• Journal of Auto-vehicle Safety Association
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• v.14 no.4
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• pp.16-20
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• 2022

Accurate state estimation is important for autonomous driving. However, the estimation error increases in situations that a lot of longitudinal slip occurs. Therefore, this paper presents a vehicle state estimation method using an Extended Kalman Filter. The filter estimates the states of the host vehicle robust to wheel slip. It utilizes the measurements of the four-wheel rotational speeds, longitudinal acceleration, yaw-rate, and steering wheel angle. Nonlinear measurement model is represented by Ackermann Model. The main advantage of this approach is the accurate estimation of yaw rate due to the measurement of the steering wheel angle. The proposed algorithm is verified in scenarios of autonomous emergency braking (AEB), lane change (LC), lane keeping (LK) using an automated vehicle. The results show that the proposed algorithm guarantees accurate estimation in such scenarios.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.37.2-37
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• 2001

This paper addresses the robust adaptive output feedback tracking for nonlinear systems under disturbances whose bounds are unknown. A new algorithm is proposed for estimation of unknown bounds and adaptive control of the uncertain nonlinear systems. The State estimation is solved using K-filters, together with the construction of a bound of an error in the state estimation due to the perturbation of the disturbance. Tuning functions are used to estimate unknown system parameters without overparametrization. The proposed control algorithm ensures that the out put tracking error converges to a residual set which can be arbitrarily small, while maintaining the boundedness of all other variables. A simulation shows the effectiveness of the proposed approach

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2023.05a
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• pp.252-253
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• 2023

Container terminal automation might offer many potential benefits, such as increased productivity, reduced cost, and improved safety. Autonomous trucks can lead to more efficient container transport. A robust lane detection method is proposed using score-based generative modeling through stochastic differential equations for image-to-image translation. Image processing techniques are combined with Density-Based Spatial Clustering of Applications with Noise (DBSCAN) and Genetic Algorithm (GA) to ensure lane positioning robustness. The proposed method is validated by a dataset collected from the port terminals under different environmental conditions and tested the robustness of the lane detection method with stochastic noise.

• The Transactions of the Korea Information Processing Society
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• v.4 no.9
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• pp.2309-2314
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• 1997

The study introduces a neural network to predict the bankruptcy of insurance companies. As a method to optimize the network, a genetic algorithm suggests optimal structure and network parameters. The neural network designed by genetic algorithm is compared with discriminant analysis, logistic regression, ID3, and CART. The robust neural network model shows the best performance among those models compared.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.52-55
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• 1997

This paper discusses an automatic visual-servoing system, in which a laser and a CCD camera are used for imaging the pattern of joint groove. The algorithm used here is simple and robust to find out the gap width and gap center. As a consequence, the speed of algorithm is very fast and optimized. A feature of this system is that it processes only by summing the vertical line and horizontal line of screen without any image preprocessing in order to get the energy information of lines alternatively. It is practical and useful for the system requiring a fast process time of vision.

• Proceedings of the IEEK Conference
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• 2000.11d
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• pp.263-266
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• 2000

We proposes a new fingerprint minutia matching algorithm which matches the fingerprint minutiae by using adaptive distance. In general, fingerprint is deformed by pressure and orientation when a user press his fingerprint to sensor. These nonlinear deformations change the distance between minutiae and reduce verification rate. We define the adaptive distance using ridge frequency. Adaptive distance normalizes the distance between minutiae and compensates for nonlinear deformation. Our algorithm can distinguish two different fingerprints better and is more robust. Experimental results show that the performance of the proposed algorithm is superior to using Euclidean distance.

• Proceedings of the KIEE Conference
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• 2006.07d
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• pp.2033-2034
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• 2006

In this paper, we applied genetic algorithm to current control for robust control and stability. In conclusion, we prove that current control of genetic algorithm can be high efficiency.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.10
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• pp.639-642
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• 2005

In this paper, a robust nonlinear echo cancellation is proposed, where a third-order adaptive Volterra filtering is employed along with an expanded correlation LMS (ECLMS) algorithm to compensate for nonlinear distortion in the echo path. (e.g., DAC of the hybrid network). Finally, the robustness in the echo cancellation of the proposed approach is demonstrated using computer simulations, where high attenuation of echo signals is achieved even in the double-talk situation (e.n., BdB improvement in ERLE).

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.92.3-92
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• 2002

A lot of localization algorithms have been developed in order to achieve autonomous navigation. However, most of localization algorithms are restricted to certain conditions. In this paper, Monte Carlo localization scheme with a map-matching algorithm is suggested as a robust localization method for the Public Service Robot to accomplish its tasks autonomously. Monte Carlo localization can be applied to local, global and kidnapping localization problems. A range image based measure function and a geometric pattern matching measure function are applied for map matching algorithm. This map matching method can be applied to both polygonal environments and un-polygonal environments and achieves...

• 제어로봇시스템학회:학술대회논문집
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• 1986.10a
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• pp.298-303
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• 1986

A robust and efficient dynamic control algorithm for the position control of robotic manipulators is proposed. This algorithm consists of an open loop control and a closed loop control. The former may have a larger sampling time than the latter. The robustness and efficiency of this algorithm is demonstrated by the simulation about position control of a three-link manipulator with payload and parameter uncertainty.