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Prof. Dr. Hyun Myung
KAIST

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Research Keywords & Expertise

0 SLAM
0 Drones
0 Autonomous Navigation SLAM
0 Artificial Intelligence (AI)
0 self driving

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Journal article
Published: 30 August 2021 in IEEE Robotics and Automation Letters
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Unmanned Aerial Vehicles (UAVs) have continually proven their effectiveness in inspecting massive structures that are difficult for humans to reach. However, maintenance, such as cleaning, has yet to be conquered by UAVs. To mitigate this issue, this paper proposes a novel design for a coaxial hexarotor (Y6) with a tilting mechanism that can morph midair while in a hover, changing the flight stage from a horizontal to a vertical orientation, and vice versa, thus allowing wall-perching and wall-climbing maneuvers. Tilting rotors are located at a certain distance from the tilting axle, called a rotor offset. This configuration reduces the required distance between the wall and the platform, which benefits stability and broadens the chance to improve power efficiency. However, the servo motor slows down, and the tilting angle is one-way constrained owing to the rotor offset. These conditions can cause a critical issue with the conventional control method. To tackle the problem, a novel control method called quasi-decoupling control is proposed. Our proposed method attains promising performance, overcoming the limitations of a servo motors slow dynamics and angular constraint.

ACS Style

Hyun Myung; Hyungyu Lee; Byeongho Yu; Christian Tirtawardhana; Chanyoung Kim; Myeongwoo Jeong; Sumin Hu. CAROS-Q: Climbing Aerial RObot System Adopting Rotor Offset with a Quasi-Decoupling Controller. IEEE Robotics and Automation Letters 2021, PP, 1 -1.

AMA Style

Hyun Myung, Hyungyu Lee, Byeongho Yu, Christian Tirtawardhana, Chanyoung Kim, Myeongwoo Jeong, Sumin Hu. CAROS-Q: Climbing Aerial RObot System Adopting Rotor Offset with a Quasi-Decoupling Controller. IEEE Robotics and Automation Letters. 2021; PP (99):1-1.

Chicago/Turabian Style

Hyun Myung; Hyungyu Lee; Byeongho Yu; Christian Tirtawardhana; Chanyoung Kim; Myeongwoo Jeong; Sumin Hu. 2021. "CAROS-Q: Climbing Aerial RObot System Adopting Rotor Offset with a Quasi-Decoupling Controller." IEEE Robotics and Automation Letters PP, no. 99: 1-1.

Journal article
Published: 28 June 2021 in IEEE Robotics and Automation Letters
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Ground segmentation is crucial for terrestrial mobile platforms to perform navigation or neighboring object recognition. Unfortunately, the ground is not flat, as it features steep slopes; bumpy roads; or objects, such as curbs, flower beds, and so forth. To tackle the problem, this paper presents a novel ground segmentation method called \textit{Patchwork}, which is robust for addressing the under-segmentation problem and operates at more than 40 Hz. In this paper, a point cloud is encoded into a Concentric Zone Model--based representation to assign an appropriate density of cloud points among bins in a way that is not computationally complex. This is followed by Region-wise Ground Plane Fitting, which is performed to estimate the partial ground for each bin. Finally, Ground Likelihood Estimation is introduced to dramatically reduce false positives. As experimentally verified on SemanticKITTI and rough terrain datasets, our proposed method yields promising performance compared with the state-of-the-art methods, showing faster speed compared with existing plane fitting--based methods.

ACS Style

Hyungtae Lim; Minho Oh; Hyun Myung. Patchwork: Concentric Zone-based Region-wise Ground Segmentation with Ground Likelihood Estimation Using a 3D LiDAR Sensor. IEEE Robotics and Automation Letters 2021, PP, 1 -1.

AMA Style

Hyungtae Lim, Minho Oh, Hyun Myung. Patchwork: Concentric Zone-based Region-wise Ground Segmentation with Ground Likelihood Estimation Using a 3D LiDAR Sensor. IEEE Robotics and Automation Letters. 2021; PP (99):1-1.

Chicago/Turabian Style

Hyungtae Lim; Minho Oh; Hyun Myung. 2021. "Patchwork: Concentric Zone-based Region-wise Ground Segmentation with Ground Likelihood Estimation Using a 3D LiDAR Sensor." IEEE Robotics and Automation Letters PP, no. 99: 1-1.

