Purpose Development of autonomous robot manipulator for human-robot assembly tasks is
a key component to reach high effectiveness. In such tasks, the robot real-time object …

In many robotics studies, deep neural networks (DNNs) are being actively studied due to
their good performance. However, existing robotic techniques and DNNs have not been …

In recent years, the computer vision applications in the robotics have been improved to
approach human-like visual perception and scene/context understanding. Following this …

Artificial neural network (ANN) which has four or more layers structure is called deep NN
(DNN) and it is recognized as one of promising machine learning techniques. Convolutional …

Accurate object classification and position estimation is a crucial part of executing
autonomous pick-and-place operations by a robot and can be realized using RGB-D …

Many industrial robots have been applied relatively simple operation that requires
repeatable tasks. However, through the rapid development of deep learning with 4 th …

Traditionally, robotic assembly techniques have depended on simple sensing systems and
the robot manufacturer's programming language, which has severely restricted the extensive …

Although existing industrial robots are able to work in challenging environments, accomplish
high-precision assignments, as well as help to enhance and increase productivity, most of …

As the environments that human live are complex and uncontrolled, the object manipulation
with humanoid robots is regarded as one of the most challenging tasks. Learning a …

This paper presents a novel approach for a robot to conduct assembly tasks, namely robot
learning from human demonstrations. The learning of robotic assembly task is divided into …