• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.3
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• pp.304-309
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• 2014

In this paper, we design a hybrid wheeled and legged mobile robot with a waist joint. The proposed hybrid mobile robot is designed to have a hybrid structure with leg and wheel for the efficient movement in flat and uneven surfaces. The proposed robot have a waist joint that is used to stably transform from wheeled driving to legged walking of the robot and to overcome non-flat surface. In order to recognize various environments we use LRF sensor, PSD sensor, CCD camera. Also, a motion planning method for hybrid mobile robot with a waist joint is proposed to select wheeled driving motion and legged walking motion of the robot based the environment types. We verify the efficient mobility of the developed hybrid mobile robot through navigation experiments using the proposed motion planning method in various environments.

• Journal of Korean Society for Quality Management
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• v.49 no.3
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• pp.245-254
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• 2021

Purpose: In order to accurately reach an underwater projectile to a target point, reliable INS and accurate arrangement of INS between master and slave INS is paramount. Unlike terrestrial and aerial environments, underwater projectile will operates in a restricted environment where location information cannot be received or sent through satellites. In this report, we review the factors affecting the transfer alignment of master and slave INS, as well as how to improve the positional error between INS through improved transfer alignment algorithms. Methods: In this work, we propose an improvement algorithm and verify it through simulation and driving test. The simulation confirmed the difference in the transfer alignment azimuth by fitting the MINS and SINS indoors, displacement in posture, and the process of transfer alignment between MINS and SINS through a driving test to confirm algorithm can improve the arrangement. Results: According to this study, reason for the error in the transfer alignment between MINS/SINS is the factors of the system where movements such as roll, pitch, yaw are not inter locked in real time due to the delay in transmit/receive system. And confirm that the improved algorithm has a desirable effect on accuracy. Conclusion: Through this work, it is possible to identify ways to improve the accuracy of underwater projectiles to reach their target points under various underwater environments and launch condition.

• Journal of Korea Society of Industrial Information Systems
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• v.26 no.4
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• pp.11-18
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• 2021

We propose a method that combines learning in a virtual environment and a real environment for indoor autonomous driving through reinforcement learning. In case of learning only in the real environment, it takes about 80 hours, but in case of learning in both the real and virtual environments, it takes 40 hours. There is an advantage in that it is possible to obtain optimized parameters through various experiments through fast learning while learning in a virtual environment and a real environment in parallel. After configuring a virtual environment using indoor hallway images, prior learning was carried out on the desktop, and learning in the real environment was conducted by connecting various sensors based on Jetson Xavier. In addition, in order to solve the accuracy problem according to the repeated texture of the indoor corridor environment, it was possible to determine the corridor wall object and increase the accuracy by learning the feature point detection that emphasizes the lower line of the corridor wall. As the learning progresses, the experimental vehicle drives based on the center of the corridor in an indoor corridor environment and moves through an average of 70 steering commands.

• Journal of Auto-vehicle Safety Association
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• v.14 no.1
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• pp.6-13
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• 2022

The Ministry of Land, Infrastructure and Transport (MoLIT) and the Korean Automobile Testing and Research Institute (KATRI) are supporting the development of Lv.3 automated vehicle (hereinafter, AV) technology by constructing an automated driving pilot city (as known as K-City) equipped with total 5 evaluation environments (urban, motorway, suburban, community road, and autonomous parking facility) which is a test bed exclusively for AV (2017~2018). An upgrade project is in a progress to materialize harsh environments such as bad weather (rain, fog, etc.) and reproduction of communication jamming (GPS blocking, etc.) with the purpose of supporting the development of Lv.4 connected & automated vehicle (hereinafter, CAV) technology (2019~2022). We intend to proactively establish a national level standard for CAV test-bed and test road requirements, test method, etc. for establishment of a road map for the construction of the test bed which is being promoted step by step and analyze and, when required, benchmark the case of China that has announced and is utilizing it. Through this, we plan to define standardized requirements (evaluation facility, evaluation system, etc.) on the test bed for the development of Lv.4/4+ CAV technology and utilize the same for the design and construction of a test bed, establishment of a road map for the construction of a real car-based test environment related to the support for autonomous driving service substantiation, etc. through provision of an evaluation environment utilizing K-City, and the establishment of a K-City upgrade strategies, etc.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.35 no.4
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• pp.55-62
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• 2012

In this study, it was observed through the ability of performing secondary tasks and baseline fetal heart rate how the supply of lavender, peppermint and highly concentrated oxygen (40%) affected distraction due to the performance of secondary tasks in the driving environment. Twelve male university students conducted secondary tasks while driving in the environments (6 in total) mixed and designed with oxygen concentration (21%, 40%) and the condition of odors (Normal, Lavender, Peppermint). The test was proceeded in order of stable state (5mins), driving (5mins), and secondary tasks (1min), and by extracting ECG data from every section by 30secs, the mean value of baseline fetal heart rate was calculated. As a result of analysis, in the ability of performing secondary tasks, a percentage of correct answers showed no difference in oxygen concentration and the condition of odors (p > 0.05). In performance completion time, a percentage of correct answers decreased showing a statistically significant difference in the condition of odors compared with the condition where odors were not provided (p < 0.05). As for baseline fetal heart rate, in the comparison between sections, while performing secondary tasks, it increased showing a significant difference compared with stable state and driving state (p < 0.05). The effect of interaction was observed in oxygen concentration and the condition of odors. When odors were not provided, baseline fetal heart rate decreased in 40% oxygen concentration compared with 21% oxygen concentration (p < 0.05), however, when peppermint was provided, it increased in 40% oxygen concentration compared with 21% oxygen concentration (p < 0.05). In conclusion, the fact that the condition of odors increased the ability of calculation, and when only the highly concentrated oxygen was provided, parasympathetic nerve system was activated, however, when highly concentrated oxygen was provided with peppermint at the same time, sympathetic nervous system (sns) was activated, which had a negative effect on the autonomic nervous system was drawn.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.6
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• pp.235-249
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• 2020

