Kwon Son

Localization of a mobile robot using the image of a moving object

This paper proposes a new approach for determining the location of a mobile robot using the image of a moving object. This scheme combines data from the observed position, using dead-reckoning sensors, and the estimated position, using images of moving objects captured by a fixed camera to determine the location of a mobile robot. Using the a priori known path of a moving object and a perspective camera model, the geometric constraint equations that represent the relation between image frame coordinates for a moving object and the estimated robots position are derived. Since the equations are based on estimated position, measurement error may exist. However, the proposed method utilizes the error between the observed and estimated image coordinates to localize the mobile robot, and the Kalman filtering scheme is used for the estimation of the mobile robot location. The proposed approach is applied for a moving object on the wall to show the reduction of uncertainty in the determining of mobile robot location.

Localization of a mobile robot using images of a moving target

In this paper, the localization of a mobile robot using images of a moving target is introduced. Typical objects are stored in the database for the localization of the mobile robot. With a fixed camera, a perspective camera model and a given object database, an image frame can provide the pose (distance and orientation) of the object with respect to the camera. Utilizing the consecutive image frames and motion estimation technology, the relative pose of the object with respect to the camera can be obtained accurately; and during the process, calibration of camera with respect to the world frame, i.e. localization of a mobile robot, is gradually performed. This localization scheme is demonstrated by the experiments.

Development of the PNU vehicle driving simulator and its performance evaluation

A vehicle driving simulator is a virtual reality device in which a human being is able to feel as if they are actually driving a vehicle. The driving simulator consists of a motion platform, a driving operating system, a motion controller, a visual and audio system, a vehicle dynamic analysis system, etc. In this paper, the main procedures in the development of a driving simulator are classified as follows: 1) a motion platform and a motion controller, which can track a reference trajectory, were developed; 2) a new washout algorithm to realize the motion of an actual vehicle in the driving simulator was developed, and this algorithm enables one to change the real motion space of a vehicle into the workspace of the driving simulator; and 3) a visual and audio system for a more realistic feeling were developed. Finally, an integration system to communicate and monitor among the subsystems was developed. The performance evaluation of the developed Pusan National University vehicle driving simulator (PUNVDS) was carried out.

Sliding mode controller with sliding perturbation observer based on gain optimization using genetic algorithm

The Stewart platform manipulator is a closed-kinematics chain robot manipulator that is capable of providing high structural rigidity and positional accuracy. However, this is a complex and nonlinear system, so the control performance of the system is not so good. In this paper, a new robust motion control algorithm is proposed. The algorithm uses partial state feedback for a class of nonlinear systems with modeling uncertainties and external disturbances. The major contribution is the design of a robust observer for the state and the perturbation of the Stewart platform, which is combined with a variable structure controller (VSC). The combination of controller and observer provides the robust routine called sliding mode control with sliding perturbation observer (SMCSPO). The optimal gains of SMCSPO, which is determined by nominal eigenvalues, are easily obtained by genetic algorithm. The proposed fitness function that evaluates the gain optimization is to put sliding function. The control performance of the proposed algorithm is evaluated by the simulation and experiment to apply to the Stewart platform. The results showed high accuracy and good performance.

Improving tracking performance of industrial SCARA robots using a new sliding mode control algorithm

This paper addresses the implementation of a new sliding mode control algorithm for high speed and high precision tasks, which is robust against variations in the robot parameters and load. The effects of nonlinear dynamics, which are difficult to model accurately, become prominent in high speed operations. This paper attempts to treat the nonlinear dynamics of a SCARA robot as a disturbance. Based upon this approach, a new sliding mode control algorithm is proposed, in which a switching control input can be obtained easily and is determined to satisfy the existence condition for sliding mode control. A graphic simulator is used to evaluate the proposed algorithm for a SCARA robot. Simulation results show that the proposed algorithm is robust against disturbances and can reduce the magnitude of chattering, which is an unavoidable problem in sliding mode control. Experiments are carried out to validate the simulated results with an industrial SCARA robot using DSPs.

