• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1589-1592
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• 1997

Among the prerequisite abilities (perception of environment, path planning and position estimation) of an autonomous mobile robot, position estimation has been seldom studied by mobile robot researchers. In most cases, conventional positioin estimation has been performed by placing landmarks or giving the entrire environmental information in advance. Unlikely to the conventional ones, the study addresses a new method that the robot itself can select distinctive features in the environment and save them as landmarks without any a priori knowledge, which can maximize the autonomous behavior of the robot. First, an orjentaion probaility model is applied to construct a lcoal map of robot's surrounding. The feature of the object in the map is then extracted and the map is saved as landmark. Also, presented is the position estimation method that utilizes the correspondence between landmarks and current local map. In dong this, the uncertainty of the robot's current positioin is estimated in order to select the corresponding landmark stored in the previous steps. The usefulness of all these approaches are illustrated with the results porduced by a real robot equipped with ultrasonic sensors.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.8 no.5
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• pp.76-82
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• 1999

During operating given working a robot manipulator makes some problems such as the accumulation of the error or the deviation from the command trajectory. These problems are mainly due to the disturbance noise or unmodeled system parameters. To solve these problems most of robot manipulators equip the controller. But if exact controller gains are not seleced we can't decrease the working efficiency(such as compensation about error or deviation) of the robot manipulator. So in this paper we present the controller gain tuning law by which we can find the controller gain which satisfies the per-formance specification of the robot manipulator during working of the robot. The proposed algorithm is derived from the Laypunov direct method. And by the simulation on the 4-axis SCARA type robot(SAMSUNG SM5 Robot) we guarantee the performance of this algorithm.

• Journal of Auto-vehicle Safety Association
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• v.14 no.2
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• pp.51-56
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• 2022

This paper presents an Ground Segmentation algorithm to eliminate unnecessary Lidar Point Cloud Data (PCD) in an autonomous driving system. We consider Random Sample Consensus (Ransac) Algorithm to process lidar ground data. Ransac designates inlier and outlier to erase ground point cloud and classified PCD into two parts. Test results show removal of PCD from ground area by distinguishing inlier and outlier. The paper validates ground rejection algorithm in real time calculating the number of objects recognized by ground data compared to lidar raw data and ground segmented data based on the z-axis. Ground Segmentation is simulated by Robot Operating System (ROS) and an analysis of autonomous driving data is constructed by Matlab. The proposed algorithm can enhance performance of autonomous driving as misrecognizing circumstances are reduced.

• Transactions of the Korean Society of Mechanical Engineers
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• v.19 no.2
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• pp.568-579
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• 1995

An off-line programming (OLP) system was proposed and developed in order to save cost and time in adjusting a robot to new workcells or applying new algorithms to actual trajectory planning. The developed OLP system was especially designed to be operated in a PC level host computer. A SCARA robot with four axes was selected as an objective robot. The OLP system developed in this study consisted of such modules as data base, three-dimensional graphics, kinematics, trajectory planning, dynamics, control, and commands. Each module was constructed to form an independent unit so that it can be easily modified or improved. The OLP system was programmed for a graphic user interface in Borland $C^{++}$ language. Some of system operating commands and an interpreter were devised and used for more convenient programming of robot simulations.s.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2011.06a
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• pp.317-318
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• 2011

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1994.10a
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• pp.323-329
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• 1994

In the systems such as walking robots or high speed operating manipulators, the effect of nonlinear terms is important and can not be neglected. Therefore the application of linear control law to such systems is inadequate. Moreover, because of the mathematical modeling errors the systems may become unstable. In this study, we designed a nonlinear controller with sliding mode scheme, which is robust to the modeling errors and applied this control algorithm to the 5 DOF biped robot system. Throught the computer simulations, we examined walking characteris and walking stability of the 5 DOF biped robot system.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.5
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• pp.434-443
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• 2007

Presently, the exploration of an unknown environment is an important task for thee new generation of mobile service robots and mobile robots are navigated by means of a number of methods, using navigating systems such as the sonar-sensing system or the visual-sensing system. To fully utilize the strengths of both the sonar and visual sensing systems. This paper presents a technique for localization of a mobile robot using fusion data of multi-ultrasonic sensors and vision system. The mobile robot is designed for operating in a well-structured environment that can be represented by planes, edges, comers and cylinders in the view of structural features. In the case of ultrasonic sensors, these features have the range information in the form of the arc of a circle that is generally named as RCD(Region of Constant Depth). Localization is the continual provision of a knowledge of position which is deduced from it's a priori position estimation. The environment of a robot is modeled into a two dimensional grid map. we defines a vision-based environment recognition, phisically-based sonar sensor model and employs an extended Kalman filter to estimate position of the robot. The performance and simplicity of the approach is demonstrated with the results produced by sets of experiments using a mobile robot.

• IEMEK Journal of Embedded Systems and Applications
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• v.15 no.2
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• pp.87-94
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• 2020

This paper introduces a method to control an industrial robot arm to imitate the movement of the human arm and hand using electromyography (EMG) signals. The proposed method is implemented on the UR3 robot that is a popular industrial robot and a MYO armband that measure the EMG signals generated by human muscles. The communications for the UR3 robot and the MYO armband are integrated in the robot operating system (ROS) that is a middle-ware to develop robot systems easily. The movement of the human arm and hand is detected by the MYO armband, which is utilized to recognize and to estimate the speed of the movement of the operator's arm and the motion of the operator's hand. The proposed system can be easily used when human's detailed movement is required in the environment where human can't work. An experiments have been conducted to verify the performance of the proposed method using the teleoperation of the UR3 robot.

• Nuclear Engineering and Technology
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• v.54 no.6
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• pp.2198-2203
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• 2022

As robotics become more sophisticated, there are a growing number of generic systems being used for routine tasks in nuclear environments to reduce risk to radiation workers. The nuclear sector has called for more commercial-off-the-shelf (COTS) devices and components to be used in preference to nuclear specific hardware, enabling robotic operations to become more affordable, reliable, and abundant. To ensure reliable operation in nuclear environments, particularly in high-gamma facilities, it is important to quantify the tolerance of electronic systems to ionizing radiation. To deliver their full potential to end-users, mobile robots require sophisticated autonomous behaviors and sensing, which requires significant computational power. A popular choice of computing system, used in low-cost mobile robots for nuclear environments, is the UP Core single board computer. This work presents estimates of the total ionizing dose that the UP Core running the Robot Operating System (ROS) can withstand, through gamma irradiation testing using a Co-60 source. The units were found to fail on average after 111.1 ± 5.5 Gy, due to faults in the on-board power management circuitry. Its small size and reasonable radiation tolerance make it a suitable candidate for robots in nuclear environments, with scope to use shielding to enhance operational lifetime.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.1
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• pp.52-57
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• 2014

This paper presents an implementation of a smooth path planning method considering physical limits on a real time operating system for a two-wheel mobile robot. A Bezier curve is utilized to make a smooth path considering a robot's position and direction angle through the defined path. A convolution operator is used to generate the center velocity trajectory to travel the distance of the planned path while satisfying the physical limits. The joint space velocity is computed to drive the two-wheel mobile robot from the center velocity. Trajectory planning, velocity command according to the planned trajectory, and monitoring of encoder data are implemented with a multi-tasking system. And the synchronization of tasks is performed with a real-time mechanism of Event Flag. A real time system with multi-tasks is implemented and the result is compared with a non-real-time system in terms of path tracking to the designed path. The result shows the usefulness of a real-time multi-tasking system to the control system which requires real-time features.