• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.4
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• pp.549-557
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• 2021

In this research, we will use the existing OID sensor environment for smart robots, which are a type of educational robot, but we would like to propose that the problem of running be handled by a program. Maybe you have driving information We are building a driving test environment focusing on environment, position recognition, route planning, obstacle avoidance and path reset, and it is not the average final error rate, but the time when the error increases The experiment was conducted by a household that catches the moment of recalibration. Through the process, stable running results were obtained compared to the previous experiment. In this research, I think that it will be a development method that can improve the running performance of educational robots equipped with low-cost sensors currently on the market.

• IEMEK Journal of Embedded Systems and Applications
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• v.17 no.2
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• pp.123-128
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• 2022

This paper proposes a mobile robot platform for education that can experiment with various autonomous driving algorithms such as obstacle avoidance and path planning. The platform consists of a robot module and a remote controller module, both of which are based on the Arduino Nano 33 IoT embedded board. The robot module is designed as a differential drive type using two encoder motors, and the speed of the motor is controlled using PID control. In the case of the remote controller module, a command to control the robot platform is received with a 2-axis joystick input, and an elliptical grid mapping technique is used to convert the joystick input into a linear and angular velocity command of the robot. WiFi and Zigbee are used for communication between the robot module and the remote controller module. The proposed robot platform was tested by measuring and comparing the linear velocity and angular velocity of the actual robot according to the linear velocity and angular velocity commands of the robot generated by the input of the joystick.

• Journal of IKEEE
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• v.25 no.4
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• pp.584-590
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• 2021

This paper proposes a removal method of signal interference between ultrasound sensors where ghost signals due to interference are excluded and correct signal is recognized in distance mensurement using ultrasound sensors. The proposed method detects and excludes ghost signals when previous measured distance is compared to current measured distance and the distance difference exceeds a threshold. The threshold is fixed in conventional methods, so ghost signals cannot be correctly excluded when ultrasound sensor or target object move rapidly. On the contrary, to improve accuracy, the threshold is not fixed in the proposed method, and the threshold is adpatively determined based on the relative velocity when ultrasound sensor or target object move. Experiments of distance measurement with ultrasound signal interference are carried out where multiple ultrasound sensors of same type are exploited with maximum interference, and the results show that the proposed method efficiently exclude ghost signals.

• Journal of IKEEE
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• v.26 no.2
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• pp.169-175
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• 2022

This paper introduces an interference elimination method using k-nearest neighbor (KNN) algorithm for precise distance estimation by reducing interference between ultrasonic sensors. Conventional methods compare current distance measurement result with previous distance measurement results. If the difference exceeds some thresholds, conventional methods recognize them as interference and exclude them, but they often suffer from imprecise distance prediction. KNN algorithm classifies input values measured by multiple ultrasonic sensors and predicts high accuracy outputs. Experiments of distance measurements are conducted where interference frequently occurs by multiple ultrasound sensors of same type, and the results show that KNN algorithm significantly reduce distance prediction errors. Also the results show that the prediction performance of KNN algorithm is superior to conventional voting methods.

• The Journal of Korea Robotics Society
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• v.16 no.4
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• pp.327-335
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• 2021

In this paper, we propose an embedded robot system based on "ROS2 on Yocto" that can support various robots. We developed a lightweight OS based on the Yocto Project as a next-generation robot platform targeting cloud robotics. Yocto Project was adopted for portability and scalability in both software and hardware, and ROS2 was adopted and optimized considering a low specification embedded hardware system. We developed SLAM, navigation, path planning, and motion for the proposed robot system validation. For verification of software packages, we applied it to home cleaning robot and indoor delivery robot that were already commercialized by LG Electronics and verified they can do autonomous driving, obstacle recognition, and avoidance driving. Memory usage and network I/O have been improved by applying the binary launch method based on shell and mmap application as opposed to the conventional Python method. Finally, we verified the possibility of mass production and commercialization of the proposed system through performance evaluation from CPU and memory perspective.

• Proceedings of the Korea Information Processing Society Conference
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• 2009.04a
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• pp.15-18
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• 2009

