• 제어로봇시스템학회논문지
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• 제22권12호
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• pp.1053-1060
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• 2016

As location recognition for autonomous vehicles develops, the need for a precise map for autonomous driving has increased. A precise map must be built based upon accurate position. Recent studies have accelerated research in this area by using various sensors that calculate the accurate position by comparing and recognizing objects around the roads. However, application of such methods is limited because these studies only take objects with significant verticality into consideration. Thus, new research is needed to overcome the limitations: a method that is not constrained by the existence of certain types of surrounding objects shall be proposed. Most roads contain road marking information, such as lanes, direction signs, and pedestrian crossings. Such information on the road surface is a valuable resource for building a precise map. This paper proposes a method of building a precise map by using road marking information.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.1184-1189
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• 2003

Map building and position estimation capabilities are practically indispensable for a mobile robot to execute its given tasks in its working environments. An autonomous map building method and a smart localization method is proposed in our previous works. The experimental verifications are carried out in this paper. We applied the proposed algorithms to mobile service robots in large-scale indoor buildings. Experimental results show that our strategy is reliable and feasible in tough conditions like non-polygonal and dynamic environments. The advantages of the algorithms are well-illustrated through real experiments.

• Journal of Advanced Marine Engineering and Technology
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• 제32권2호
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• pp.351-358
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• 2008

This paper introduces a map building algorithm which can collect environmental information using ultrasonic sensors. And also this paper discusses a traveling algorithm using environmental information which leads to the map building algorithm. In order to accomplish the proposed traveling algorithm, this paper additionally discusses a path revision algorithm. For verifying the proposed algorithms, several experiments are executed using a mobile robot physically designed in this paper. The conclusion is that the proposed algorithm is very effective and is applicable to mobile robots especially requiring a low-cost environmental information.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.724-728
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• 2005

This paper represents a development of a range finder sensor module for indoor 2-D mapping and modified Hough transformation for map building. A range finder sensor module has been developed by using optic PSD (Position Sensitive Detector) sensor array at a low price. While PSD sensor is cost effective and light weighting, it has switching noise and white noise. To remove these noises, we propose a heuristic filter. For line-based map building, also we proposed advanced Hough transformation and navigation algorithm. Some experiments were illustrated for the validity of the developed system.

• 제어로봇시스템학회논문지
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• 제17권2호
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• pp.102-107
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• 2011

In this paper we present cooperation of heterogeneous robot team, composed of a wheeled robot and a helicopter for localization and map building. This heterogeneous robot team can successfully fulfill task by combining the abilities of both robots than single robot because wheeled robot and helicopter have complementing ability. The scenario describes a tightly cooperative task, where the wheeled robot move carrying the helicopter and detect obstacles, if there are obstacles, helicopter take off for map building and land, then robot team move destination avoiding obstacles. We present PID controller for position control of helicopter and transformation algorithm to global coordinate from image pixel coordinate. Experimental result show that the proposed method is valid.

• Journal of Advanced Marine Engineering and Technology
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• 제32권1호
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• pp.184-191
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• 2008

In order for a mobile robot to move under unknown or uncertain environment, it must have an environmental information. In collecting environmental information, the mobile robot can use various sensors. In case of using ultrasonic sensors to collect an environmental information, it is able to comprise a low-cost environmental recognition system compared with using other sensors such as vision and laser range-finder. This paper proposes a map building algorithm which can collect environmental information using ultrasonic sensors. And also this paper suggests a traveling algorithm using environmental information which leads to the map building algorithm. In order to accomplish the proposed traveling algorithm, this paper additionally discusses a position revision algorithm.

• Journal of information and communication convergence engineering
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• 제7권3호
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• pp.281-285
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• 2009

Mobile robot has various sensors for describing the external world. The ultrasonic sensor widely applied to the most mobile robot to detect the obstacle and environment owing to low cost, its easy to use. However, ultrasonic sensor has major problems: the uncertainty information of sensor, false readings caused by specular reflection, multi path effect, low angular resolution and sensitivity to changes in temperature and humidity. This paper describes a sensor system for map building of mobile robot. It was made of low cost PSD (Position Sensitive Detector) sensor array and high speed RISC MPU. PSD sensor is cost effective and light weighting but its output signal has many noises. We propose heuristic S/W filter to effectively remove these noises. The developed map building sensor system was equipped on a mobile robot and was compared with ultrasonic sensor through field test.