The Ministry of Land, Infrastructure and Transport established safety standards for Level 3 autonomous vehicles for the first time in the world in December 2019, and specified the safety standards for conditional autonomous driving systems. Accordingly, it is necessary to analyze the influence of various driving environments on take-over. In this study, using a driving simulator, we investigated how traffic conditions and weather conditions affect take-over time and stabilization time. The experimental procedure was conducted in the order of preliminary training, practice driving, and test driving, and the test driving was conducted by dividing into a traffic density and geometry experiment and a weather environment experiment. As a result of the experiment, it was analyzed that the traffic volume and weather environment did not affect the take-over time and take-over stabilization time, and only the curve radius affects take-over stabilization time.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.12
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• pp.363-370
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• 2023

Object detection technology that accurately recognizes the road and surrounding conditions is a key technology in the field of autonomous driving. In the field of autonomous driving, object detection technology requires real-time performance as well as accuracy of inference services. Task offloading technology should be utilized to apply object detection technology for accuracy and real-time on resource-constrained devices rather than high-performance machines. In this paper, experiments such as performance comparison of task offloading, performance comparison according to input image resolution, and performance comparison according to camera object resolution were conducted and the results were analyzed in relation to the application of task offloading for real-time object detection of autonomous driving in resource-constrained devices. In this experiment, the low-resolution image could derive performance improvement through the application of the task offloading structure, which met the real-time requirements of autonomous driving. The high-resolution image did not meet the real-time requirements for autonomous driving due to the increase in communication time, although there was an improvement in performance. Through these experiments, it was confirmed that object recognition in autonomous driving affects various conditions such as input images and communication environments along with the object recognition model used.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.2
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• pp.108-114
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• 2015

Automated driving systems require a high level of performance regarding environmental perception, especially in urban environments. Today's on-board sensors such as radars or cameras do not reach a satisfying level of development from the point of view of robustness and availability. Thus, map data is often used as an additional data input to support these systems. An accurate digital map is used as a powerful additional sensor. In this paper, we propose a new approach for vehicle localization using a lane map and a single-layer LiDAR. The maps are created beforehand using a highly accurate DGPS and a single-layer LiDAR. A pose estimation of the vehicle was derived from an iterative closest point (ICP) match of LiDAR's intensity data to the lane map, and the estimated pose was used as an observation inside a Kalmanfilter framework. The achieved accuracy of the proposed localization algorithm is evaluated with a highly accurate DGPS to investigate the performance with respect to lateral vehicle control.

• IEMEK Journal of Embedded Systems and Applications
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• v.7 no.2
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• pp.61-70
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• 2012

This paper describes terrain-adaptive attitude controller for a hybrid mobile platform which operates in wheel & track mode. The wheel mode of the hybrid mobile platform allows quick driving performance in the flatland, while the track mode provides adaptive movement in the rough ground or stairway. The switching of the platform between two modes is automatically controlled by attitude controller algorithm. In addition, in the track mode, the platform automatically adjusts its attitude angle to overcome the obstacles in front. This paper demonstrates the attitude controller for the aforementioned wheel-track hybrid mobile platform in order to overcome terrain obstacles by using an adaptive method. The driving performance of the hybrid mobile platform has been tested and verified in various surrounding environments in both wheel and track mode. Further, this paper presents the experiments by using the track structure of mobile platform on forming adaptive attitude under various types of obstacles. The practicability and effectiveness of the proposed attitude controller of the platform has been demonstrated in urban building and a test-bed.

• Journal of Korean Institute of Industrial Engineers
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• v.26 no.3
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• pp.257-264
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• 2000

This research suggested a method by which the driver space can be designed to best accommodate the driver's anthropometric characteristics. Three-dimensional manikins and a variable seating buck were developed and used for this study. Manikins were designed with 18 links comprising the 95th percentile male and 5th percentile female data. The seating buck was built to create various driving environments using the distance and the height between the H-point(hip pivot) of the seat and the AHP(accelerator heel point), the angle of the back rest, the angle of the steering wheel, the vertical distance of the steering wheel, and the location of the T.G.S.(transmission gear shift) knob. Measurements of each variable were collected with a coordinate measuring machine by positioning the 3-D manikin under various combinations of the design factors of the seating buck, which was constructed based on mid-size domestic passenger cars. The data were then converted to the joint angles of the driver. The combination of the measurements for an optimal driving environment is suggested by applying sets of the joint angles at which the driver feels comfortable.