• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.4
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• pp.76-89
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• 2014

In this paper, we propose a MAC(Media Access Control) protocol based on flexible RWT(RTS Waiting Time) for underwater mobile ad-hoc networks with a three-way handshaking mechanism. This protocol can solve a problem of collision between RTS(Request-To-Send) and CTS(Clear-To-Send) packets in existing MACA(Multiple Access with Collision Avoidance) protocol. This proposed MAC protocol is also an effective protocol which can apply to underwater mobile ad-hoc networks in a real field by using implementable technologies. We set flexible RTS Waiting Time called RWT, considering various characteristics of underwater environment. It is possible to support variable network size according to node mobility. Finally, we conduct a performance evaluation between proposed MAC protocol and existing MACA based MAC protocol through practical implementation and experiment. As a result, we verify the superiority of our proposed MAC protocol in terms of throughput, packet drop rate, average transmission time, energy consumption and channel utilization.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.43 no.6 s.312
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• pp.1-8
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• 2006

Many researches on path planning and obstacle avoidance for the fundamentals of mobile robot have been done recently. Informations from various sensors can be used to find obstacles and plan feasible path. In spite of many solutions of finding optimal path, each can be applied in only a constrained condition. This means that it is difficult to find university good algorithm. An optimal path with a complicated computation generates a time delay which cannot avoid moving obstacles. In this paper, we propose an algorithm of path planning and obstacle avoidance for mobile robot. We call the proposed method Random Access Sequence(RAS) method. In the proposed method, a small region is set first and numbers are assigned to its neighbors, then the path is selected using these numbers and cumulative numbers. It has an advantage of fast planning time and completeness of path if one exists. This means that new path selection may be possible within short time and that helps a robot to avoid obstacle in dynamic environments. Using the information of the start and destination position, the RAS can be performed for collision-free navigation by reforming feasible paths repeatedly in dynamic environments.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.4
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• pp.707-714
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• 2016

Active driving safety systems for vehicle, such as the front collision avoidance, lane departure warning, and lane change assistance, have been popular to be adopted to the compact car. For improving performance and competitive cost, FMCW radar has been researched to adopt a phased array or a multi-beam antenna, and to integrate the front and the side radar. In this paper we propose several efficient methods to implement the signal processing module of FMCW radar system using low cost DSP. The pulse width modulation (PWM) based analog conversion, the approximation of time-eating functions, and the adoption of vector-based computation, etc, are proposed and implemented. The implemented signal processing board shows the real-time performance of 1.4ms pulse repetition interval (PRI) with 1024pt-FFT. In real road we verify the radar performance under real-time constraints of 10Hz update time.

• Journal of the Korean Society of Industry Convergence
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• v.25 no.5
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• pp.853-859
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• 2022

In this study, we analyzed the instantaneous trajectory generation capability and target arrival rate of a mobile robot by changing the parameter of the TEB (Timed Elastic Band) Local Planner among local planners that affect the instantaneous obstacle avoidance ability of the mobile robot using ROS (Robot Operating System) simulation and real experience. As a result, we can expect a decrease in the target arrival time of the mobile robot through a decrease in the parameter values of the TEB Local Planner's min_obstacle_dist, inflation_dist, and penalty_epsilon. However, if this parameter is reduced too much, the risk of obstacle collision of the moving robot is increases, so it is important to combine the appropriate values to construct the parameter.

• Journal of Korea Society of Industrial Information Systems
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• v.24 no.5
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• pp.115-120
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• 2019

In this paper, we present the results of the performance statistical analysis of the multi-robot formation control based on receding horizon particle swarm optimization (RHPSO). The formation control problem of multi-robot system can be defined as a constrained nonlinear optimization problem when considering collision avoidance between robots. In general, the constrained nonlinear optimization problem has a problem that it takes a long time to find the optimal solution. The RHPSO algorithm was proposed to quickly find a suboptimal solution to the optimization problem of multi-robot formation control. The computational complexity of the RHPSO increases as the number of candidate solutions and generations increases. Therefore, it is important to find a suboptimal solution that can be used for real-time control with minimal candidate solutions and generations. In this paper, we compared the formation error according to the number of candidate solutions and the number of generations. Through numerical simulations under various conditions, the results are analyzed statistically and the minimum number of candidate solutions and the minimum number of generations of the RHPSO algorithm are derived within the allowable control error.