• 융합신호처리학회논문지
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• 제5권4호
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• pp.256-262
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• 2004

로봇이 자율주행을 하는데 있어 중요한 요소는 로봇 스스로 위치를 추정하고 동시에 주위 환경에 대한 지도를 작성하는 것이다. 본 논문에서는 어안렌즈를 이용한 비전 기반 위치 추정 및 매핑 알고리즘을 제안한다. 로봇에 어안렌즈가 부착된 카메라를 천정을 바라볼 수 있도록 부착하여 스케일 불변 특징을 갖는 고급의 영상 특징을 구하고, 이 특징들을 맵 빌딩과 위치 추정에 이용하였다. 전처리 과정으로 어안렌즈를 통해 입력된 영상을 카메라 보정을 행하여 축방향 왜곡을 제거하고 레이블링과 컨벡스헐을 이용하여 보정된 영상에서 천정영역과 벽영역으로 분할한다. 최초 맵 빌딩시에는 분할된 영역에 대해 특징점을 구하고 맵 데이터베이스에 저장한다. 맵 빌딩이 종료될 때까지 연속하여 입력되는 영상에 대해 특징점들을 구하고 맵과 매칭되는 점들을 찾고 매칭되지 않은 점들에 대해서는 기존의 맵에 추가하는 과정을 반복한다. 위치 추정은 맵 빌딩 과정과 맵 상에서 로봇의 위치를 찾는데 이용된다. 로봇의 위치에서 구해진 특징점들은 로봇의 실제 위치를 추정하기 위해 기존의 맵과 매칭을 행하고 동시에 기존의 맵 데이터베이스는 갱신된다. 제안한 방법을 적용하면 50㎡의 영역에 대한 맵 빌딩 소요 시간은 2분 이내, 위치 추정시 위치 정확도는 ±13cm, 로봇의 자세에 대한 각도 오차는 ±3도이다.

• 로봇학회논문지
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• 제4권3호
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• pp.169-176
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• 2009

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.

• 전기전자학회논문지
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• 제9권1호
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• pp.7-18
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• 2005

로봇이 자율주행을 하는데 있어 중요한 요소는 로봇 스스로 위치를 추정하고 동시에 주위 환경에 대한 지도를 작성하는 것이다 본 논문에서는 스케일 불변 특정을 이용한 비전 기반 위치 추정 및 매핑 알고리즘을 제안한다. 로봇에 어안렌즈가 부착된 카메라를 천정을 바라볼 수 있도록 부착하여 스케일 불변 특정을 갖는 고급의 영상 특정을 구하여 맹 빌딩과 위치 추정을 수행한다. 먼저, 전처리 과정으로 어안렌즈를 통해 입력된 영상을 카메라 보정을 행하여 축방향 왜곡을 제거하고 레이블링과 컨벡스헐을 적용하여 천정영역과 벽영역으로 분할한다 최초 맵 빌딩시에는 분할된 영역에 대해 특정점을 구하고 맵 데이터베이스에 저장한다. 맵 빌딩이 종료될 때까지 연속하여 입력되는 영상에 대해 특정점들을 구하고 이미 작성된 맵과 매칭되는 점들을 찾고 매칭되지 않은 점들에 대해서는 기존의 맴에 추가하는 과정을 반복한다. 위치 추정은 맵 빌딩과정에서 매칭되는 점들을 찾을 때 동시에 수행되어 진다. 그리고 임의의 위치에서 기존의 작성된 맵과 매칭되는 점들을 찾음으로서 위치 추정이 행해지며 동시에 기존의 맵 데이터베이스의 특정점들을 갱신하게 된다. 제안한 방법은 $50m^2$의 영역에 대해 맵 빌딩을 2 분내에 수행할 수 있었으며, 위치의 정확도는 ${\pm}13cm$, 위치에 대한 로봇의 자세(각도)는 ${\pm}3$도의 오차를 갖는다.