경위선이 비교적 넓은 간격으로 표시된 종이지도(이하 지도)에서 임의 지점의 경위도 좌표 값을 파악하는 것은 매우 불편하다. 따라서 휴대용GPS 단말기(이하 휴대용GPS)에 표시된 현재 위치의 경위도 좌표 값으로 지도상에서 그 위치를 파악하는 것도 역시 불편하다. 이러한 문제들로 풍부한 지리정보가 담겨져 있는 지도임에도 불구하고 휴대용GPS와 병용하는 것은 결코 쉽지 않다. 더욱 지도상에 다수의 좌표선과 해당 좌표 값 및 측지계가 표시되어 있지 않으면 휴대용GPS와 함께 사용하는 것은 불가능에 가깝다. 본 연구에서는 지도기반 평면격자좌표계란 새로운 기법을 이용하여 어떠한 형태의 지도라도 휴대용GPS와 편리하게 병용할 수 있는 방법을 모색해보고자 한다. 지도기반 평면격자좌표계(Map Based Rectangular Grid, 이하 평면격자좌표계)란 직접 지도에 임의로 기획하는 좌표계로서 축척에 관계없이 지도의 가로･세로 방향으로 1cm 간격마다 한 단위씩 수치가 증가하도록 구성한 좌표계이다. 휴대용GPS의 좌표계 설정에서 사용자가 직접 좌표계 속성을 입력할 수 있는 기능을 통해 임의의 위치 좌표 값을 지도에 기획한 평면격자좌표 값으로 표시할 수 있으므로 보다 편리하고 신속하게 지도상에서 임의의 위치 파악이 가능해진다. 또한 이 좌표계의 특성상 지도상에서 특정 지점의 평면격자좌표 값을 편리하고 신속하게 파악할 수 있을 뿐만 아니라 해당 수치를 휴대용GPS에 그대로 입력하여 특정지점(Waypoint)으로 저장할 수도 있다. 하지만 사용되는 지도에 따라 휴대용GPS에서 다소 복잡한 좌표계 설정을 재시도해야 하고, 취득한 평면격자좌표의 값은 상대적 좌표 값이라는 단점을 지니고 있다.

RRT* (Rapidly exploring Random Tree*) based algorithms are widely used for path planning. Informed RRT* uses RRT* for generating an initial path and optimizes the path by limiting sampling regions to the area around the initial path. RRT* algorithms have several limitations such as slow convergence speed, large memory requirements, and difficulties in finding paths when narrow aisles or doors exist. In this paper, we propose an algorithm to deal with these problems. The proposed algorithm applies the image skeletonization to the gridmap image for generating an initial path. Because this initial path is close to the optimal cost path even in the complex environments, the cost can converge to the optimum more quickly in the proposed algorithm than in the conventional Informed RRT*. Also, we can reduce the number of nodes and memory requirement. The performance of the proposed algorithm is verified by comparison with the conventional Informed RRT* and Informed RRT* using initial path generated by A*.

Recent studies on automatic parking have actively adopted the technology developed for mobile robots. Among them, the path planning scheme plans a route for a vehicle to reach a target parking position while satisfying the kinematic constraints of the vehicle. However, previous methods require a large amount of computation and/or cannot be easily applied to different environmental conditions. Therefore, there is a need for a path planning scheme that is fast, efficient, and versatile. In this study, we use a multi-dimensional path grid map to solve the above problem. This multi-dimensional path grid map contains a route which has taken a vehicle's kinematic constraints into account; it can be used with the A* algorithm to plan an efficient path. The proposed method was verified using Prescan which is a simulation program based on MATLAB. It is shown that the proposed scheme can successfully be applied to both parallel and vertical parking in an efficient manner.

Mapping is a fundamental element for robotic services. There are available many types of map data representation such as grid map, metric map, topology map, etc. As more robots are deployed for services, more chances of exchanging map data among the robots emerge and standardization of map data representation (MDR) becomes more valuable. Currently, activities in developing MDR standard are underway in IEEE Robotics and Automation Society. The MDR standard is for a common representation and encoding of the two-dimensional map data used for navigation by mobile robots. The standard focuses on interchange of map data among components and systems, particularly those that may be supplied by different vendors. This paper aims to introduce MDR standard and its application to map merging. We have applied the basic structure of the MDR standard to a grid map and Voronoi graph as a kind of topology map and performed map merging between two different maps. Simulation results show that the proposed MDR is suitable for map data exchange among robots.

