Jun-Seok Yang

A travelling control of mobile robot based on sonar sensors

This paper describes the design and real implementation of wall following and fuzzy perception concept with a non-holonomic mobile robot named KHAN-Robo. The main focus of this paper is obtaining a fuzzy perception of the environment in the design of each reactive behavior and solving the problem of behavior combination to implement a fuzzy behavior based control architecture. It should be remarked that, the proposed technique of the nonholonomic constraints are considered in the design of each behavior. Furthermore, in order to improve the capabilities of the intelligent control system and its practical applicability, teleoperation and planned behaviors, together with their combination with reactive ones, have been considered. Experimental results, of an application to control the KHAN-Robo autonomous vehicle, demonstrate the robustness of the proposed method.

An intelligent motion control of two wheel driving robot based voice recognition

Recently, it is possible to control the motion by the information on the robots own postures, because a type of motion and gesture produces almost the same pattern of noise every time. In this paper, we describe an voice recognition control system for robot system which can robustly recognize voice by adults and children in noisy environments. We evaluate the performance of robot control system in a communication robot placed in a real noisy environment. Voice is captured using a wireless microphone. To suppress interference and noise and to attenuate reverberation, we implemented a multi-channel system consisting of an outlier-robust generalized side-lobe canceller technique and a feature-space noise suppression using criteria. Voice activity periods are detected based end-point detection.

A Study on Kinematics Modeling and Motion Control Algorithm Development in Joint for Vertical Type Articulated Robot Arma

In this paper, we propose a new technique to the design and real-time control of an adaptive controller for robotic manipulator based on digital signal processors. The Texas Instruments DSPs(TMS320C80) chips are used in implementing real-time adaptive control algorithms to provide enhanced motion control performance for dual-arm robotic manipulators. In the proposed scheme, adaptation laws are derived from model reference adaptive control principle based on the improved Lyapunov second method. The proposed adaptive controller consists of an adaptive feed-forward and feedback controller and time-varying auxiliary controller elements. The proposed control scheme is simple in structure, fast in computation, and suitable for real-time control. Moreover, this scheme does not require any accurate dynamic modeling, nor values of manipulator parameters and payload. Performance of the proposed adaptive controller is illustrated by simulation and experimental results for a dual arm robot manipulator with eight joints. joint space and cartesian space.

A study on robust motion control of humanoid type robot for cooperative working

We present a new technology for real-time walking of a humanoid robot. A humanoid robot necessitates achieving stabilization for real time walking since it has basic problems such as structural stability. In this paper, a robust control algorithm for stable walking is proposed based the ground reaction forces, which are measured using force sensors during walking, and the environmental conditions are estimated from these situation. From this information the robot selects the proper motion and overcomes ground irregularities effectively. In order to generate the proper angel of the joint. The performance of the proposed algorithm is verified by simulation and experiments for a 20-DOFs humanoid robot.

A study on robust control of articulated robot arm with seven joints

In this paper, we present two kinds of robust control schemes for robot system which has the parametric uncertainties. In order to compensate these uncertainties, we use the neural network control system that has the capability to approximate any nonlinear function over the compact input space. In the proposed control schemes, we need not derive the linear formulation of robot dynamic equation and tune the parameters. We also suggest the robust adaptive control laws in all proposed schemes for decreasing the effect of approximation error. To reduce the number of neural of network, we consider the properties of robot dynamics and the decomposition of the uncertainty function. The proposed controllers are robust not only to the structured uncertainty such as payload parameter, but also to the unstructured one such as friction model and disturbance. The reliability of the control scheme is shown by computer simulations and experiment of robot manipulator with 7 axis.

A study on travelling control of humanoid type mobile robot with three wheel

We Present a new technique to control of mobile robot for trajectory Tracking based fuzzy perception concept with robot named HMRO-I. The main focus of this paper is obtaining a fuzzy perception of the environment in the design of each reactive behavior and solving the problem of behavior combination to implement a fuzzy behavior based control architecture. It should be remarked that, the proposed technique of the nonholonomic constraints are considered in the design of each behavior. Furthermore, in order to improve the capabilities of the intelligent control system and its practical applicability, teleoperation and planned behaviors, together with their combination with reactive ones, have been considered. Experimental results, of an application to control the HMRO-I Robot autonomous vehicle, demonstrate the robustness of the proposed method.

A study on gripping control of robotic hand with ten joints for cooperative working

Recently it is very important to control robot hands more compact and precise sensors in order to increase compensate the grasping capability and to reduce cabling through the finger in the manipulator. As a matter of fact, the miniaturization and cabling harness represents a significant limitation to the design of small sized precise sensor. The main focus of this research is on a robust grasping control of hand fingers, which consists of a flexible multi-fingered with ten joints.

A Study on Precise Control of Industrial Robot Arm for Manufacturing Process Automation

In this paper, we present two kinds of robust control schemes for robot system which has the parametric uncertainties. In order to compensate these uncertainties, we use the neural network control system that has the capability to approximate any nonlinear function over the compact input space. In the proposed control schemes, we need not derive the linear formulation of robot dynamic equation and tune the parameters. We also suggest the robust adaptive control laws in all proposed schemes for decreasing the effect of approximation error. To reduce the number of neural of network, we consider the properties of robot dynamics and the decomposition of the uncertainty function. The proposed controllers are robust not only to the structured uncertainty such as payload parameter, but also to the unstructured one such as friction model and disturbance. The reliability of the control scheme is shown by computer simulations and experiment of robot manipulator with 7 axis.