• Journal of the Korea Institute of Military Science and Technology
• /
• v.3 no.1
• /
• pp.38-46
• /
• 2000

In this paper, robust depth and course controllers of AUV(autonomous underwater vehicles) using LMI-based H$_{\infty}$ servo control are proposed. The $H_{\infty}$ servo problem is modified to an $H_{\infty}$ control problem for the generalized plant that includes a reference input mode, and then a sub-optimal solution that satisfies a given performance criteria is calculated by LMI(Linear Matrix Inequality) approach. The robust depth and course controllers are designed to be satisfied the robust stability about the modeling error generated from the perturbation of the hydrodynamic coefficients and the robust tracking property under sea wave and tide disturbances. The performances of the designed controllers are evaluated by computer simulations, and these simulation results show the applicability of the proposed robust depth and course controller.

• International Journal of Internet, Broadcasting and Communication
• /
• v.12 no.2
• /
• pp.21-29
• /
• 2020

This paper presents an effective single image haze removal using edge-preserving and adaptive transmission estimation to enhance the visibility of outdoor images vulnerable to weather and environmental conditions with computational complexity reduction. The conventional methods involve the time-consuming refinement process. The proposed transmission estimation however does not require the refinement, since it preserves the edges effectively, which selects one between the pixel-based dark channel and the patch-based dark channel in the vicinity of edges. Moreover, we propose an adaptive transmission estimation to improve the visual quality particularly in bright areas like sky. Experimental results with various hazy images represent that the proposed method is superior to the conventional methods in both subjective visual quality and computational complexity. The proposed method can be adopted to compose a haze removal module for realtime devices such as mobile devices, digital cameras, autonomous vehicles, and so on as well as PCs that have enough processing resources.

• Journal of Auto-vehicle Safety Association
• /
• v.10 no.1
• /
• pp.32-37
• /
• 2018

This paper proposes autonomous speed control strategy for an Electric Vehicle on urban road. SNU campus road is used to reperesent urban road situation. Motor efficiency of driving on campus circulation road can be improved by controlling velocity properly. Given information of campus road, especially slope of road, acceleration is selected from candidate, considering consumed power, human factor and driving time. To apply urban situation, preceding vehicle is also considered. With preceding vehicle, acceleration is defined according to clearance and relative velocity. Acceleration is bounded in normal range. Proposed acceleration control method is activated with proper velocity range for campus circulation road. With acceleration control, motor efficiency becomes better than driving with constant vehicle. To evaluate the performance of proposed acceleration controller, simulation study is conducted via MATLAB.

• 제어로봇시스템학회:학술대회논문집
• /
• 1999.10a
• /
• pp.313-316
• /
• 1999

In this paper, a quantization algorithm by which the accumulative error can be prevented is presented. In digital control systems, the quantization cannot be avoided because of the finite word length of digital computers. The error due to quantization of the computed values may be tolerable in case of directly using them. In case of using the accumulated values, the error between sum of the original values and that of the quantized values becomes larger as the number of the values to be summed increases. Such an increasing accumulative error is critical for the control of precise NC machines, robots and autonomous vehicles. To solve this problem, a quantization algorithm without the accumulative error is presented. Basically, the algorithm is based on the feedback loop by which the accumulationive of the quantization error can be prevented. The error boundness of the proposed algorithm is proven and a computer simulation is performed to show the validity of the algorithm.

• Ocean Systems Engineering
• /
• v.3 no.1
• /
• pp.71-77
• /
• 2013

The effective tracking area of ultra short baseline (USBL) systems strongly relates to the safety of autonomous underwater vehicles (AUVs). This problem has not been studied previously. A method for determining the effective tracking area using acoustic theory is proposed. Ray acoustic equations are used to draw rays which ascertain the effective space. The sonar equation is established in order to discover the available range of the USBL system and the background noise level using sonar characteristics. The available range defines a hemisphere like enclosure. The overlap of the effective space with the hemisphere is the effective area for USBL systems tracking AUVs. Lake and sea trials show the proposed method's validity.

