Multi-sensor Based Dual Arm Autonomous Mobile Robot for Human-Robot Interactions And Services

• Main Authors: Kai-Chieh Huang, 黃凱杰
• Other Authors: Ren-C Luo
• Format: Others
• Language: en_US
• Published: 2013
• Online Access: http://ndltd.ncl.edu.tw/handle/07250698259600621355

碩士 === 國立臺灣大學 === 電機工程學研究所 === 101 === Since technology developed rapidly and societal evolvement progressively, people begin to pursue higher quality of life and the requirements in social welfare, medical care, home care, education and other services are increased. With the progress of intelligent robot industry, how to integrate robots into the daily life and how robots provide a comfortable, safe and healthy life become common visions in both academia and industry in recently years. Thus, the development of intelligent robot industry has been one of the priority prospects of industries. Among these, the service robot integrated multi-functions has become one of significant issues in Human-Robot Interactions and Services. This thesis is focus on the development of a position control algorithm for a seven-DOF dual arm autonomous robot and the human body gesture recognition system in human-robot interaction. The intelligent service robot utilizes the depth image system to obtain the skeleton of the user in environment, recognize and interact with the users. The seven-DOF dual arm autonomous robot position control strategy utilizes system identification method to obtain the motor transfer function for each axis, which involves the equivalent model of the mechanical loading structure, and implement Model Predictive Control to replace the traditional PID position loop controller. The concept is based on the predictive model of the equivalent mechanical model, and instantly calculates the optimal performance index including practical feedback information to improve the influence of unknown system structure parameters, modeling error, and the uncertainties of the environment. Moreover, it effectively improves the problems that the model having some characteristics which general control theory is not able to deal with. It also improves the deficiency of the infinite horizon optimal control which is only able to handle time-invariant system. All the systems, user interface, software and applications proposed in this thesis are implemented with C++ programming language in Windows platform. With relative stable facial features extraction, the proposed algorithm is implemented in robots developed in our laboratory at the International Center of Excellence on Intelligent Robotics and Automation Research (iCeiRA) at National Taiwan University.