Review of deep reinforcement learning-based object grasping: Techniques, open challenges, and recommendations

MQ Mohammed, KL Chung, CS Chyi - IEEE Access, 2020 - ieeexplore.ieee.org
The motivation behind our work is to review and analyze the most relevant studies on deep
reinforcement learning-based object manipulation. Various studies are examined through a …

Reinforcement learning for pick and place operations in robotics: A survey

A Lobbezoo, Y Qian, HJ Kwon - Robotics, 2021 - mdpi.com
The field of robotics has been rapidly developing in recent years, and the work related to
training robotic agents with reinforcement learning has been a major focus of research. This …

Transporter networks: Rearranging the visual world for robotic manipulation

A Zeng, P Florence, J Tompson… - … on Robot Learning, 2021 - proceedings.mlr.press
Robotic manipulation can be formulated as inducing a sequence of spatial displacements:
where the space being moved can encompass an object, part of an object, or end effector. In …

Neural descriptor fields: Se (3)-equivariant object representations for manipulation

A Simeonov, Y Du, A Tagliasacchi… - … on Robotics and …, 2022 - ieeexplore.ieee.org
We present Neural Descriptor Fields (NDFs), an object representation that encodes both
points and relative poses between an object and a target (such as a robot gripper or a rack …

Visual room rearrangement

L Weihs, M Deitke, A Kembhavi… - Proceedings of the …, 2021 - openaccess.thecvf.com
There has been a significant recent progress in the field of Embodied AI with researchers
developing models and algorithms enabling embodied agents to navigate and interact …

kpam: Keypoint affordances for category-level robotic manipulation

L Manuelli, W Gao, P Florence, R Tedrake - The International Symposium …, 2019 - Springer
We would like robots to achieve purposeful manipulation by placing any instance from a
category of objects into a desired set of goal states. Existing manipulation pipelines typically …

SimPLE, a visuotactile method learned in simulation to precisely pick, localize, regrasp, and place objects

M Bauza, A Bronars, Y Hou, I Taylor… - Science Robotics, 2024 - science.org
Existing robotic systems have a tension between generality and precision. Deployed
solutions for robotic manipulation tend to fall into the paradigm of one robot solving a single …

Self-supervised learning for precise pick-and-place without object model

L Berscheid, P Meißner, T Kröger - IEEE Robotics and …, 2020 - ieeexplore.ieee.org
Flexible pick-and-place is a fundamental yet challenging task within robotics, in particular
due to the need of an object model for a simple target pose definition. In this work, the robot …

Simulated and real robotic reach, grasp, and pick-and-place using combined reinforcement learning and traditional controls

A Lobbezoo, HJ Kwon - Robotics, 2023 - mdpi.com
The majority of robots in factories today are operated with conventional control strategies
that require individual programming on a task-by-task basis, with no margin for error. As an …

Challenges for future robotic sorters of mixed industrial waste: A survey

T Kiyokawa, J Takamatsu… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
To achieve recycling of mixed industrial waste toward an advanced sustainable society,
waste sorting automation through robots is crucial and urgent. For this purpose, a robot is …