Journal article
Published: 01 June 2021 in Journal of Korea Robotics Society
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ACS Style

Euigon Jung; Wonho Song; Hyun Myung. High-Definition Map-based Local Path Planning for Dynamic and Static Obstacle Avoidance. Journal of Korea Robotics Society 2021, 16, 112 -121.

AMA Style

Euigon Jung, Wonho Song, Hyun Myung. High-Definition Map-based Local Path Planning for Dynamic and Static Obstacle Avoidance. Journal of Korea Robotics Society. 2021; 16 (2):112-121.

Chicago/Turabian Style

Euigon Jung; Wonho Song; Hyun Myung. 2021. "High-Definition Map-based Local Path Planning for Dynamic and Static Obstacle Avoidance." Journal of Korea Robotics Society 16, no. 2: 112-121.

Journal article
Published: 26 April 2021 in IEEE Robotics and Automation Letters
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This letter presents benchmark tests of various visual(-inertial) odometry algorithms on NVIDIA Jetson platforms. The compared algorithms include mono and stereo, covering Visual Odometry (VO) and Visual-Inertial Odometry (VIO): VINS-Mono, VINS-Fusion, Kimera, ALVIO, Stereo-MSCKF, ORB-SLAM2 stereo, and ROVIO. As these methods are mainly used for unmanned aerial vehicles (UAVs), they must perform well in situations where the size of the processing board and weight is limited. Jetson boards released by NVIDIA satisfy these constraints as they have a sufficiently powerful central processing unit (CPU) and graphics processing unit (GPU) for image processing. However, in existing studies, the performance of Jetson boards as a processing platform for executing VO/VIO has not been compared extensively in terms of the usage of computing resources and accuracy. Therefore, this study compares representative VO/VIO algorithms on several NVIDIA Jetson platforms, namely NVIDIA Jetson TX2, Xavier NX, and AGX Xavier, and introduces a novel dataset ‘KAIST VIO dataset’ for UAVs. Including pure rotations, the dataset has several geometric trajectories that are harsh to visual(-inertial) state estimation. The evaluation is performed in terms of the accuracy of estimated odometry, CPU usage, and memory usage on various Jetson boards, algorithms, and trajectories. We present the results of the comprehensive benchmark test and release the dataset for the computer vision and robotics applications.

ACS Style

Jinwoo Jeon; Sungwook Jung; Eungchang Lee; Duckyu Choi; Hyun Myung. Run Your Visual-Inertial Odometry on NVIDIA Jetson: Benchmark Tests on a Micro Aerial Vehicle. IEEE Robotics and Automation Letters 2021, 6, 1 -1.

AMA Style

Jinwoo Jeon, Sungwook Jung, Eungchang Lee, Duckyu Choi, Hyun Myung. Run Your Visual-Inertial Odometry on NVIDIA Jetson: Benchmark Tests on a Micro Aerial Vehicle. IEEE Robotics and Automation Letters. 2021; 6 (3):1-1.

Chicago/Turabian Style

Jinwoo Jeon; Sungwook Jung; Eungchang Lee; Duckyu Choi; Hyun Myung. 2021. "Run Your Visual-Inertial Odometry on NVIDIA Jetson: Benchmark Tests on a Micro Aerial Vehicle." IEEE Robotics and Automation Letters 6, no. 3: 1-1.

Editorial
Published: 23 April 2021 in Sensors
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For several decades, various sensors and sensing systems have been developed for smart cities and civil infrastructure systems

ACS Style

Hyun Myung; Yang Wang. Robotic Sensing and Systems for Smart Cities. Sensors 2021, 21, 2963 .

AMA Style

Hyun Myung, Yang Wang. Robotic Sensing and Systems for Smart Cities. Sensors. 2021; 21 (9):2963.

Chicago/Turabian Style

Hyun Myung; Yang Wang. 2021. "Robotic Sensing and Systems for Smart Cities." Sensors 21, no. 9: 2963.