• Ocean Systems Engineering
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• v.10 no.4
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• pp.415-434
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• 2020

Detecting objects is important for the safe operation of ships, and enables collision avoidance, risk detection, and autonomous sailing. This study proposes a ship detection method from images and videos taken at sea using one of the state-of-the-art deep neural network-based object detection algorithms. A deep learning model is trained using a public maritime dataset, and results show it can detect all types of floating objects and classify them into ten specific classes that include a ship, speedboat, and buoy. The proposed deep learning model is compared to a universal trained model that detects and classifies objects into general classes, such as a person, dog, car, and boat, and results show that the proposed model outperforms the other in the detection of maritime objects. Different deep neural network structures are then compared to obtain the best detection performance. The proposed model also shows a real-time detection speed of approximately 30 frames per second. Hence, it is expected that the proposed model can be used to detect maritime objects and reduce risks while at sea.

• Spatial Information Research
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• v.15 no.4
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• pp.363-370
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• 2007

This study has been carried for the development of the basic algorithm of helicopter navigation system based on TRN (Terrain Referenced Navigation) with information input from the GPS. The helicopter determines flight path due to Origination-Destination analysis on the Cartesian coordinate system of 3-D DTM. This system shows 3-D mesh map and the O-D flight path profile for the pilot's acknowledgement of the terrain, at first. The system builds TCF (terrain clearance floor) far the buffer zone upon the surface of ground relief to avid the ground collision. If the helicopter enters to the buffer zone during navigation, the real-time warning message which commands to raise the body pops up using Matlab menu. While departing or landing, control of the height of the body is possible. At present, the information (x, y, z coordinates) from the GPS is assumed to be input into the system every 92.8 m of horizontal distance while navigating along flight path. DTM of 3" interval has been adopted from that which was provided by ChumSungDae Co., Ltd..

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.9
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• pp.888-897
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• 2015

A flight capability to take a terrain following flight near the ground is required to reduce the probability that a fighter aircraft can be detected by foe's radar fence in the battlefield. The success rate for mission flight has increased by adopting TFS (Terrain Following System) to enable the modern advanced fighter to fly safely near the ground at the low altitude. This system has applied to the state-of-the-art fighter and bomber, such as B-1, F-111, F-16 E/F and F-15, since the research begins from 1960's. In this paper, the terrain following system and GCAS (Ground Collision Avoidance System) was developed, based on a digital database with UTAS's TERPRROM (TERrain PROfile Matching) equipment. This system calculates the relative location of the aircraft in the terrain database by using the aircraft status information provided by the radar altimeter and the INS (Inertial Navigation System), based on the digital terrain database loaded previously in the DTC (Data Transfer Cartridge), and figures out terrain features around. And, the system is a manual terrain following system which makes a steering command cue refer to flight path marker, on the HUD (Head Up Display), for vertical acceleration essential for terrain following flight and enables a pilot to follow it. The cue is based on the recognized terrain features and TCH (Target Clearance Height) set by a pilot in advance. The developed terrain following system was verified in the real-time pilot evaluation in FA-50 HQS (Handling Quality Simulator) environment.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.7
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• pp.3309-3328
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• 2017

The application of Internet of Things (IoT) in the next generation cellular networks imposes a new characteristic on the data traffic, where a massive number of small packets need to be transmitted. In addition, some emerging IoT-based emergency services require a real-time data delivery within a few milliseconds, referring to as ultra-low latency transmission. However, current techniques cannot provide such a low latency in combination with a mice-flow traffic. In this paper, we propose a dynamic resource reservation schema based on an air-interface slicing scheme in the context of a massive number of sensors with emergency flows. The proposed schema can achieve an air-interface latency of a few milliseconds by means of allowing emergency flows to be transported through a dedicated radio connection with guaranteed network resources. In order to schedule the delay-sensitive flows immediately, dynamic resource updating, silence-probability based collision avoidance, and window-based re-transmission are introduced to combine with the frame-slotted Aloha protocol. To evaluate performance of the proposed schema, a probabilistic model is provided to derive the analytical results, which are compared with the numerical results from Monte-Carlo simulations.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.344-352
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• 2022

Accurate indoor localization of construction workers and mobile assets is essential in safety management. Existing positioning methods based on GPS, wireless, vision, or sensor based RTLS are erroneous or expensive in large-scale indoor environments. Tightly coupled sensor fusion mitigates these limitations. This research paper proposes a state-of-the-art positioning methodology, addressing the existing limitations, by integrating Stereo Visual Inertial Odometry (SVIO) with fiducial landmarks called AprilTags. SVIO determines the relative position of the moving assets or workers from the initial starting point. This relative position is transformed to an absolute position when AprilTag placed at various entry points is decoded. The proposed solution is tested on the NVIDIA ISAAC SIM virtual environment, where the trajectory of the indoor moving forklift is estimated. The results show accurate localization of the moving asset within any indoor or underground environment. The system can be utilized in various use cases to increase productivity and improve safety at construction sites, contributing towards 1) indoor monitoring of man machinery coactivity for collision avoidance and 2) precise real-time knowledge of who is doing what and where.