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 …

A review of robot learning for manipulation: Challenges, representations, and algorithms

O Kroemer, S Niekum, G Konidaris - Journal of machine learning research, 2021 - jmlr.org
A key challenge in intelligent robotics is creating robots that are capable of directly
interacting with the world around them to achieve their goals. The last decade has seen …

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 …

Data-driven grasp synthesis—a survey

J Bohg, A Morales, T Asfour… - IEEE Transactions on …, 2013 - ieeexplore.ieee.org
We review the work on data-driven grasp synthesis and the methodologies for sampling and
ranking candidate grasps. We divide the approaches into three groups based on whether …

Dex-net 3.0: Computing robust vacuum suction grasp targets in point clouds using a new analytic model and deep learning

J Mahler, M Matl, X Liu, A Li, D Gealy… - … on robotics and …, 2018 - ieeexplore.ieee.org
Vacuum-based end effectors are widely used in industry and are often preferred over
parallel-jaw and multifinger grippers due to their ability to lift objects with a single point of …

Dex-net 1.0: A cloud-based network of 3d objects for robust grasp planning using a multi-armed bandit model with correlated rewards

J Mahler, FT Pokorny, B Hou… - … on robotics and …, 2016 - ieeexplore.ieee.org
This paper presents the Dexterity Network (Dex-Net) 1.0, a dataset of 3D object models and
a sampling-based planning algorithm to explore how Cloud Robotics can be used for robust …

High precision grasp pose detection in dense clutter

M Gualtieri, A Ten Pas, K Saenko… - 2016 IEEE/RSJ …, 2016 - ieeexplore.ieee.org
This paper considers the problem of grasp pose detection in point clouds. We follow a
general algorithmic structure that first generates a large set of 6-DOF grasp candidates and …

Using geometry to detect grasp poses in 3d point clouds

A Ten Pas, R Platt - Robotics Research: Volume 1, 2018 - Springer
This paper proposes a new approach to using machine learning to detect grasp poses on
novel objects presented in clutter. The input to our algorithm is a point cloud and the …