• 한국정밀공학회지
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• 제31권3호
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• pp.253-259
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• 2014

This study proposes a map-based control method to improve a vehicle's lateral stability, and the performance of the proposed method is compared with that of the conventional model-referenced control method. Model-referenced control uses the sliding mode method to determine the compensated yaw moment; in contrast, the proposed map-based control uses the compensated yaw moment map acquired by vehicle stability analysis. The vehicle stability region is calculated by a topological method based on the trajectory reversal method. The performances of model-referenced control and map-based control are compared under various road conditions and driving inputs. Model-referenced control uses a control input to satisfy the linear reference model, and it generates unnecessary tire lateral forces that may lead to worse performance than an uncontrolled vehicle with step steering input on a road with low friction coefficient. The simulation results show that map-based control provides better stability than model-referenced control.

• 제어로봇시스템학회논문지
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• 제8권6호
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• pp.492-497
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• 2002

Map building is the process of modeling the robot's environment. The map is usually built based on a grid-based or topological approach, which has its own merits and demerits. These two methods, therefore, can be integrated to provide a better way of map building, which compensates for each other's drawbacks. In this paper, a method of building the topological map based on the occupancy grid map through a Voronoi diagram is presented and verified by various simulations. This Voronoi diagram is made by using a labeled Voronoi diagram scheme which is suitable for the occupancy grid maps. It is shown that the Proposed method is efficient and simple fur building a topological map. The simple path-planning problem is simulated and experimented verify validity of the proposed approach.

• 제어로봇시스템학회논문지
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• 제17권9호
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• pp.916-921
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• 2011

Mobile robot localization is the task of estimating the robot pose in a given environment. This research deals with outdoor localization based on an elevation map. Since outdoor environments are large and contain many complex objects, it is difficult to robustly estimate the robot pose. This paper proposes a Hausdorff distance-based map matching method. The Hausdorff distance is exploited to measure the similarity between extracted features obtained from the robot and elevation map. The experiments and simulations show that the proposed Hausdorff distance-based map matching is useful for robust outdoor localization using an elevation map. Also, it can be easily applied to other probabilistic approaches such as a Markov localization method.

• 제어로봇시스템학회논문지
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• 제12권7호
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• pp.693-699
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• 2006

An accurate and compact map is essential to an autonomous mobile robot system. For navigation, it is efficient to use an occupancy grid map because the environment is represented by probability distribution. But it is difficult to apply it to the large environment since it needs a large amount of memory proportional to the environment size. As an alternative, a topological map can be used to represent it in terms of the discrete nodes with edges connecting them. It is usually constructed by the Voronoi-like graphs, but in this paper the topological map is incrementally built based on the local grid map using the thinning algorithm. This algorithm can extract only meaningful topological information by using the C-obstacle concept in real-time and is robust to the environment change, because its underlying local grid map is constructed based on the Bayesian update formula. In this paper, the position probability is defined to evaluate the quantitative reliability of the end nodes of this thinning-based topological map (TTM). The global TTM can be constructed by merging each local TTM by matching the reliable end nodes determined by the position probability. It is shown that the proposed TTM can represent the environment accurately in real-time and it is readily extended to the global TTM.

• 전기학회논문지
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• 제58권8호
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• pp.1605-1614
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• 2009

The technique of simultaneous localization and mapping is the most important research topic in mobile robotics. In the process of building a map in its available memory, the robot memorizes environmental information on the plane of grid or topology. Several approaches about this technique have been presented so far, but most of them use mapping technique as either grid-based map or topology-based map. In this paper we propose a frame of solving the SLAM problem of linking map covering, map building, localizing, path finding and obstacle avoiding in an automatic way. Some algorithms integrating grid and topology map are considered and this make the SLAM performance faster and more stable. The proposed scheme uses an occupancy grid map in representing the environment and then formulate topological information in path finding by A${\ast}$ algorithm. The mapping process is shown and the shortest path is decided on grid based map. Then topological information such as direction, distance is calculated on simulator program then transmitted to robot hardware devices. The localization process and the dynamic obstacle avoidance can be accomplished by topological information on grid map. While mapping and moving, pose of the robot is adjusted for correct localization by implementing additional pixel based image layer and tracking some features. A laser range finer and electronic compass systems are implemented on the mobile robot and DC geared motor wheels are individually controlled by the adaptive PD control method. Simulations and experimental results show its performance and efficiency of the proposed scheme are increased.