대류권의 건조가스 및 수증기에 의한 GPS 신호의 지연은 GPS 측위 정확도를 저하시키는 주요 원인으로 정밀 측위를 위해서 반드시 소거해야할 대상이다. 이 논문에서는 실시간으로 대류권 지연정보를 생성하여 GPS 측위에 적용하기 앞서, 대류권 지연정보 생성 알고리즘의 가용성을 파악하기 위해 후처리 기반으로 전국의 GPS 상시관측망을 이용하여 한반도 상공의 대류권 지연량 격자 지도를 생성하는 과정을 구현하였다. GPS 자료처리 소프트웨어는 GIPSY 5.0을 사용하였고, 건조지연량과 습윤지연량을 구분하여 산출하기 위해 전국의 AWS 관측망의 관측자료를 이용하였다. 대류권 지연정보에 대한 격자 지도를 생성한 후 격자 지도의 정확도를 검증한 결과, 격자 지도와 GPS 관측소 위치에서 산출된 대류권 지연량의 RMSE는 ZHD 0.7mm, ZWD 7.5mm, ZTD 8.7mm로 나타났다. 산출된 대류권 지연정보를 단일주파수 기반 상대 측위 알고리즘에 적용하여 대류권 지연정보 보정시 측위정확도 향상 정도를 분석하였다. 결과로 측위정확도는 기선거리가 약 297km인 수원(SUWN)과 목포(MKPO)의 상대처리 결과에서 최대 36%가 향상됨을 확인할 수 있었다.

This paper presents a method of sonar grid map matching for topological place recognition. The proposed method provides an effective rotation invariant grid map matching method. A template grid map is firstly extracted for reliable grid map matching by filtering noisy data in local grid map. Using the template grid map, the rotation invariant grid map matching is performed by Ring Projection Transformation. The rotation invariant grid map matching selects candidate locations which are regarded as representative point for each node. Then, the topological place recognition is achieved by calculating matching probability based on the candidate location. The matching probability is acquired by using both rotation invariant grid map matching and the matching of distance and angle vectors. The proposed method can provide a successful matching even under rotation changes between grid maps. Moreover, the matching probability gives a reliable result for topological place recognition. The performance of the proposed method is verified by experimental results in a real home environment

This paper presents a method of topological modeling using only low-cost sonar sensors. The proposed method constructs a topological model by extracting sub-regions from the local grid map. The extracted sub-regions are considered as nodes in the topological model, and the corresponding edges are generated according to the connectivity between two sub-regions. A grid confidence for each occupied grid is evaluated to obtain reliable regions in the local grid map by filtering out noisy data. Moreover, a convexity measure is used to extract sub-regions automatically. Through these processes, the topological model is constructed without predefining the number of sub-regions in advance and the proposed method guarantees the convexity of extracted sub-regions. Unlike previous topological modeling methods which are appropriate to the corridor-like environment, the proposed method can give a reliable topological modeling in a home environment even under the noisy sonar data. The performance of the proposed method is verified by experimental results in a real home environment.

Low-cost sensors have been widely used for mobile robot navigation in recent years. However, navigation performance based on low-cost sensors is not good enough to be practically used. Among many navigation techniques, building of an accurate map is a fundamental task for service robots, and mapping with low-cost IR sensors was investigated in this research. The robot’s orientation uncertainty was considered for mapping by modifying the Bayesian update formula. Then, the data association scheme was investigated to improve the quality of a built map when the robot’s pose uncertainty was large. Six low-cost IR sensors mounted on the robot could not give rich data enough to align the range data by the scan matching method, so a new sample-based method was proposed for data association. The real experiments indicated that the mapping method proposed in this research was able to generate a useful map for navigation.

Representing an environment as the probabilistic grids is effective to sense outlines of the environment in the mobile robot area. Outlines of an environment can be expressed factually by using the probabilistic grids especially if sonar sensors would be supposed to build an environment map. However, the difficult problem of a sonar such as a specular reflection phenomenon should be overcome to build a grid map through sonar observations. In this paper, the NRF(Neighborhood Recognition Factor) was developed for building a grid map in which the specular reflection effect is minimized. Also the reproduction rate of the gird map built by using NRF was analyzed with respect to a true map. The experiment was conducted in a home environment to verify the proposed technique.