Patent Network Analysis and Quadratic Assignment Procedures to Identify the Convergence of Robot Technologies

نویسندگان

  • Woo Jin Lee
  • Won Kyung Lee
  • So Young Sohn
چکیده

Because of the remarkable developments in robotics in recent years, technological convergence has been active in this area. We focused on finding patterns of convergence within robot technology using network analysis of patents in both the USPTO and KIPO. To identify the variables that affect convergence, we used quadratic assignment procedures (QAP). From our analysis, we observed the patent network ecology related to convergence and found technologies that have great potential to converge with other robotics technologies. The results of our study are expected to contribute to setting up convergence based R&D policies for robotics, which can lead new innovation.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

ANFIS+PID Hybrid Controller Design for Controlling of a 6-DOF Robot Manipulator and its Error Convergence Analysis

In this paper, an ANFIS+PID hybrid control policy has been addressed to control a 6-degree-of freedom (6-DOF) robotic manipulator. Then its error convergence has been also evaluated. The ability to formulate and estimate the system uncertainties and disturbances along with system dynamics and rejecting the disturbances effect are some advantages of the proposed method in   comparing with the co...

متن کامل

A Recurrent Neural Network for Solving Strictly Convex Quadratic Programming Problems

In this paper we present an improved neural network to solve strictly convex quadratic programming(QP) problem. The proposed model is derived based on a piecewise equation correspond to optimality condition of convex (QP) problem and has a lower structure complexity respect to the other existing neural network model for solving such problems. In theoretical aspect, stability and global converge...

متن کامل

Designing Path for Robot Arm Extensions Series with the Aim of Avoiding Obstruction with Recurring Neural Network

In this paper, recurrent neural network is used for path planning in the joint space of the robot with obstacle in the workspace of the robot. To design the neural network, first a performance index has been defined as sum of square of error tracking of final executor. Then, obstacle avoidance scheme is presented based on its space coordinate and its minimum distance between the obstacle and ea...

متن کامل

Optimal discrete-time control of robot manipulators in repetitive tasks

Optimal discrete-time control of linear systems has been presented already. There are some difficulties to design an optimal discrete-time control of robot manipulator since the robot manipulator is highly nonlinear and uncertain. This paper presents a novel robust optimal discrete-time control of electrically driven robot manipulators for performing repetitive tasks. The robot performs repetit...

متن کامل

A Recurrent Neural Network to Identify Efficient Decision Making Units in Data Envelopment Analysis

In this paper we present a recurrent neural network model to recognize efficient Decision Making Units(DMUs) in Data Envelopment Analysis(DEA). The proposed neural network model is derived from an unconstrained minimization problem. In theoretical aspect, it is shown that the proposed neural network is stable in the sense of lyapunov and globally convergent. The proposed model has a single-laye...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره 11  شماره 

صفحات  -

تاریخ انتشار 2016