Journal article
Published: 23 February 2021 in IEEE Robotics and Automation Letters
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Scan data of urban environments often include representations of dynamic objects, such as vehicles, pedestrians, and so forth. However, when it comes to constructing a 3D point cloud map with sequential accumulations of the scan data, the dynamic objects often leave unwanted traces in the map. These traces of dynamic objects act as obstacles and thus impede mobile vehicles from achieving good localization and navigation performances. To tackle the problem, this letter presents a novel static map building method called ERASOR , Egocentric RAtio of pSeudo Occupancy-based dynamic object Removal, which is fast and robust to motion ambiguity. Our approach directs its attention to the nature of most dynamic objects in urban environments being inevitably in contact with the ground. Accordingly, we propose the novel concept called pseudo occupancy to express the occupancy of unit space and then discriminate spaces of varying occupancy. Finally, Region-wise Ground Plane Fitting (R-GPF) is adopted to distinguish static points from dynamic points within the candidate bins that potentially contain dynamic points. As experimentally verified on SemanticKITTI, our proposed method yields promising performance against state-of-the-art methods overcoming the limitations of existing ray tracing-based and visibility-based methods.

ACS Style

Hyungtae Lim; Sungwon Hwang; Hyun Myung. ERASOR: Egocentric Ratio of Pseudo Occupancy-Based Dynamic Object Removal for Static 3D Point Cloud Map Building. IEEE Robotics and Automation Letters 2021, 6, 2272 -2279.

AMA Style

Hyungtae Lim, Sungwon Hwang, Hyun Myung. ERASOR: Egocentric Ratio of Pseudo Occupancy-Based Dynamic Object Removal for Static 3D Point Cloud Map Building. IEEE Robotics and Automation Letters. 2021; 6 (2):2272-2279.

Chicago/Turabian Style

Hyungtae Lim; Sungwon Hwang; Hyun Myung. 2021. "ERASOR: Egocentric Ratio of Pseudo Occupancy-Based Dynamic Object Removal for Static 3D Point Cloud Map Building." IEEE Robotics and Automation Letters 6, no. 2: 2272-2279.

Journal article
Published: 16 September 2020 in Remote Sensing
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With the increasing demand for autonomous systems in the field of inspection, the use of unmanned aerial vehicles (UAVs) to replace human labor is becoming more frequent. However, the Global Positioning System (GPS) signal is usually denied in environments near or under bridges, which makes the manual operation of a UAV difficult and unreliable in these areas. This paper addresses a novel hierarchical graph-based simultaneous localization and mapping (SLAM) method for fully autonomous bridge inspection using an aerial vehicle, as well as a technical method for UAV control for actually conducting bridge inspections. Due to the harsh environment involved and the corresponding limitations on GPS usage, a graph-based SLAM approach using a tilted 3D LiDAR (Light Detection and Ranging) and a monocular camera to localize the UAV and map the target bridge is proposed. Each visual-inertial state estimate and the corresponding LiDAR sweep are combined into a single subnode. These subnodes make up a “supernode” that consists of state estimations and accumulated scan data for robust and stable node generation in graph SLAM. The constraints are generated from LiDAR data using the normal distribution transform (NDT) and generalized iterative closest point (G-ICP) matching. The feasibility of the proposed method was verified on two different types of bridges: on the ground and offshore.

ACS Style

Sungwook Jung; Duckyu Choi; Seungwon Song; Hyun Myung. Bridge Inspection Using Unmanned Aerial Vehicle Based on HG-SLAM: Hierarchical Graph-based SLAM. Remote Sensing 2020, 12, 3022 .

AMA Style

Sungwook Jung, Duckyu Choi, Seungwon Song, Hyun Myung. Bridge Inspection Using Unmanned Aerial Vehicle Based on HG-SLAM: Hierarchical Graph-based SLAM. Remote Sensing. 2020; 12 (18):3022.

Chicago/Turabian Style

Sungwook Jung; Duckyu Choi; Seungwon Song; Hyun Myung. 2020. "Bridge Inspection Using Unmanned Aerial Vehicle Based on HG-SLAM: Hierarchical Graph-based SLAM." Remote Sensing 12, no. 18: 3022.

