulation

A Billard, D Kragic - Science, 2019 - science.org
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 …

Dex-net 2.0: Deep learning to plan robust grasps with synthetic point clouds and analytic grasp metrics

J Mahler, J Liang, S Niyaz, M Laskey, R Doan… - ar**, perception and interaction: A survey
S Garg, N Sünderhauf, F Dayoub… - … and Trends® in …, 2020 - nowpublishers.com
For robots to navigate and interact more richly with the world around them, they will likely
require a deeper understanding of the world in which they operate. In robotics and related …

Grounded human-object interaction hotspots from video

T Nagarajan, C Feichtenhofer… - Proceedings of the …, 2019 - openaccess.thecvf.com
Learning how to interact with objects is an important step towards embodied visual
intelligence, but existing techniques suffer from heavy supervision or sensing requirements …

Grounding 3d object affordance from 2d interactions in images

Y Yang, W Zhai, H Luo, Y Cao… - Proceedings of the …, 2023 - openaccess.thecvf.com
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 …

Object-based affordances detection with convolutional neural networks and dense conditional random fields

A Nguyen, D Kanoulas, DG Caldwell… - 2017 IEEE/RSJ …, 2017 - ieeexplore.ieee.org
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 …