• Journal of Institute of Control, Robotics and Systems
• /
• v.16 no.5
• /
• pp.463-468
• /
• 2010

An obstacle avoidance method for a mobile robot is proposed in this paper. Our research was focused on the obstacles that can be found indoors since a robot is usually used within a building. It is necessary that the robot maintain the desired direction after successfully avoiding the obstacles to achieve a good autonomous navigation performance for the specified project mission. Sensors such as laser, ultrasound, and PSD (Position Sensitive Detector) can be used to detect and analyze the obstacles. A PSD sensor was used to detect and measure the height and width of the obstacles on the floor. The PSD sensor was carefully calibrated before measuring the obstacles to achieve better accuracy. Data obtained from the repeated experiments were used to plot an error graph which was fitted to a polynomial curve. The polynomial equation was used to navigate the robot. We also obtained a direction-error model of the robot after avoiding the obstacles. The prototypes for the obstacle and direction-error were modeled using a neural network whose inputs are the obstacle height, robot speed, direction of the wheels, and the error in direction. A mobile robot operated by a notebook computer was setup and the proposed algorithm was used to navigate the robot and avoid the obstacles. The results showed that our algorithm performed very well during the experiments.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.39C no.11
• /
• pp.1177-1184
• /
• 2014

An wired ship area network has functionality of remote control and autonomous management of various sensors and instruments embedded or boarded in a ship. For such environment, the DiffServ (Differentiated Services) realizes that the high-speed real-time flow with the higher priority has the guaranteed minimum data rate and is delivered faster. As a result of this DiffServ effect, the intelligent Ship Area Networks can be implemented. In this paper, an packet drop technique is proposed to outperform the previous RIO (RED In and Out) drop mechanism for DiffServ in ship area networks. the proposed packet drop technique does not manage the individual flows and divides them into several flow groups according to a criterion. And it guarantees the fairness between individual flows in the same QoS class through the group-based control. In simulation results of the proposed packet drop technique, the link utilization decreases than RIO. But it guarantees more data rates to DiffServ flows passing multiple bottleneck links.

• Journal of Ocean Engineering and Technology
• /
• v.32 no.5
• /
• pp.402-409
• /
• 2018

This paper describes the plan and procedure of a development test and evaluation that will be performed to verify the performance and technology of multi-mission unmanned surface vehicles (MMUSVs). In order to verify the design requirement of MMUSVs, we designed and manufactured the common platform of MMUSVs, which have an overall length of8.4 m, a displacement of 3,100 kg, and a speed of more than35 kts. The platform is equipped with several sub-systems, including radar and an EOTS/IRS. The EOTS/IRS, along with the search radar, is used for effective detection, identification, and targeting. The core technologies of MMUSV for DT&E will be investigated. The common platform design technologies, remote operating and control system technologies, autonomous navigation technologies, and unmanned operational technology of sensors and equipment will be studied for the development of the MMUSV's core technologies. The system will be able to make precise observations and track targets both manually and automatically during day and night conditions. Currently, the verification tests for each of the technologies and for the integrated system are in the pipeline for DT&E, which will be performed next year. Also, software reliability and life tests will be performed.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.37C no.12
• /
• pp.1328-1336
• /
• 2012

Compared to terrestrial RF communications, underwater acoustic communications have several limitations such as limited bandwidth, high level of fading effects, and a large underwater propagation delay. In this paper, in order to tackle those limitations of underwater communications and to make it possible to form a large underwater monitoring systems, we propose a hierarchical underwater network architecture, which consists of underwater sensors, clusterheads, underwater/surface sink nodes, autonomous underwater vehicles (AUVs). In the proposed architecture, for the maximization of packet delivery ratio and the minimization of underwater sensor's energy consumption, a hybrid routing protocol is used. More specifically, cluster members use Tree based routing to transmit sensing data to clusterheads. AUVs on optimal trajectory movements collect the aggregated data from clusterhead and finally forward the data to the sink node. Also, in order to minimize the maximum travel distance of AUVs, an Integer Linear Programming based algorithm is employed. Performance analysis through simulations shows that the proposed architecture can achieve a higher data delivery ratio and lower energy consumption than existing routing schemes such as gradient based routing and geographical forwarding. Start after striking space key 2 times.

• The Journal of Korea Robotics Society
• /
• v.1 no.1
• /
• pp.17-24
• /
• 2006

Though the final goal of mobile robot navigation is to be autonomous, operators' intelligent and skillful decisions are necessary when there are many scattered obstacles. There are several limitations even in the camera-based tele-operation of a mobile robot, which is very popular for the mobile robot navigation. For examples, shadowed and curved areas cannot be viewed using a narrow view-angle camera, especially in bad weather such as on snowy or rainy days. Therefore, it is necessary to have other sensory information for reliable tele-operations. In this paper, sixteen ultrasonic sensors are attached around a mobile robot in a ring pattern to measure the distances to obstacles. A collision vector is introduced in this paper as a new tool for obstacle avoidance, which is defined as a normal vector from an obstacle to the mobile robot. Based on this collision vector, a virtual reflection force is generated to avoid the obstacles and then the reflection force is transferred to an operator who is holding a joystick to control the mobile robot. Relying on the reflection force, the operator can control the mobile robot more smoothly and safely. For this bi-directional tele-operation, a master joystick system using a hall sensor was designed to resolve the existence of nonlinear sections, which are usual for a general joystick with two motors and potentiometers. Finally, the efficiency of a force reflection joystick is verified through the comparison of two vision-based tele-operation experiments, with and without force reflection.