Journal article
Published: 10 September 2020 in IEEE Transactions on Instrumentation and Measurement
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This paper proposes a novel adaptive Kalman filter (AKF) to estimate the unknown probability of measurement loss using the interacting multiple-model (IMM) filtering framework, yielding the IMM-AKF algorithm. In the proposed IMM-AKF algorithm, the state, Bernoulli random variable, and measurement loss probability are jointly inferred based on the variational Bayesian (VB) approach. In particular, a new likelihood definition is derived for the mode probability update process of the IMMAKF algorithm. Experiments demonstrate the superiority of the proposed IMM-AKF algorithm over existing filtering algorithms by adaptively estimating the unknown time-varying measurement loss probability.

ACS Style

Wonkeun Youn; Nak Yong Ko; Stephen Andrew Gadsden; Hyun Myung. A Novel Multiple-Model Adaptive Kalman Filter for an Unknown Measurement Loss Probability. IEEE Transactions on Instrumentation and Measurement 2020, 70, 1 -11.

AMA Style

Wonkeun Youn, Nak Yong Ko, Stephen Andrew Gadsden, Hyun Myung. A Novel Multiple-Model Adaptive Kalman Filter for an Unknown Measurement Loss Probability. IEEE Transactions on Instrumentation and Measurement. 2020; 70 (99):1-11.

Chicago/Turabian Style

Wonkeun Youn; Nak Yong Ko; Stephen Andrew Gadsden; Hyun Myung. 2020. "A Novel Multiple-Model Adaptive Kalman Filter for an Unknown Measurement Loss Probability." IEEE Transactions on Instrumentation and Measurement 70, no. 99: 1-11.

Journal article
Published: 13 August 2020 in IEEE/ASME Transactions on Mechatronics
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ACS Style

Wonkeun Youn; Yulong Huang; Hyun Myung. Corrections to “Outlier-Robust Student's-t-Based IMM-VB Localization for Manned Aircraft Using TDOA Measurements” [Jun 20 1646-1658]. IEEE/ASME Transactions on Mechatronics 2020, 25, 2139 -2139.

AMA Style

Wonkeun Youn, Yulong Huang, Hyun Myung. Corrections to “Outlier-Robust Student's-t-Based IMM-VB Localization for Manned Aircraft Using TDOA Measurements” [Jun 20 1646-1658]. IEEE/ASME Transactions on Mechatronics. 2020; 25 (4):2139-2139.

Chicago/Turabian Style

Wonkeun Youn; Yulong Huang; Hyun Myung. 2020. "Corrections to “Outlier-Robust Student's-t-Based IMM-VB Localization for Manned Aircraft Using TDOA Measurements” [Jun 20 1646-1658]." IEEE/ASME Transactions on Mechatronics 25, no. 4: 2139-2139.

Article
Published: 05 August 2020 in International Journal of Control, Automation and Systems
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This paper proposes a novel complete navigation system for autonomous flight of small unmanned aerial vehicles (UAVs) in GPS-denied environments. The hardware platform used to test the proposed algorithm is a small, custom-built UAV platform equipped with an onboard computer, RGB-D camera, 2D light detection and ranging (LiDAR), and altimeter. The error-state Kalman filter (ESKF) based on the dynamic model for low-cost IMU-driven systems is proposed, and visual odometry from the RGB-D camera and height measurement from the altimeter are fed into the measurement update process of the ESKF. The pose output of the ESKF is then integrated into the open-source simultaneous location and mapping (SLAM) algorithm for pose-graph optimization and loop closing. In addition, the computationally efficient collision-free path planning algorithm is proposed and verified through simulations. The software modules run onboard in real time with limited onboard computational capability. The indoor flight experiment demonstrates that the proposed system for small UAVs with low-cost devices can navigate without collision in fully autonomous missions while establishing accurate surrounding maps.

ACS Style

Wonkeun Youn; Hayoon Ko; Hyungsik Choi; Inho Choi; Joong-Hwan Baek; Hyun Myung. Collision-free Autonomous Navigation of A Small UAV Using Low-cost Sensors in GPS-denied Environments. International Journal of Control, Automation and Systems 2020, 19, 953 -968.

AMA Style

Wonkeun Youn, Hayoon Ko, Hyungsik Choi, Inho Choi, Joong-Hwan Baek, Hyun Myung. Collision-free Autonomous Navigation of A Small UAV Using Low-cost Sensors in GPS-denied Environments. International Journal of Control, Automation and Systems. 2020; 19 (2):953-968.

