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추계적 페트리넷을 통한 동적 환경에서의 지능적인 환경정보의 갱신
박중태(Joong-Tae Park),이용주(Yong-Ju Lee),송재복(Jae-Bok Song) 대한전기학회 2006 대한전기학회 학술대회 논문집 Vol.2006 No.10
This paper proposes an intelligent decision framework for update of the environment model using GSPN(generalized stochastic petri nets). The GSPN has several advantages over direct use of the Markov Process. The modeling, analysis, and performance evaluation are conducted on the mathematical basis. By adopting the probabilistic approach, our decision framework helps the robot to decide the time to update the map. The robot navigates autonomously for a long time in dynamic environments. Experimental results show that the proposed scheme is useful for service robots which work semi-permanently and improves dependability of navigation in dynamic environments.
박중태(Joong-Tae Park),송재복(Jae-Bok Song) 제어로봇시스템학회 2011 제어·로봇·시스템학회 논문지 Vol.17 No.3
This paper describes a sensor fusion-based semantic map building which can improve the capabilities of a mobile robot in various domains including localization, path-planning and mapping. To build a semantic map, various environmental information, such as doors and cliff areas, should be extracted autonomously. Therefore, we propose a method to detect doors, cliff areas and robust visual features using a laser scanner and a vision sensor. The GHT (General Hough Transform) based recognition of door handles and the geometrical features of a door are used to detect doors. To detect the cliff area an robust visual features, the tilting laser scanner and SIFT features are used, respectively. The proposed method was verified by various experiments and showed that the robot could build a semantic map autonomously in various indoor environments.
기능별로 분류된 프레임워크에 기반한 실내용 이동로봇의 주행시스템
박중태(Joong-Tae Park),송재복(Jae-Bok Song) 제어로봇시스템학회 2009 제어·로봇·시스템학회 논문지 Vol.15 No.7
This paper proposes a new integrated navigation system for a mobile robot in indoor environments. This system consists of five frameworks which are classified by function. This architecture can make the navigation system scalable and flexible. The robot can recover from exceptional situations, such as environmental changes, failure of entering the narrow path, and path occupation by moving objects, using the exception recovery framework. The environmental change can be dealt with using the probabilistic approach, and the problems with the narrow path and path occupation are solved using the ray casting algorithm and the Bayesian update rule. The proposed navigation system was successfully applied to several robots and operated in various environments. Experimental results showed good performance in that the exception recovery framework significantly increased the success rate of navigation. The system architecture proposed in this paper can reduce the time for developing robot applications through its reusability and changeability.
박중태(Joong-Tae Park),송재복(Jae-Bok Song),김문상(Munsang Kim) 대한기계학회 2010 대한기계학회 춘추학술대회 Vol.2010 No.11
This paper describes a sensor fusion-based exploration scheme for semantic map building. To build a semantic map, a robot should extract meaningful features such as doors, corridor and so on. Therefore, we propose a method to detect doors and cliff areas using a laser scanner and a vision sensor. This paper also proposes an exploration strategy which is suitable to extract the meaningful features. Various experiments demonstrate that a robot can build a semantic map autonomously in unknown environments.
박중태(Joong-Tae Park),송재복(Jae-Bok Song) 제어로봇시스템학회 2009 제어·로봇·시스템학회 논문지 Vol.15 No.12
This paper proposes an exploration strategy to efficiently find a specific place in large unknown environments with wall-following based path planning. Many exploration methods proposed so far showed good performance but they focused only on efficient planning for modeling unknown environments. Therefore, to successfully accomplish the room finding task, two additional requirements should be considered. First, suitable path-planning is needed to recognize the room number. Most conventional exploration schemes used the gradient method to extract the optimal path. In these schemes, the paths are extracted in the middle of the free space which is usually far from the wall. If the robot follows such a path, it is not likely to recognize the room number written on the wall because room numbers are usually too small to be recognized by camera image from a distance. Second, the behavior which re-explores the explored area is needed. Even though the robot completes exploration, it is possible that some rooms are not registered in the constructed map for some reasons such as poor recognition performance, occlusion by a human and so on. With this scheme, the robot does not have to visit and model the whole environment. This proposed method is very simple but it guarantees that the robot can find a specific room in most cases. The proposed exploration strategy was verified by various experiments.
외곽선 영상과 Support Vector Machine 기반의 문고리 인식을 이용한 문 탐지
이동욱(Dong-Wook Lee),박중태(Joong-Tae Park),송재복(Jae-Bok Song) 제어로봇시스템학회 2010 제어·로봇·시스템학회 논문지 Vol.16 No.12
A door can serve as a feature for place classification and localization for navigation of a mobile robot in indoor environments. This paper proposes a door detection method based on the recognition of various door handles using the general Hough transform (GHT) and support vector machine (SVM). The contour and color histogram of a door handle extracted from the database are used in GHT and SVM, respectively. The door recognition scheme consists of four steps. The first step determines the region of interest (ROI) images defined by the color information and the environment around the door handle for stable recognition. In the second step, the door handle is recognized using the GHT method from the ROI image and the image patches are extracted from the position of the recognized door handle. In the third step, the extracted patch is classified whether it is the image patch of a door handle or not using the SVM classifier. The door position is probabilistically determined by the recognized door handle. Experimental results show that the proposed method can recognize various door handles and detect doors in a robust manner.
한혜민(Hye-Min Han),박중태(Joong-Tae Park),송재복(Jae-Bok Song) 제어로봇시스템학회 2011 제어·로봇·시스템학회 논문지 Vol.17 No.12
This paper proposes a novel approach to building an occupancy grid map using sonar data. It is very important for a mobile robot to recognize and construct its surrounding environments for navigation. However, the grid map constructed by ultrasonic sensors cannot represent a realistic shape of given environments due to incorrect sonar measurements caused by specular reflection. To overcome this problem, we propose an advanced sonar sensor model which consists of distance and shape factors used to determine the reliability of sensor data. Through this sensor model, a robot can build a high-quality grid map. The proposed method was verified by various experiments and showed that the robot could build an accurate map with sonar data in various indoor environments.
정민국(Min-Kuk Jung),박중태(Joong-Tae Park),송재복(Jae-Bok Song) 대한기계학회 2012 大韓機械學會論文集A Vol.36 No.6
기존의 경로계획 방법은 최단거리의 경로를 생성하는 것에 목적을 둔다. 그러나 이렇게 선택된 최적의 경로가 안전한 주행을 보장해주지는 못하는데, 이는 종종 좁은 통로나 이동 장애물이 많은 영역으로 경로를 생성하기 때문이다. 그러므로 로봇은 정보 격자지도를 이용하여 안전하게 이동할 수 있는 경로를 생성하는 것이 필요하다. 이 정보 격자지도는 기존의 지도가 가지고 있는 영역의 정보 외에 유도지역과 위험지역을 포함한다. 안전한 경로는 인력과 척력을 이용하여 위험지역을 우회하고 유도지역으로 접근되어 생성된다. 실험 및 시뮬레이션은 제안된 방법이 안전한 영역으로 경로를 생성시켜, 안전하게 주행하는 데 유용하다는 것을 보여준다. Conventional path planning methods have focused on the generation of an optimal shortest path to the goal. However, this optimal path cannot guarantee safe navigation, because it can often lead to a narrow area. Therefore, we propose a Coulomb’s law?based safe path planning method that uses an information grid map. The information grid map includes four types of information: occupied, empty, guide, and dangerous areas. A safe path can be generated away from the dangerous area and close to the guide area by repulsive and attractive forces, respectively. Experiments and simulations show that the proposed method can generate paths inside the safe region and is useful for safe navigation.