• 로봇학회논문지
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• 제16권3호
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• pp.283-290
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• 2021

We propose a task and motion planning algorithm for clearing obstacles and wiping surfaces, which is essential for surface disinfection during the pathogen disinfection process. The proposed task and motion planning algorithm determines task parameters such as grasping pose and placement location during the planning process without using pre-specified or discretized values. Furthermore, to quickly inspect many unit motions, we propose a motion feasibility prediction algorithm consisting of collision checking and an SVM model for inverse mechanics and self-collision prediction. Planning time analysis shows that the feasibility prediction algorithm can significantly increase the planning speed and success rates in situations with multiple obstacles. Finally, we implemented a hierarchical control scheme to enable wiping motion while following a planner-generated joint trajectory. We verified our planning and control framework by conducted an obstacle-clearing and surface wiping experiment in a simulated disinfection environment.

• Journal of the Korean Data and Information Science Society
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• 제27권3호
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• pp.803-814
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• 2016

Recent times have seen an exponential increase in the amount of spatial data, which is in many cases associated with temporal data. Recent advances in computer technology and computation of hierarchical Bayesian models have enabled to analyze complex spatio-temporal data. Our work aims at modeling data of daily average nitrogen dioxide (NO2) levels obtained from 25 air monitoring sites in Seoul between 2003 and 2010. We considered an independent Gaussian process model and an auto-regressive model and carried out estimation within a hierarchical Bayesian framework with Markov chain Monte Carlo techniques. A Gaussian predictive process approximation has shown the better prediction performance rather than a Hierarchical auto-regressive model for the illustrative NO2 concentration levels at any unmonitored location.

• International Journal of Control, Automation, and Systems
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• 제3권4호
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• pp.509-523
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• 2005

We are developing a novel framework, PRIDE (PRediction In Dynamic Environments), to perform moving object prediction (MOP) for autonomous ground vehicles. The underlying concept is based upon a multi-resolutional, hierarchical approach which incorporates multiple prediction algorithms into a single, unifying framework. The lower levels of the framework utilize estimation-theoretic short-term predictions while the upper levels utilize a probabilistic prediction approach based on situation recognition with an underlying cost model. The estimation-theoretic short-term prediction is via an extended Kalman filter-based algorithm using sensor data to predict the future location of moving objects with an associated confidence measure. The proposed estimation-theoretic approach does not incorporate a priori knowledge such as road networks and traffic signage and assumes uninfluenced constant trajectory and is thus suited for short-term prediction in both on-road and off-road driving. In this article, we analyze the complementary role played by vehicle kinematic models in such short-term prediction of moving objects. In particular, the importance of vehicle process models and their effect on predicting the positions and orientations of moving objects for autonomous ground vehicle navigation are examined. We present results using field data obtained from different autonomous ground vehicles operating in outdoor environments.

• 한국통신학회논문지
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• 제32권6A호
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• pp.550-557
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• 2007

인과 관계에 대한 직관적인 개념으로 Bayesian Networks 알고리즘이나 트리 구조 추측 알고리즘 그리고 유전자 알고리즘을 사용하여 다양한 구조의 상황을 예측을 하게 된다. 하지만 이런 예측 알고리즘들을 상황인지 서비스 구현에 적용하기에는 실제 구현의 어려움과 실시간 환경에서 트레이닝 데이터 처리에서 오는 시간 지연 문제 등이 발생하게 된다. 이 때문에 특정 목적의 상황인지 시스템에서 이 알고리즘들이 어느 정도의 예측 정확도와 신뢰도를 가지고 상황 정보에 부합하는지 미지수이다. 따라서 본 논문에서는 기존의 예측 알고리즘과는 다른 접근 방식을 통해, 사용자의 습관이나 행동양식을 데이터베이스로 만들어 이를 고려함으로써 상황인지 시스템의 상황 정보와 부합되는 Flexible Window 기법을 이용한 위치 예측 알고리즘을 제안한다. 제안된 Flexible Window 기법을 이용한 위치 예측 알고리즘은 동일한 실험 조건 아래, Fixed Window 기법을 이용한 위치 예측 알고리즘보다 평균적으로 5.10% 더 우수한 성능을 보인다. 이 방식은 기하급수적으로 늘어나는 상황 정보를 감안했을 때 알고리즘 수행 시 처리 시간의 감소와 예측 정확도를 향상 시킬 수 있다.

• 융합보안논문지
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• 제12권4호
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• pp.91-96
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• 2012

무선 네트워크의 많은 분야 중에서 MANET(Mobile Ad-hoc Network)은 상당히 발전이 되어있는 기술이다. MANET을 구성하는 노드들은 다중 홉 무선 연결을 이용하여 데이터 전달을 하게 된다. 이러한 환경에서 노드들의 데이터 접근 성능과 가용성을 향상시킬 수 있는 방법이 캐싱 기법이다. 기존의 많은 연구들은 이동 노드들의 다중 홉 연결을 향상시키기 위해 동적인 라우팅 프로토콜에 대해 많은 연구가 이루어져왔다. 그러나 노드들의 이동으로 인하여 유효한 캐시 정보의 관리 및 유지가 쉽지 않다. 본 논문에서는 이동 노드가 원하는 정보의 캐시 발견시 오버헤드를 줄이고 노드들의 이동으로 인한 연결 관리를 위해 클러스터 기반 캐싱 기법을 제안하였다. 그리고 각 클러스터 헤드에서 유효한 캐시 테이블을 유지할 수 있도록 하기 위해 HLP를 이용하였다. 본 논문에서 제안한 기법의 효율성은 실험을 통해 확인하였다.

• 한국조경학회지
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• 제28권2호
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• pp.18-27
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• 2000

The importance of constraints has been one of major issues in recreation for prediction of choice behavior; however, traditional conjoint choice model did not consider the effects of these variables or fail to integrate them into choice model adequately. The purposes of this research are (a) to estimate the effects of constraints in theme park choice behavior by the constraints-induced conjoint choice model, and (b) to test additional explanatory power of the additional constraints in this suggested model against the more parsimonious traditional model. A leading polling agency was employed to select respondents. Both alternative generating and choice set generating fractional factorial design were conducted to meet the necessary and sufficient conditions for calibration of the constraints-induced conjoint choice model. Th alternative-specific model was calibrated. The log-likelihood ratio test revealed that suggested model was accepted in the favor of the traditional model, and the goodness-of-fit($\rho$$^2$) of suggested and traditional model was 0.48427 and 0.47950, respectively. There was no difference between traditional and suggested model in estimates of attribute levels of car and shuttle bus because alternatives were created to estimate the effects of constraints independently from mode related variables. Most parameters values of constraints had the expected sign and magnitude: the results reflected the characteristics of the theme parks, such as abundance of natural attractions and poor accessibility in Everland, location of major fun rides indoor in Lotte World, city park like characteristics of Dream Land, and traffic jams in Seoul. Instead of the multinomial logit model, the nested logit model is recommended for future researches because this model more reasonably reflects the real decision-making process in park choice. Development of new methodology too integrate this hierarchical decision-making into choice model is anticipated.