Chicago/Turabian Style

Wonkeun Youn; Hayoon Ko; Hyungsik Choi; Inho Choi; Joong-Hwan Baek; Hyun Myung. 2020. "Collision-free Autonomous Navigation of A Small UAV Using Low-cost Sensors in GPS-denied Environments." International Journal of Control, Automation and Systems 19, no. 2: 953-968.

Journal article
Published: 19 March 2020 in IEEE/ASME Transactions on Mechatronics
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This paper proposes a novel outlier-robust localization algorithm that is based on time difference of arrival (TDOA) measurements at an airport for multilateration (MLAT) surveillance. An outlier-robust filtering scheme is derived based on Student's-t-distribution, where the state, a scale matrix, and a degree of freedom (DOF) parameter are estimated simultaneously using variational Bayesian (VB) inference. An interacting multiple model (IMM) filter with different system models is implemented to handle the multimodal dynamics of the aircraft, yielding the IMM-VB algorithm. Specifically, the likelihood function is newly derived using VB inference for the combination procedure in the proposed IMM-VB algorithm. The experimental results obtained from a flight test using a commercial aircraft at an airport demonstrate that the proposed IMM-VB algorithm has better localization accuracy and robustness to outlier measurements than the existing state-of-the-art approaches.

ACS Style

Wonkeun Youn; Yulong Huang; Hyun Myung. Outlier-Robust Student's-$t$-Based IMM-VB Localization for Manned Aircraft Using TDOA Measurements. IEEE/ASME Transactions on Mechatronics 2020, 25, 1646 -1658.

AMA Style

Wonkeun Youn, Yulong Huang, Hyun Myung. Outlier-Robust Student's-$t$-Based IMM-VB Localization for Manned Aircraft Using TDOA Measurements. IEEE/ASME Transactions on Mechatronics. 2020; 25 (3):1646-1658.

Chicago/Turabian Style

Wonkeun Youn; Yulong Huang; Hyun Myung. 2020. "Outlier-Robust Student's-$t$-Based IMM-VB Localization for Manned Aircraft Using TDOA Measurements." IEEE/ASME Transactions on Mechatronics 25, no. 3: 1646-1658.

Journal article
Published: 13 December 2019 in IEEE Access
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Among various sensors used to recognize obstacles in marine environments, vision sensors are the most basic. Vision sensors are significantly affected by the surrounding environment and cannot recognize distant objects. However, despite these drawbacks, they can detect objects that radars cannot detect in nearby regions. They can also recognize small obstacles such as boats that are not equipped with an automatic identification system (AIS) or buoys. Thus, vision sensors and radar can be used in a complementary manner. This paper proposes a vision sensor-based model, called Skip-ENet (or SENet), for recognizing obstacles in real time. Compared with ENet, the amount of computation is not significantly higher. Further, SENet can segment complex marine obstacles effectively by increasing the values for the class accuracy and mean Intersection of Union (mIoU). Moreover, this model enables even low-cost embedded systems to compute 10 or more frames per second (fps). The superiority of the proposed model was verified by comparing its performance with that of the conventional segmentation models MobileNet, ENet, and DeeplabV3+.

ACS Style

Hanguen Kim; Jungmo Koo; Donghoon Kim; Byeolteo Park; Yonggil Jo; Hyun Myung; Donghwa Lee. Vision-Based Real-Time Obstacle Segmentation Algorithm for Autonomous Surface Vehicle. IEEE Access 2019, 7, 179420 -179428.

AMA Style

Hanguen Kim, Jungmo Koo, Donghoon Kim, Byeolteo Park, Yonggil Jo, Hyun Myung, Donghwa Lee. Vision-Based Real-Time Obstacle Segmentation Algorithm for Autonomous Surface Vehicle. IEEE Access. 2019; 7 (99):179420-179428.

Chicago/Turabian Style

Hanguen Kim; Jungmo Koo; Donghoon Kim; Byeolteo Park; Yonggil Jo; Hyun Myung; Donghwa Lee. 2019. "Vision-Based Real-Time Obstacle Segmentation Algorithm for Autonomous Surface Vehicle." IEEE Access 7, no. 99: 179420-179428.

