• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.1
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• pp.70-75
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• 2003

There come various types of robot with researches for mobile robot. This paper introduces the multi-joint snake robot having 16 degree of freedom and composing of eight-axis. The biological snake robot uses the forward movement friction and the proposed artificial snake robot uses the un-powered wheel instead of the body of snake. To determine the enable joint angle of each joint, the controller inputs are considered such as color and distance using PC Camera and ultra-sonic sensor module, respectively. The movement method of snake robot is sequential moving from head to tail through body. The target for movement direction is decided by a certain article be displayed in the PC Camera. In moving toward that target, if there is any obstacle then the snake robot can avoid by itself. In this paper, we show the method of snake robot for tracing the target with experiment.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.11
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• pp.904-911
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• 2016

This paper presents a novel driving system by the humanoid robot to drive a vehicle in disaster response situations. To enhance robot's capability for substituting human activities in responding to natural and man-made disaster, the one of prerequisite skills for the rescue robot is the mounted mobility to maneuver a vehicle safely in disaster site. Therefore, our driving system for the humanoid is developed in order to steer a vehicle through unknown obstacles even under poor communication conditions such as time-delay and black-out. Especially, the proposed system includes a tele-manipulation interface and stable navigation strategies. First, we propose a new type of path estimation method to overcome limited communication. Second, we establish navigation strategies when the operator cannot recognize obstacles based on Dynamic Window Approach. The effectiveness of the proposed developments is verified through simulation and experiments, which demonstrate suitable system for driving a vehicle in disaster response.

• 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.

• ETRI Journal
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• v.45 no.5
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• pp.887-898
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• 2023

Aerial base stations (ABSs) seem promising to enhance the coverage and capacity of fifth-generation and upcoming networks. With the flexible mobility of ABSs, they can be positioned in air to maximize the number of users served with a guaranteed quality of service (QoS). However, ABSs may be overloaded or underutilized given inefficient placement, and user association has not been well addressed. Hence, we propose a three-dimensional ABS placement scheme with a delay-QoS-driven user association to balance loading among ABSs. First, a load balancing utility function is designed based on proportional fairness. Then, an optimization problem for joint ABS placement and user association is formulated to maximize the utility function subject to statistical delay QoS requirements and ABS collision avoidance constraints. To solve this problem, we introduce an efficient modified gray wolf optimizer for ABS placement with a greedy user association strategy. Simulation results demonstrate that the proposed scheme outperforms baselines in terms of load balancing and delay QoS provisioning.

• JSTS:Journal of Semiconductor Technology and Science
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• v.16 no.5
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• pp.595-604
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• 2016

Utilizing a standard 130-nm CMOS process, a RF frontend is designed at 24 GHz for automotive collision avoidance radar application. Single IF direct conversion receiver (DCR) architecture is adopted to achieve high integration level and to alleviate the DCR problem. The proposed frontend is composed of a two-stage LNA and downconversion mixers. To save power consumption, and to enhance gain and linearity, stacked NMOS-PMOS $g_m$-boosting technique is employed in the design of LNA as the first stage. The switch transistors in the mixing stage are biased in subthreshold region to achieve low power consumption. The single balanced mixer is designed in PMOS transistors and is also realized based on the well-known folded architecture to increase voltage headroom. This frontend circuit features enhancement in gain, linearity, and power dissipation. The proposed circuit showed a maximum conversion gain of 19.6 dB and noise figure of 3 dB at the operation frequency. It also showed input and output return losses of less than -10 dB within bandwidth. Furthermore, the port-to-port isolation illustrated excellent characteristic between two ports. This frontend showed the third-order input intercept point (IIP3) of 3 dBm for the whole circuit with power dissipation of 6.5 mW from a 1.5 V supply.

• Journal of the Korea Institute of Military Science and Technology
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• v.18 no.6
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• pp.711-720
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• 2015

Recently many studies of Radar systems mounted on ground vehicles for autonomous driving, SLAM (Simultaneous localization and mapping) and collision avoidance have been reported. Since several pixels per an object may be generated in a close-range radar application, a width of an object can be estimated automatically by various signal processing techniques. In this paper, we tried to attempt to develop an algorithm to estimate obstacle width using Radar images. The proposed method consists of 5 steps - 1) background clutter reduction, 2) local peak pixel detection, 3) region growing, 4) contour extraction and 5)width calculation. For the performance validation of our method, we performed the test width estimation using a real data of two cars acquired by commercial radar system - I200 manufactured by Navtech. As a result, we verified that the proposed method can estimate the widths of targets.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.11
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• pp.4436-4452
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• 2015

The IEEE 802.15.6 standard is introduced to satisfy all the requirements for monitoring systems operating in, on, or around the human body. In this paper, analytical models are developed for evaluating the performance of the IEEE 802.15.6 CSMA/CA-based medium access control protocol for wireless body area networks (WBAN) under unsaturation condition. We employ a three-dimensional Markov chain to model the backoff procedure, and an M/G/1/K queuing system to describe the packet queues in the buffer. The throughput and delay performances of WBAN operating in the beacon mode are analyzed in heterogeneous network comprised of different user priorities. Simulation results are included to demonstrate the accuracy of the proposed analytical model.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.2
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• pp.100-106
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• 2013

This paper presents design and control of an 'Omni-directional Cleaning Robot (OdCR)' which employs omni-wheels at three edges of its triangular configuration. Those omni-wheels enable the OdCR to move in any directions so that lateral movement is possible. For OdCR to be localized, a StarGazer sensor is used to provide accurate position and heading angle based on landmarks on the ceiling. In addition to that, ultrasonic sensors are installed to detect obstacles around OdCR's way. Experimental studies are conducted to test the functionality of the system.

• 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.

• Journal of Ocean Engineering and Technology
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• v.36 no.1
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• pp.61-81
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• 2022

The available underwater acoustic spectrum is limited. Therefore, it is imperative to avoid frequency interference from overlapping frequencies of underwater acoustic equipment (UAE) for the co-existence of the UAE. Cognitive technology that senses idle spectrum and actively avoids frequency interference is an efficient method to facilitate the collision-free operation of multiple UAE with overlapping frequencies. Cognitive technology is adopted to identify the frequency usage of UAE to apply cognitive technology. To this end, we investigated two principle underwater acoustic sources: UAE and marine animals. The UAE is classified into five types: underwater acoustic modem, acoustic positioning system, multi-beam echo-sounder, side-scan sonar, and sub-bottom profiler. We analyzed the parameters of the frequency band, directivity, range, and depth, which play a critical role in the design of underwater acoustic cognitive technology. Moreover, the frequency band of several marine species was also examined. The mid-frequency band from 10 - 40 kHz was found to be the busiest. Lastly, this study provides useful insights into the design of underwater acoustic cognitive technologies, where it is essential to avoid interference among the UAE in this mid-frequency band.