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-based object manipulation. Various studies are examined through a …
Reinforcement learning for pick and place operations in robotics: A survey
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 …
training robotic agents with reinforcement learning has been a major focus of research. This …
Transporter networks: Rearranging the visual world for robotic manipulation
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 …
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
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 …
points and relative poses between an object and a target (such as a robot gripper or a rack …
Visual room rearrangement
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 …
developing models and algorithms enabling embodied agents to navigate and interact …
kpam: Keypoint affordances for category-level robotic manipulation
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 …
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
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 …
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
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 …
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 …
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 …
waste sorting automation through robots is crucial and urgent. For this purpose, a robot is …