Journal article
Published: 25 November 2019 in IEEE Transactions on Instrumentation and Measurement
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This paper proposes a new skewed outlier-robust localization algorithm that is based on time difference of arrival (TDOA) measurements at an airport. A new outlier-robust filtering framework is derived based on the skew Gaussian-gamma mixture (SGGM) distribution, where the state, a mixing parameter, a shape parameter, a scale matrix, and the degrees of freedom (DOF) are inferred simultaneously using variational Bayesian (VB) approach. An interacting multiple-model (IMM) filter with different kinematic system models is implemented to handle the multimodal dynamics of the vehicle, yielding the IMM-SGGM algorithm. In particular, a new measurement likelihood based on the SGGM distribution is derived utilizing VB inference for the combination procedure in the proposed IMM-SGGM algorithm. Car-mounted experiments using TDOA measurements at an airport were conducted to verify the effectiveness of the proposed algorithm. The performance of the proposed IMM-SGGM algorithm is evaluated through comparisons with state-of-the-art approaches. The experimental results demonstrate that the proposed IMM-SGGM algorithm has better localization accuracy and robustness to skewed outlier measurements than the state-of-the-art approaches.

ACS Style

Wonkeun Youn; Yulong Huang; Hyun Myung. Robust Localization Using IMM Filter Based on Skew Gaussian-Gamma Mixture Distribution in Mixed LOS/NLOS Condition. IEEE Transactions on Instrumentation and Measurement 2019, 69, 5166 -5182.

AMA Style

Wonkeun Youn, Yulong Huang, Hyun Myung. Robust Localization Using IMM Filter Based on Skew Gaussian-Gamma Mixture Distribution in Mixed LOS/NLOS Condition. IEEE Transactions on Instrumentation and Measurement. 2019; 69 (7):5166-5182.

Chicago/Turabian Style

Wonkeun Youn; Yulong Huang; Hyun Myung. 2019. "Robust Localization Using IMM Filter Based on Skew Gaussian-Gamma Mixture Distribution in Mixed LOS/NLOS Condition." IEEE Transactions on Instrumentation and Measurement 69, no. 7: 5166-5182.

Journal article
Published: 15 October 2019 in IEEE Sensors Journal
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ACS Style

Wonkeun Youn; Matthew B. Rhudy; Am Cho; Hyun Myung. Fuzzy Adaptive Attitude Estimation for a Fixed-Wing UAV With a Virtual SSA Sensor During a GPS Outage. IEEE Sensors Journal 2019, 20, 1456 -1472.

AMA Style

Wonkeun Youn, Matthew B. Rhudy, Am Cho, Hyun Myung. Fuzzy Adaptive Attitude Estimation for a Fixed-Wing UAV With a Virtual SSA Sensor During a GPS Outage. IEEE Sensors Journal. 2019; 20 (3):1456-1472.

Chicago/Turabian Style

Wonkeun Youn; Matthew B. Rhudy; Am Cho; Hyun Myung. 2019. "Fuzzy Adaptive Attitude Estimation for a Fixed-Wing UAV With a Virtual SSA Sensor During a GPS Outage." IEEE Sensors Journal 20, no. 3: 1456-1472.

Journal article
Published: 22 June 2019 in ETRI Journal
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ACS Style

Yu-Cheol Lee; Hyun Myung. Hierarchical sampling optimization of particle filter for global robot localization in pervasive network environment. ETRI Journal 2019, 41, 782 -796.

AMA Style

Yu-Cheol Lee, Hyun Myung. Hierarchical sampling optimization of particle filter for global robot localization in pervasive network environment. ETRI Journal. 2019; 41 (6):782-796.

Chicago/Turabian Style

Yu-Cheol Lee; Hyun Myung. 2019. "Hierarchical sampling optimization of particle filter for global robot localization in pervasive network environment." ETRI Journal 41, no. 6: 782-796.

Journal article
Published: 21 June 2019 in Sensors
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Mosquito control is important as mosquitoes are extremely harmful pests that spread various infectious diseases. In this research, we present the preliminary results of an automated system that detects the presence of mosquitoes via image processing using multiple deep learning networks. The Fully Convolutional Network (FCN) and neural network-based regression demonstrated an accuracy of 84%. Meanwhile, the single image classifier demonstrated an accuracy of only 52%. The overall processing time also decreased from 4.64 to 2.47 s compared to the conventional classifying network. After detection, a larvicide made from toxic protein crystals of the Bacillus thuringiensis serotype israelensis bacteria was injected into static water to stop the proliferation of mosquitoes. This system demonstrates a higher efficiency than hunting adult mosquitos while avoiding damage to other insects.