• Journal of Korea Multimedia Society
• /
• v.20 no.2
• /
• pp.144-152
• /
• 2017

Among the technologies for implementing autonomous vehicles, advanced driver assistance system is a key technology to support driver's safe driving. In the technology using the vision sensor having a high utility, various preprocessing methods are used prior to feature extraction for lane detection. However, in the existing methods, the unnecessary lane candidates such as cars, lawns, and road separator in the road area are false positive. In addition, there are cases where the lane candidate itself can not be extracted in the area under the overpass, the lane within the dark shadow, the center lane of yellow, and weak lane. In this paper, we propose an efficient preprocessing method using k-means clustering for image division and the HSV color model. When the proposed preprocessing method is applied, the true positive region is maximally maintained during the lane detection and many false positive regions are removed.

• The Journal of Korea Robotics Society
• /
• v.6 no.2
• /
• pp.182-188
• /
• 2011

This paper describes a method of road tracking by using a vision and laser with extracting road boundary (road lane and curb) for navigation of intelligent transport robot in structured road environments. Road boundary information plays a major role in developing such intelligent robot. For global navigation, we use a global positioning system achieved by means of a global planner and local navigation accomplished with recognizing road lane and curb which is road boundary on the road and estimating the location of lane and curb from the current robot with EKF(Extended Kalman Filter) algorithm in the road assumed that it has prior information. The complete system has been tested on the electronic vehicles which is equipped with cameras, lasers, GPS. Experimental results are presented to demonstrate the effectiveness of the combined laser and vision system by our approach for detecting the curb of road and lane boundary detection.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.8 no.12
• /
• pp.4489-4501
• /
• 2014

We propose a novel lane detection method based on classification in image sequences. Both structural and statistical features of the extracted bright shape are applied to the neural network for finding correct lane marks. The features used in this paper are shown to have strong discriminating power to locate correct traffic lanes. The traffic lanes detected in the current frame is also used to estimate the traffic lane if the lane detection fails in the next frame. The proposed method is fast enough to apply for real-time systems; the average processing time is less than 2msec. Also the scheme of the local illumination compensation allows robust lane detection at nighttime. Therefore, this method can be widely used in intelligence transportation systems such as driver assistance, lane change assistance, lane departure warning and autonomous vehicles.

• Journal of Institute of Control, Robotics and Systems
• /
• v.21 no.8
• /
• pp.773-780
• /
• 2015

Navigation in outdoor environments is a fundamental and challenging problem for unmanned ground vehicles. Detecting lane markings or boundaries on the road may be one of the solutions to make navigation easy. However, because of various environments and road conditions, a robust lane detection is difficult. In this paper, we propose a new approach for estimating virtual lanes on a traversable region. Estimating the virtual lanes consist of two steps: (i) we detect virtual road region through road model selection based on traversability at current frame and similarity between the interframe and (ii) we estimate virtual lane using the number of lane on the road and results of previous frame. To improve the detection performance and reduce the searching region of interests, we use a probability map representing the traversability of the outdoor terrain. In addition, by considering both current and previous frame simultaneously, the proposed method estimate more stable virtual lanes. We evaluate the performance of the proposed approach using real data in outdoor environments.

• Journal of Institute of Control, Robotics and Systems
• /
• v.18 no.2
• /
• pp.87-93
• /
• 2012

In this paper, a formation guidance method for UAVs (Unmanned Aerial Vehicles) to simulate the formation flight of birds proposed. The proposed method solves all issues of approaching for formation, formation keeping, and scarce chance to be collided with each UAV during formation process. Also, we design the feedforward controller to compensate the change of speed and heading for maneuvering of the leader UAV and the feedback controller to consider the response lag of the system. The stability and performance of the proposed controller is verified via numerical simulations of the full 6-Dof model of UAV.