지능형 휠체어 구현에 있어 초음파 센서의 배열은 전동휠체어가 장애물을 감지할 수 있는 능력을 결정한다. 따라서 본 논문에서는 지능형 휠체어의 장애물 감지를 위한 초음파 센서의 효과적인 배열 방법을 제안한다. 초음파 센서 모듈은 총 10개의 4개 세트로 구성되어 있다. 전동 휠체어의 전방, 좌, 우측에는 각각 3개의 센서를 48도씩 중첩되게 겹쳐 하나의 세트로 구성하고, 후방에는 하나의 센서를 구성한다. 지능형 휠체어는 사용자 인터페이스, 장애물 회피 모듈, 모터 제어 모듈, 초음파 센서 모듈로 구성된다. 사용자 인터페이스는 정해진 명령을 하달 받고, 모터 제어 모듈은 하달된 명령과 센서들에 의해 반환된 장애물과의 거리 정보로 모터제어보드에 연결되어 있는 두 개의 좌우 모터들을 조종한다. 센서 모듈은 전동휠체어가 움직이는 동안에 주기적으로 센서들로부터 거리 값을 반환 받아 벽 또는 장애물을 감지하여 장애물의 위치를 사용자 인터페이스를 통해서 알려 주고, 또한 장애물 회피 모듈에 의해 장애물을 우회 하도록 움직인다. 제안된 방법의 센서 배열은 실험을 통해 지능형 휠체어가 임의로 설치된 장애물을 효과적으로 감지하고 보다 정확하게 장애물을 회피 할 수 있음을 보였다.

• International conference on construction engineering and project management
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• 2005.10a
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• pp.539-543
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• 2005

The research presented in this paper enables real-time 3D modeling to help make construction processes ultimately faster, more predictable and safer. Initial research efforts used an emerging sensor technology and proved its usefulness in the acquisition of range information for the detection and efficient representation of static and moving objects. Based on the time-of-flight principle, the sensor acquires range and intensity information of each image pixel within the entire sensor's field-of-view in real-time with frequencies of up to 30 Hz. However, real-time working range data processing algorithms need to be developed to rapidly process range information into meaningful 3D computer models. This research ultimately focuses on the application of safer heavy equipment operation. The paper compares (a) a previous research effort in convex hull modeling using sparse range point clouds from a single laser beam range finder, to (b) high-frame rate update Flash LADAR (Laser Detection and Ranging) scanning for complete scene modeling. The presented research will demonstrate if the FlashLADAR technology can play an important role in real-time modeling of infrastructure assets in the near future.

• Nuclear Engineering and Technology
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• v.54 no.11
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• pp.4030-4048
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• 2022

In this study, road transportation tests were conducted with surrogate fuel assemblies under normal conditions of transport to evaluate the vibration and shock load characteristics of spent nuclear fuel (SNF). The overall test data analysis was conducted based on the measured acceleration and strain data obtained from the speed bump, lane-change, deceleration, obstacle avoidance, and circular tests. Furthermore, representative shock response spectrums and power spectral densities of each test mode were acquired. Amplification or attenuation characteristics were investigated according to the load transfer path. The load attenuated significantly as it transferred from the trailer to the cask. By contrast, the load amplified as it transferred from the cask to the surrogate SNF assembly. The fuel loading location on the cask disk assembly did not exhibit a significant influence on the strain measured from the fuel rods. The principal strain was in the vertical direction, and relatively large strain values were obtained in spans with large spacing between spacer grids. The influence of the lateral location of fuel rods was also investigated. The fuel rods located at the side exhibited relatively large strain values than those located at the center. Based on the strain data obtained from the test results, a hypothetical road transportation scenario was established. A fatigue evaluation of the SNF rod was performed based on this scenario. The evaluation results indicate that no fatigue damage occurred on the fuel rods.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.94-96
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• 2021

In this paper, we develop a new navigation algorithm for industrial mobile robots to arrive at the destination in unknown environment. To achieve this, we suggest a navigation algorithm that combines Dynamic Window Approach (DWA) and Dijkstra path planning algorithm. We compare Local Dynamic Window Approach (LDWA), Global Dynamic Window Approach(GDWA), Rapidly-exploring Random Tree (RRT) Algorithm. The navigation algorithm using Dijkstra algorithm combined with LDWA and GDWA makes mobile robots to reach the destination. and obstacles faced during the path planning process of LDWA and GDWA. Then, we compare on time taken to arrive at the destination, obstacle avoidance and computation complexity of each algorithm. To overcome the limitation, we seek ways to use the optimized navigation algorithm for industrial use.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2023.05a
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• pp.221-222
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• 2023

The purpose of this study is to analyze the applicability and limitations of SPOT robots in the construction industry. The SPOT robot, which is being introduced to construction sites for smart construction with the progress of the 4th industrial revolution, is shaped like a four-legged dog and is equipped with various sensors for data collection and autonomous driving. In this study, hardware and software were analyzed, such as the size of the SPOT robot, mobility on slopes and heights, operating environment, and software functions that can collect data with a sensor weighing up to 14 kg. In addition, while the SPOT robot operates in a construction environment, performance such as stability, accuracy, signal connection distance, and obstacle avoidance are evaluated, and the applicability and limitations of the SPOT robot in the construction industry are analyzed. Based on this analysis, the purpose of this study is to evaluate when and how SPOT robots can be effectively used at construction sites, identify limitations, and derive contributions and improvements for the construction industry.