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 …

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 …

We present a novel approach to perform object-independent grasp synthesis from depth
images via deep neural networks. Our generative grasping convolutional neural network …

Camera viewpoint selection is an important aspect of visual grasp detection, especially in
clutter where many occlusions are present. Where other approaches use a static camera …

In the aviation industry, automated inspection is essential for ensuring quality of production.
It allows acceleration of procedures for quality control of parts or mechanical assemblies. As …

We address a class of manipulation problems where the robot perceives the scene with a
depth sensor and can move its end effector in a space with six degrees of freedom—3D …

Picking a specific object from clutter is an essential component of many manipulation tasks.
Partial observations often require the robot to collect additional views of the scene before …

Robust robotic grasping in clutter still remains a challenging problem despite its great
practical value. This article presents an information-theoretic exploration approach that aims …

In this work, we present an effective multi-view approach to closed-loop end-to-end learning
of precise manipulation tasks that are 3D in nature. Our method learns to accomplish these …

For the robotic grasping of randomly stacked objects in a cluttered environment, the active
multiple viewpoints method can improve grasping performance by improving the …