Abstract Collision avoidance of Arm Robot is designed for the robot to collide objects, collide
the environment, and collide its body. Self-collision avoidance was successfully trained …

In this research, an intelligence collision avoidance system on a mobile robot was designed
using the AlexNet image classifier method. AlexNet is a convolutional neural network …

To address the local minimum issue commonly encountered in active collision avoidance
using artificial potential field (APF), this paper presents a novel algorithm that integrates APF …

Robot arms are machines which are not only used in industrial technologies but also other
applications such as medicine and agriculture. The robot arm movement control is important …

Inspired by the advantages of the hierarchical feature extraction of deep learning, this work
investigates the development of a Convolutional Neural Network (CNN) algorithm to solve …

The inverse kinematics is the foundation and emphases of the industrial robot control.
Traditional solutions of inverse kinematics cause many difficulties to the exploitation of many …

In this study, we propose a new deep convolutional generative adversarial kinematics
network (DCGAKN) to establish inverse kinematics of self-assembly robotic arm. We design …

Robotic Arms are used in many fields due to their high accuracy. A robotic arm has the
advantage of solving the same tasks as a human arm because of its similar structure and …

Robotic arm movements are highly dependent on design and deployment of sensors &
actuation devices & their duty cycles. Optimizing current-level duty cycles for these devices …

Machine learning is presently acknowledged as a significant ingredient of research in many
fields, including robotics. The use of robots to perform assorted tasks is evident in difficult …