• 제어로봇시스템학회논문지
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• 제21권2호
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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.

• Transactions on Control, Automation and Systems Engineering
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• 제1권1호
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• pp.62-68
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• 1999

FCM(Fuzzy Cognitive Map) is proposed for representing causal reasoning. Its structure allows systematic causal reasoning through a forward inference. Authors have already proposed a diagnostic system based on FCM to utilized to identify the true origin of fault by on-line pattern diagnosis. In FCM based fault diagnosis, Temporal Associative Memories (TAM) recall of FCM is utilized to identify the true origin of fault by on-line pattern match where predicted pattern sequences obtained from TAM recall of fault FCM models are compared with actually observed ones. In engineering processes, the propagation delays are induced by the dynamics of processes and may vary with variables involved. However, disregarding such propagation delays in FCM-based fault diagnosis may lead to erroneous diagnostic results. To solve the problem, a concept of FTCM(Fuzzy Time Cognitive Map) is introduced into FCM-based fault diagnosis in this work. Expecially, translation method of FTCM makes it possible to diagnose the fault for some discrete time. Simulation studies through two-tank system is carried out to verify the effectiveness of the proposed diagnostic scheme.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.186-189
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• 2005

In a clinical setting, developing a reliable method for the automated drug infusion system would improve a drug therapy under the unexpected and acute changes of hemodynamics. The conventional proportional-integral-derivative (PID) controller might not be able to achieve maximum performance because of the unexpected change of the intra- and inter-patient variability. The fuzzy PID control and the conventional PID control were tested under the unexpected response of mean arterial blood pressure (MAP) to a vasopressor agent during acute hypotension. Compared with the conventional PID control, the fuzzy PID control performed the robust MAP regulation regardless of the unexpected MAP response (average absolute value of the error between target value and actual MAP: 0.98 vs. 2.93 mmHg in twice response of the expected MAP and 2.59 vs. 9.75 mmHg in three-times response of the expected MAP). The result was due to the adaptive change of the proportional gain in PID parameters.

• Agricultural and Biosystems Engineering
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• 제4권1호
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• pp.22-27
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• 2003

An autonomous tractor requires not only automatic steering (automatic guidance) but also automated control of tractor functions and implement operations. Examples of tractor functions include engine throttle, transmission speed, and 3-point hitch position. Implement operations include tillage, planting, and cultivating. This article provides an overview of a map-based methodology used for the implementation of autonomous field operations of agricultural tractors. The procedure for developing autonomous field operation maps were presented, and several important issues in the implementation of map-based autonomous operations were discussed. These issues included combining field operation maps, position offset, and real-time sensing and update of field operation maps.

• 한국통신학회논문지
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• 제29권10A호
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• pp.1131-1138
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• 2004

IP 기반의 이동 통신망에서는 사용자들에게 연속적인 이동성을 제공하기 위해서 여러 이동성 에이젼트가 사용된다. 대규모 모바일 IP 시스템의 경우 이러한 에이젼트의 확장성과 규모성이 중요한 문제가 될 수 있다. 모바일 Ipv6에서의 시그널링 부하와 핸드오프 지연 시간을 줄이기 위해서 제안된 계층적 모바일 Ipv6에서는 MAP이라고 하는 지역 홈 에이젼트를 사용하여 위치 등록을 지역적으로 처리 가능하도록 한다. 하지만 한 지역 내에서의 움직임이 많은 경우 이러한 MAP이 성능상의 병목 지점이 될 수 있다. 이는 MAP이 시그널링 트래픽 뿐만이 아니라 이동 단말기에게 전달되는 데이터 트래픽에 대한 터널링 기능도 담당하기 때문이다. 따라서 보다 안정적인 서비스를 위해서는 이러한 MAP에서 서비스 받는 단말기의 수를 제한할 필요가 있다. 본 논문에서는 기존의 무선망 자원 할당에서 사용되던 수락 제어 기법과 SMR (Session-to-Mobility Ratio)에 기반한 교체 기법을 이용하여 MAP의 부하를 효과적으로 제어할 수 있는 적응형 부하 제어 기법을 제안한다. 성능 분석을 위해서 제안한 기법을 마르코브 체인을 통해 모델링하여 핸드오프 이동 단말기 봉쇄 확률과 새 이동 단말기 봉쇄 확률을 분석하였다. 그 결과 제안한 기법은 두 봉쇄 확률을 아주 낮은 수준으로 낮출 수 있다는 것을 알 수 있었다.