• KIPS Transactions on Software and Data Engineering
• /
• v.2 no.4
• /
• pp.239-250
• /
• 2013

Context-aware mobile computing has become the primary approach to realize automatic, autonomous, and user-centric computing in the context of largely increasing the amount of mobile devices used that embed available sensors. However, designing an inference engine nonetheless requires the tasks of analyzing contexts, situations that can be inferred, etc. Moreover, a mobile device has limited resources and limited computation capability, which results in recognizing the common sense of its unsuitable environment for processing inference. Hence, we propose context-situation reasoning elements and their formal models in this paper, and we verify the formal models' applicability by applying them to an example. Finally, we design and implement an inference engine that realize the context-situation inference elements in computing environment, and we experiment an example by using the proposed inference engine to verify applicability and reusability of the inference engine.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.52 no.7
• /
• pp.153-161
• /
• 2015

In the present study, as part of the technology development (Quality of Life Technology, QoLT) to improve the socio-economic status of people with disabilities as an extension of these studies, we propose the development of the smart wheelchair system and navigation technology for stable and safe driving in various environments. For the disabled and the elderly make driving easy and convenient with manual/autonomous driving condition, we firstly develop the user-oriented smart wheelchair system with optimized sensors for environment recognition, and then we propose a navigation framework of a hierarchical structure to ensure real-time response, as well as driving stability when traveling to various environmental changes, and to enable a more efficient operation. From the result of several independent experiments, we ensure efficiency and safety of smart wheelchair and its navigation system.

• Smart Structures and Systems
• /
• v.24 no.5
• /
• pp.567-585
• /
• 2019

In the past two decades, structural health monitoring (SHM) systems have been widely installed on various civil infrastructures for the tracking of the state of their structural health and the detection of structural damage or abnormality, through long-term monitoring of environmental conditions as well as structural loadings and responses. In an SHM system, there are plenty of sensors to acquire a huge number of monitoring data, which can factually reflect the in-service condition of the target structure. In order to bridge the gap between SHM and structural maintenance and management (SMM), it is necessary to employ advanced data processing methods to convert the original multi-source heterogeneous field monitoring data into different types of specific physical indicators in order to make effective decisions regarding inspection, maintenance and management. Conventional approaches to data analysis are confronted with challenges from environmental noise, the volume of measurement data, the complexity of computation, etc., and they severely constrain the pervasive application of SHM technology. In recent years, with the rapid progress of computing hardware and image acquisition equipment, the deep learning-based data processing approach offers a new channel for excavating the massive data from an SHM system, towards autonomous, accurate and robust processing of the monitoring data. Many researchers from the SHM community have made efforts to explore the applications of deep learning-based approaches for structural damage detection and structural condition assessment. This paper gives a review on the deep learning-based SHM of civil infrastructures with the main content, including a brief summary of the history of the development of deep learning, the applications of deep learning-based data processing approaches in the SHM of many kinds of civil infrastructures, and the key challenges and future trends of the strategy of deep learning-based SHM.

• Smart Structures and Systems
• /
• v.6 no.5_6
• /
• pp.439-459
• /
• 2010

Structural health monitoring (SHM) of civil infrastructure using wireless smart sensor networks (WSSNs) has received significant public attention in recent years. The benefits of WSSNs are that they are low-cost, easy to install, and provide effective data management via on-board computation. This paper reports on the deployment and evaluation of a state-of-the-art WSSN on the new Jindo Bridge, a cable-stayed bridge in South Korea with a 344-m main span and two 70-m side spans. The central components of the WSSN deployment are the Imote2 smart sensor platforms, a custom-designed multimetric sensor boards, base stations, and software provided by the Illinois Structural Health Monitoring Project (ISHMP) Services Toolsuite. In total, 70 sensor nodes and two base stations have been deployed to monitor the bridge using an autonomous SHM application with excessive wind and vibration triggering the system to initiate monitoring. Additionally, the performance of the system is evaluated in terms of hardware durability, software stability, power consumption and energy harvesting capabilities. The Jindo Bridge SHM system constitutes the largest deployment of wireless smart sensors for civil infrastructure monitoring to date. This deployment demonstrates the strong potential of WSSNs for monitoring of large scale civil infrastructure.

• Korean Journal of Remote Sensing
• /
• v.37 no.5_1
• /
• pp.1163-1175
• /
• 2021

In autonomous driving, road markings are an essential element for object tracking, path planning and they are able to provide important information for localization. This paper presents an approach to update and measure road surface markers with HD maps as well as matching using inverse perspective mapping. The IPM removes perspective effects from the vehicle's front camera image and remaps them to the 2D domain to create a bird-view region to fit with HD map regions. In addition, letters and arrows such as stop lines, crosswalks, dotted lines, and straight lines are recognized and compared to objects on the HD map to determine whether they are updated. The localization of a newly installed object can be obtained by referring to the measurement value of the surrounding object on the HD map. Therefore, we are able to obtain high accuracy update results with very low computational costs and low-cost cameras and GNSS/INS sensors alone.