Variability analysis of lower extremity joint kinematics during walking in healthy young adults

The first objective of this study was to determine the kinematic variability of the lower extremity joints using methods from the mathematical chaos theory in a normal walking environment in conjunction with a large population of healthy young adults. The second objective was to test the hypothesis that variability characteristics are different between joints and to further investigate differences between male and female and right and left subgroups. A total of forty young healthy subjects (20 males: 24.1+/-3.1 years; 20 females: 22.5+/-3.2 years) volunteered, and their joint motions were captured while walking on a treadmill for 90 s in order to estimate Lyapunov Exponent (LE) values. Means and standard deviations of the LEs ranged from 0.035+/-0.016 (right ankle) to 0.073+/-0.023 (left knee) for the male subjects and from 0.028+/-0.014 (left ankle) to 0.065+/-0.028 (right hip) for the female subjects. Between the males and females, differences in LEs were observed to be statistically significant only for the left knee. There were no statistically significant differences between the right and left sides of the joints. However, differences between joints were statistically significant except between the hip and knee. These results are the first such comparison of the variability in the lower extremity without the confounding effect of walking speed on the variability of joint motions, and can serve as a normative database.

Implementation of a new sliding mode control for SCARA robot

This paper addresses the implementation of a new sliding mode control algorithm for a high speed/precision controller which is robust against the variation of robot parameters and load. The nonlinear dynamics become prominent in high speed operation but can hardly be modeled accurately. Therefore, we consider the nonlinear inertia, Coriolis and centrifugal force terms as external disturbances. This approach is applied to sliding mode control to obtain switching control inputs. The control input obtained satisfy the existence condition of sliding mode. A dynamic simulator has been developed and used to evaluate the proposed algorithm for SCARA robots. Simulated results show that the proposed algorithm is robust against disturbances and reduces the amount of chattering. An experiment was performed to demonstrate the simulated results in a real system.

Gait Study on the Normal and ACL Deficient Patients After Ligament Reconstruction Surgery Using Chaos Analysis Method

The anterior cruciate ligament(ACL) is an important stabilizer of knee joint. The ACL injury of knee is common and a serious ACL injury leads to ligament reconstruction surgery. Gait analysis is essential to identify knee condition of patients who display abnormal gait. The purpose of this study is to evaluate and classify knee condition of ACL deficient patients using a nonlinear dynamic method. The nonlinear method focuses on understanding how variations in the gait pattern change over time. The experiments were carried out for 17 subjects(l2 healthy subjects and five subjects with unilateral deficiency) walking on a motorized treadmill for 100 seconds. Three dimensional kinematics of the lower extremity were collected by using four cameras and KWON 3D motion analysis system. The largest Lyapunov exponent calculated from knee joint flexion-extension time series was used to quantify knee stability. The results revealed the difference between healthy subjects and patients. The deficient knee was significantly unstable compared with the contralateral knee. This study suggests an evaluation scheme of the severity of injury and the level of recovery. The proposed Lyapunov exponent can be used in rehabilitation and diagnosis of recoverable patients.

Measurement and three-dimensional graphic representations of Korean seatpan and seatback contours

Abstract In order to evaluate and design seats ergonomically, a human-seat interface model was developed as part of a multi-factorial ergonomic design study. It used three-dimensional computer graphics: a Korean contour model for the seatpan and the seatback. Using seatpan and seatback contour measuring equipment, a 18 × 15 and 15 × 15 contour was developed for each subject. The proposed systematic approach of quantitative measurements and evaluation will provide for performance and comfort in seating.

Implementation of a Robust Dynamic Control for SCARA Robot

A control system for SCARA robot is designed for implementing a robust dynamic control algorithm. This study focuses on the use of DSPs in the design of joint controllers and interfaces in between the host controller and four joint controllers and in between the joint controllers and four servo drives. The mechanical body of SCARA robot and the servo drives, are selected from the commercially available products. The four joint controllers, assigned to each joint separately, are combined into a common system through the mother board hardwarewise and through the global memory softwarewise. The mother board is designed to connect joint controllers onto the board through the slots adopting PC/104 bus structures. The global memory stores the common data which can be shared by joint controllers and used by the host computer directly, and it virtually combines the whole system into one. To demonstrate the performance and efficiency of the system, a robust inverse dynamic algorithm is proposed and implemented for a faster and more precise control. The robust inverse dynamic algorithm is basically derived from an inverse dynamic algorithm and a PID compensator. Based upon the derived dynamic equations of SCARA robot, the inverse dynamic algorithm is initially implemented with l msec of control cycle—0.3 msec is actually used for the control algorithm—in this system. The algorithm is found to be inadequate for the high speed and precision tasks due to inherent modelling errors and time-varying factors. Therefore a variable PID algorithm is combined with the inverse dynamic algorithm to reinforce robustness of control. Experimental data using the proposed algorithm are presented and compared with the results obtained from the PID and the inverse dynamic algorithms.