ACS Style

Kyukwang Kim; Jieum Hyun; Hyeongkeun Kim; Hwijoon Lim; Hyun Myung. A Deep Learning-Based Automatic Mosquito Sensing and Control System for Urban Mosquito Habitats. Sensors 2019, 19, 2785 .

AMA Style

Kyukwang Kim, Jieum Hyun, Hyeongkeun Kim, Hwijoon Lim, Hyun Myung. A Deep Learning-Based Automatic Mosquito Sensing and Control System for Urban Mosquito Habitats. Sensors. 2019; 19 (12):2785.

Chicago/Turabian Style

Kyukwang Kim; Jieum Hyun; Hyeongkeun Kim; Hwijoon Lim; Hyun Myung. 2019. "A Deep Learning-Based Automatic Mosquito Sensing and Control System for Urban Mosquito Habitats." Sensors 19, no. 12: 2785.

Conference paper
Published: 16 June 2019 in Proceedings of the 2nd Annual International Conference on Material, Machines and Methods for Sustainable Development (MMMS2020)
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Over the last few years, drilling system has been extensively used for a miscellaneous number of applications. However, in certain applications, e.g., shallow drilling and excavation on a difficult or rugged terrain, excavation using conventional drilling methods are not applicable. Considering the aggravating obstacles of drill bit application, in this study, digging attitude of burrowing animals (rabbits and moles) is studied. The soil penetrating force developed by burrowing animals, nevertheless, is indeed inadequate for harder and deeper excavation. Therefore, to overcome the aforementioned issues, this paper proposes a hybrid digging mechanism by combining the advantage of employing a drill bit and forelimbs mechanism adapted from burrowing animals. Emulating the role of their teeth, triangle-shaped drill bit, i.e., step drill bit, is exploited and a linkage mechanism is utilized to represent their digging motion using limbs. Dynamic simulation is performed to evaluate the digging performance of this robot.

ACS Style

Christian Tirtawardhana; Byeongho Yu; WanCheol Myeong; Hyun Myung. Development of Integrated Digging Robot Using Drill Bit-Limbs Hybrid Mechanism That Mimics Burrowing Animals Behavior. Proceedings of the 2nd Annual International Conference on Material, Machines and Methods for Sustainable Development (MMMS2020) 2019, 323 -332.

AMA Style

Christian Tirtawardhana, Byeongho Yu, WanCheol Myeong, Hyun Myung. Development of Integrated Digging Robot Using Drill Bit-Limbs Hybrid Mechanism That Mimics Burrowing Animals Behavior. Proceedings of the 2nd Annual International Conference on Material, Machines and Methods for Sustainable Development (MMMS2020). 2019; ():323-332.

Chicago/Turabian Style

Christian Tirtawardhana; Byeongho Yu; WanCheol Myeong; Hyun Myung. 2019. "Development of Integrated Digging Robot Using Drill Bit-Limbs Hybrid Mechanism That Mimics Burrowing Animals Behavior." Proceedings of the 2nd Annual International Conference on Material, Machines and Methods for Sustainable Development (MMMS2020) , no. : 323-332.

Conference paper
Published: 16 June 2019 in Proceedings of the 2nd Annual International Conference on Material, Machines and Methods for Sustainable Development (MMMS2020)
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Drilling technology has been used in various fields such as civil engineering and resource exploration. Recently, technology development aiming at space exploration and directional drilling skills has gained international attention and is being studied. Purpose of this research is developing a small embedded directional excavation robot which is not restricted in topography and can solve environmental problems. For this purpose, biomimetic mechanism of the robot’s forelimbs is designed that imitates the mole, then the excavation force was analyzed. Consequentially, the biomimeticity of the design was verified.

ACS Style

Junseok Lee; Jongheon Kim; Hyun Myung. Design of Forelimbs and Digging Mechanism of Biomimetic Mole Robot for Directional Drilling. Proceedings of the 2nd Annual International Conference on Material, Machines and Methods for Sustainable Development (MMMS2020) 2019, 341 -351.

