• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.3
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• pp.311-316
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• 2009

This paper presents the motion estimation algorithm on real-time for mobile surveillance robot using particle filter. the particle filter that based on the monte carlo's sampling method, use bayesian conditional probability model which having prior distribution probability and posterior distribution probability. However, the initial probability density was set to define randomly in the most of particle filter. In this paper, we find first the initial probability density using Sum of Absolute Difference(SAD). and we applied it in the partical filter. In result, more robust real-time estimation and tracking system on the randomly moving object was realized in the mobile surveillance robot environments.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.26 no.2
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• pp.223-229
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• 2017

Recently, robotic bin-picking tasks have drawn considerable attention, because flexibility is required in robotic assembly tasks. Generally, stereo camera systems have been used widely for robotic bin-picking, but these have two limitations: First, computational burden for solving correspondence problem on stereo images increases calculation time. Second, errors in image processing and camera calibration reduce accuracy. Moreover, the errors in robot kinematic parameters directly affect robot gripping. In this paper, we propose a method of correcting the bin-picking error by using trinocular vision system which consists of two stereo cameras andone hand-eye camera. First, the two stereo cameras, with wide viewing angle, measure object's pose roughly. Then, the 3rd hand-eye camera approaches the object, and corrects the previous measurement of the stereo camera system. Experimental results show usefulness of the proposed method.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.3
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• pp.330-336
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• 2005

Existing Bayesian update method using ultrasonic sensors only for mobile robot map building has a problem of the quality of map being degraded in the wall with irregularity, which is caused by the wide beam distribution. For improving this problem, an infrared sensors aided map building method is presented in this paper. Information of obstacle at each region in ultrasonic sensor beam is acquired using the infrared sensors and the information is used to get the confidence of ultrasonic sensor information via fuzzy inference system and genetic algorithm. Combining the resulting confidence with the result of Bayesian update method, an improve map is constructed. The proposed method showed good results in the simulations and experiments.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.8
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• pp.603-609
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• 2016

This paper presents an optimally designed master device mechanism for teleoperated interventional robotic system. The interventional procedures using the teleoperated robotic system and the physicians' requirements are summarized. The master device should implement 5-DOF motion including 2-DOF translational motion for the entry position control, 2-DOF rotational motion for the orientation control, and 1- DOF translational motion for needle insertion. The handle assembly includes a 1-DOF translational mechanism for needle insertion and buttons for operation mode selection. The mechanisms for the 2-DOF translational motion and the 2-DOF rotational motion are designed using motors and brakes based on the various mechanisms to satisfy all the above requirements, respectively. Absolute position sensors are adopted to implement automatic initial positioning and orientation matching at the first step of needle insertion.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.10
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• pp.847-852
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• 2016

In this paper, important design parameters for parallel kinematic robots are defined, paying special attention to machining errors which may cause kinematic errors at the end effector of a robot. The kinematic effects caused by each design parameter, as well as their upper/lower limits, are analyzed here. To do so, we have developed a novel software program to compute kinematic errors by considering its defined design parameters. With this program, roboticists designing parallel kinematic robots can understand the important design parameters for which upper/lower allowances have to be strictly controlled in the design process. This tactic can be used for the design of high-speed, parallel kinematic robots to reduce the design/manufacturing costs and increase kinematic precision.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.4
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• pp.505-510
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• 2005

The RPO(randomized policy optimizer) algorithm, which utilizes probabilistic policy for the action selection, is a recently developed tool in the area of reinforcement learning, and has been shown to be very successful in several application problems. In this paper, we propose a modified RPO algorithm, whose critic network is adapted via RLS(Recursive Least Square) algorithm. In order to illustrate the applicability of the modified RPO method, we applied the modified algorithm to Kimura's robot and observed very good performance. We also developed a MATLAB-based animation program, by which the effectiveness of the training algorithms on the acceleration or the robot movement were observed.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.3
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• pp.242-247
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• 2008

As an absolute positioning system, iGS is designed based on ultrasonic signals whose speed can be formulated clearly in terms of time and room temperature, which is utilized for a mobile robot localization. The iGS is composed of an RFID receiver and an ultra-sonic transmitter, where an RFID is designated to synchronize the transmitter and receiver of the ultrasonic signal. The traveling time of the ultrasonic signal has been used to calculate the distance between the iGS system and a beacon which is located at a pre-determined location. This paper suggests an effective operation method of iGS to estimate position of the mobile robot working in unstructured environment. To expand recognition range and to improve accuracy of the system, two strategies are proposed: utilization of beacons belonging to neighboring blocks and removal of the environment-reflected ultrasonic signals. As the results, the ubiquitous localization system based on iGS as a pseudo-satellite system has been developed successfully with a low cost, a high update rate, and relatively high precision.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.3
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• pp.211-217
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• 2011

This paper proposes a quasi-optimal linear DOA (Direction-of-Arrival) estimator which is necessary for the development of a real-time robot auditory system tracking moving acoustic source. It is well known that the use of conventional nonlinear filtering schemes may result in the severe performance degradation of DOA estimation and not be preferable for real-time implementation. These are mainly due to the inherent nonlinearity of the acoustic signal model used for DOA estimation. This motivates us to consider a new uncertain linear acoustic signal model based on the linear prediction relation of a noisy sinusoid. Using the suggested measurement model, it is shown that the resultant DOA estimation problem is cast into the NCRKF (Non-Conservative Robust Kalman Filtering) problem [12]. NCRKF-based DOA estimator provides reliable DOA estimates of a fast moving acoustic source in spite of using the noise-corrupted measurement matrix in the filter recursion and, as well, it is suitable for real-time implementation because of its linear recursive filter structure. The computational efficiency and DOA estimation performance of the proposed method are evaluated through the computer simulations.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.10
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• pp.1067-1072
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• 2014

The ability to overcome obstacles is necessary for field robots for various applications including the ability to climb stairs. While much research has been performed focusing on overcoming obstacles, the resulting robots do not have sufficient ability to overcome obstacles such as stairs. In this research, the purpose is to overcome relatively large obstacles by flipping locomotion through the modification of the stair climbing robotic platform of the previous research. We propose two scenarios to overcome large obstacles: a rear wheel driving system and an elevation system using a ball screw. The research is performed based on static analyses on obstacle-climbing. As the simulation results indicate, we determined the optimal posture of the robot for climbing obstacles for rear wheel driving. Also, an elevation system is analyzed for obstacle climbing. Between the two scenarios an elevation system is determined to reduce the operating torque of the actuator, and the prototype was recently assembled. The climbing ability of the robotic platform is verified. We expect the application area for this robotic platform will be in accident areas of nuclear power plants.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.10
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• pp.1063-1066
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• 2014

The humanoid robot, DRC-HUBO is developed from the KHR (KAIST Humanoid Robot) series to meet the requirements of the DARPA Robotics Challenge. DARPA Robotics Challenge was a competition to develop semi-autonomous humanoid robot so that dispatched in dangerous environments in place of humans like the Fukushima nuclear accident. In this paper, we introduce DRCH-UBO briefly and a methodology to remove debris blocking an entryway. The methodology includes inverse kinematics for DRC-HUBO and stabilization controller based on ZMP. Proposed inverse kinematics is robust, and pelvis-related tasks improve the manipulability and workspace of the arms. The controller improves the damping characteristic of the system and mitigates the instability during removal of debris. For given position and orientation of the debris, DRC-HUBO generates motion to reach the debris and lift up while stabilizing itself. Many experimental results verify our proposed methodology.