Control system architecture of an intelligent humanoid robot

Abstract

This paper presents the hardware and control software architectures of an intelligent humanoid robot. The robot has a mobile base consists of three omnidirectional wheels that allows it to move freely with three degree-of-freedom (DOF), two 6-DOF arms and 3-DOF neck and head that allows it to perform most of the common movements of human. Detail hardware components are given to show our mechanical design solution of the robot. The control software structure of the robotic system is constructed in the robot operating system (ROS) framework which is mainly used as a bridge to connect the control modules and various peripheral devices to ease our robot system task management. We have also shown the detail structure of the robot control system which consists of all key control modules which enable the robot functions: from upper level with AI-based techniques such as image and sound processing to middle level with the robot motion controllers and then to the lower level with the management of atuators and sensors. The proposed architecture is being developed and tested on a real humanoid robot prototype called Bonbon to support Enghlish teaching in elementary schools.

Optimizing Photovoltaic System Performance through the Design and Development of an Artificial Neural Network MPPT Control

“…The present status of MPPT control research is summarized in this study, which also clarifies the theoretical underpinnings and real-world applications of ANNs, FLCs, and Q-learning. The review covers significant developments, difficulties, and comparison studies of these intelligent algorithms, offering perceptions into their relative advantages and disadvantages (Nguyen, Nguyen, & Tran, 2015). The research also emphasizes the increasing agreement among scientists that intelligent algorithms have the ability to completely transform MPPT control and open the door to more flexible, reliable, and effective solar PV systems.…”