AMA Style

Junseok Lee, Jongheon Kim, Hyun Myung. Design of Forelimbs and Digging Mechanism of Biomimetic Mole Robot for Directional Drilling. Proceedings of the 2nd Annual International Conference on Material, Machines and Methods for Sustainable Development (MMMS2020). 2019; ():341-351.

Chicago/Turabian Style

Junseok Lee; Jongheon Kim; Hyun Myung. 2019. "Design of Forelimbs and Digging Mechanism of Biomimetic Mole Robot for Directional Drilling." Proceedings of the 2nd Annual International Conference on Material, Machines and Methods for Sustainable Development (MMMS2020) , no. : 341-351.

Conference paper
Published: 16 June 2019 in Proceedings of the 2nd Annual International Conference on Material, Machines and Methods for Sustainable Development (MMMS2020)
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Recently, Unmanned Aerial Vehicles (UAVs) are widely used for various purposes such as aerial reconnaissance and delivery in urban areas. However, in some urban areas there are geo-fences where aerial vehicles cannot pass through. So, the importance of a path planning including obstacle avoidance has increased. In addition to the actual observable obstacles, it is also necessary to plan the route considering special areas or boundaries such as geo-fence. In this paper, we propose an algorithm to avoid dynamically changing geo-fence. To generate an efficient path which does not pass through the geo-fence, we add a time parameter. This proposed path planning algorithm considers not only obstacles on the map at present. The goal is to create an efficient path that also takes into account the geo-fence information dynamically generated over time, along with the speed of the UAV and the time it takes to pass through a specific location. Simulations are carried out to verify the performance of the proposed path planning algorithm.

ACS Style

Jinkwang Kim; Junho Choi; Sungwook Jung; Hyun Myung. Path Planning for an Unmanned Aerial Vehicle Considering Dynamic Geo-Fence in Urban Environment. Proceedings of the 2nd Annual International Conference on Material, Machines and Methods for Sustainable Development (MMMS2020) 2019, 333 -339.

AMA Style

Jinkwang Kim, Junho Choi, Sungwook Jung, Hyun Myung. Path Planning for an Unmanned Aerial Vehicle Considering Dynamic Geo-Fence in Urban Environment. Proceedings of the 2nd Annual International Conference on Material, Machines and Methods for Sustainable Development (MMMS2020). 2019; ():333-339.

Chicago/Turabian Style

Jinkwang Kim; Junho Choi; Sungwook Jung; Hyun Myung. 2019. "Path Planning for an Unmanned Aerial Vehicle Considering Dynamic Geo-Fence in Urban Environment." Proceedings of the 2nd Annual International Conference on Material, Machines and Methods for Sustainable Development (MMMS2020) , no. : 333-339.

Journal article
Published: 07 June 2019 in IEEE Access
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In this paper, we propose a robust point cloud registration method for ground vehicles. Given the vast developments in the field of autonomous vehicles, the use of point cloud data has increased. The simultaneous localization and mapping (SLAM) algorithm is typically used to generate sophisticated point cloud maps. In the SLAM algorithm, the quality of the map depends on the performance of loop closure algorithms. The iterative closest point (ICP) algorithm is widely used for loop closure of the point cloud. However, the ICP algorithm might not work well for ground vehicles because it was originally developed for 3D reconstruction in computer vision field. Therefore, this paper proposes a method to find robust matching correspondences in the ICP algorithm on ground vehicle conditions. The performance of the proposed method is compared with other conventional methods by using KITTI open datasets. The source code is publicly released in the Github website.

ACS Style

Hyungjin Kim; Seungwon Song; Hyun Myung. GP-ICP: Ground Plane ICP for Mobile Robots. IEEE Access 2019, 7, 76599 -76610.

AMA Style

Hyungjin Kim, Seungwon Song, Hyun Myung. GP-ICP: Ground Plane ICP for Mobile Robots. IEEE Access. 2019; 7 (99):76599-76610.

Chicago/Turabian Style

Hyungjin Kim; Seungwon Song; Hyun Myung. 2019. "GP-ICP: Ground Plane ICP for Mobile Robots." IEEE Access 7, no. 99: 76599-76610.