• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.55-57
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• 2018

In Simultaneous Localization and Mapping (SLAM), the robot acquire its map of environment while simultaneously localize itself relative to the map. Now a day, a map acquired by the mobile robots limit to specific area, in an indoor environment and cannot able to navigate autonomous between different floors. We propose a design that could able to overcome this issue in order to navigate multiple floors with one end goal mission to a target destination in the course of autonomous navigation. In this research, we consider all the floors have identical structural arrangement. Internet of Things (IoT) playing crucial role in bridging between "things" and Robot Operating System (ROS) enabled mobile robots.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.10 no.6
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• pp.36-41
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• 2001

This article presents a new acceleration/deceleration method for real-time control of autonomous mobile robots. In this method, a function which produces the table of acceleration/deceleration in real-time is proposed. This function, while sat- isfying the basic concept of mechanics, can choose both various ranges of velocity and distance ranges for the selected velocities. Moreover it can control motors in real time. This function is convenient to be realized by programming. In addi- tion, it is faster than other functions because it can be written by assembly language.

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.2464-2466
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• 2001

In this paper, a behavior-based fuzzy control of mobile robots for autonomous navigation is presented. Behaviors of mobile robots are divided into two categories: reactive behavior and purposeful behavior, which are incompatible with each other. The former is reaction performed in terms of the sensory data and the latter is action for achieving the goal. The presented method generates appropriate control inputs to the robot to trade-off between the reactive and purposeful behaviors using fuzzy inferences. The method is applied to an synchro-drive type mobile robot and shown to be useful for autonomous robot navigation by providing simulation results.

• IEMEK Journal of Embedded Systems and Applications
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• v.18 no.5
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• pp.249-257
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• 2023

This paper discusses the increasing need for autonomous delivery robots due to the current growth in the delivery market, rising delivery fees, high costs of hiring delivery personnel, and the need for contactless services. Additionally, the cost of hardware and complex software systems required to build and operate autonomous delivery robots is high. To provide a low-cost alternative to this, this paper proposes a autonomous delivery robot platform using a low-cost sensor combination of 2D LIDAR, depth camera and tracking camera to replace the existing expensive 3D LIDAR. The proposed robot was developed using the RTAB-Map SLAM open source package for 2D mapping and overcomes the limitations of low-cost sensors by using the convex hull algorithm. The paper details the hardware and software configuration of the robot and presents the results of driving experiments. The proposed platform has significant potential for various industries, including the delivery and other industries.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.1
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• pp.58-69
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• 2014

This paper proposes a method for predicting maximum friction coefficients and optimal slip ratios as optimal control parameters for traction control or slip control of autonomous mobile robots on rough terrain. This paper focuses on strength of ground surface which indicates different characteristics depending on material types on surface. Strength of various material types can be estimated by Willoughby sinkage model and by a developed testbed which can measure forces, velocities, and displacements generated by wheel-terrain interaction. Estimated strength is collaborated on building improved Brixius model with friction-slip data from experiments with the testbed over sand and grass material. Improved Brixius model covers widespread material types in outdoor environments on predicting friction-slip characteristics depending on strength of ground surface. Thus, a prediction model for obtaining optimal control parameters is derived by partial differentiation of the improved Brixius model with respect to slip. This prediction model can be applied to autonomous mobile robots and finally gives secure maneuverability on rough terrain. Proposed method is verified by various experiments under similar conditions with the ones for real outdoor robots.

• The Journal of Korea Robotics Society
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• v.19 no.3
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• pp.311-317
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• 2024

Large-scale three-wheeled cleaning robots are utilized to clean large spaces such as warehouses and manufacturing plants where significant floor contamination occurs. Although there are autonomous cleaning robots, user-operated cleaning robots are often preferred because they are easy to repair and inexpensive. Therefore, workers have to spend extra time on cleaning, which reduces work efficiency. In this paper, we propose an autonomous driving system designed to automate the operation while maintaining the structure of existing cleaning robots. The contributions of this paper are as follows: 1) Hardware modules that control the driving and steering components. 2) A LiDAR-based autonomous driving system and path point generation system considering the mechanical characteristics of the cleaning robot. 3) The proposed system is implemented on an actual cleaning robot and driving tests are performed. As a result, when path planning is performed to cover the cleaning area, the average RMSE for each straight path is 0.0802 m, which is smaller than the minimum cleaning overlap of 0.3 m that occurs during the straight cleaning of the robot. This shows that the proposed system effectively covers the entire cleaning area.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.4
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• pp.611-616
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• 2018

With the recent increase in awareness of the diversification of patterns of warfare and security, technological evolution is occurring in the field of autonomous defense robots. As defense science and technology develops with the development of the concept of military utilization focusing on human lives and economic operation, the importance of autonomous robots in the effect-oriented future battlefield is increasing. The major developed countries have developed core technologies, investment strategies, priorities, data securing strategies and infrastructure development related to the field of autonomous defense robots, and research activities such as technology planning and policy strategy for autonomous defense robots in Korea have already begun. In addition, the field of autonomous defense robots encompasses technologies that represent the fourth industrial revolution, such as artificial intelligence, big data, and virtual reality, and so the expectations for this future area of technology are very high. It is difficult to predict the path of technological development due to the increase in the demand for new rather than existing technology. Moreover, the selection and concentration of strategic R&D is required due to resource constraints. It is thought that a preemptive response is needed. This study attempts to derive 6 new technologies that will shape the future of autonomous defense robots and to obtain meaningful results through an empirical study.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.846-851
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• 2004

In this paper, we propose a global ultrasonic system for the self-localization and autonomous navigation of indoor mobile robots. The ultrasonic sensor is regarded as the most cost-effective ranging system among the possible alternatives, and it is widely used for general purpose, since it requires simple electronic drivers and has relatively high accuracy. The global ultrasonic system presented in this paper consists of four or more ultrasonic generators fixed at reference positions in the global coordinates of an indoor environment and two receivers mounted on the mobile robots. By using the RF (Radio Frequency) modules added to the ultrasonic sensors, the robot is able to control the ultrasonic generation and to obtain the critical distances from the reference positions, which are required in order to localize is position in the global coordinates. A kalman filter algorithm designed for the self-localization using the global ultrasonic system and the experimental results of the autonomous navigation are presented in this paper.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.51 no.5
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• pp.182-189
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• 2002

This paper presents a framework of hybrid dynamic control systems for the motion control of wheeled mobile robot systems with nonholonomic constraints. The hybrid control system has the 3-layered hierarchical structure: digital automata for the higher process, mobile robot system for the lower process, and the interface as the interaction process between the continuous dynamics and the discrete dynamics. In the hybrid control architecture of mobile robot, the continuous dynamics of mobile robots are modeled by the switched systems. The abstract model and digital automata for the motion control are developed. In high level, the discrete states are defined by using the sensor-based search windows and the reference motions of a mobile robot in low level are specified in the abstracted motions. The mobile robots can perform both the motion planning and autonomous maneuvering with obstacle avoidance in indoor navigation problem. Simulation and experimental results show that hybrid system approach is an effective method for the autonomous maneuvering in indoor environments

• The Journal of Korea Robotics Society
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• v.9 no.1
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• pp.1-10
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• 2014

In recent years, the research of 3D mapping technique in urban environments obtained by mobile robots equipped with multiple sensors for recognizing the robot's surroundings is being studied actively. However, the map generated by simple integration of multiple sensors data only gives spatial information to robots. To get a semantic knowledge to help an autonomous mobile robot from the map, the robot has to convert low-level map representations to higher-level ones containing semantic knowledge of a scene. Given a 3D point cloud of an urban scene, this research proposes a method to recognize the objects effectively using 3D graph model for autonomous mobile robots. The proposed method is decomposed into three steps: sequential range data acquisition, normal vector estimation and incremental graph-based segmentation. This method guarantees the both real-time performance and accuracy of recognizing the objects in real urban environments. Also, it can provide plentiful data for classifying the objects. To evaluate a performance of proposed method, computation time and recognition rate of objects are analyzed. Experimental results show that the proposed method has efficiently in understanding the semantic knowledge of an urban environment.