• Proceedings of the Korean Society of Precision Engineering Conference
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• 2008.06a
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• pp.291-292
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• 2008

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.7
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• pp.658-663
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• 2012

An accurate outdoor localization method using line/arc features is suggested for mobile robots with LRFs (Laser Range Finders) and odometry. Localization is a key process for outdoor mobile robots which are used for autonomous navigation, exploration and so on. In this paper, an accurate pose correction algorithm is proposed for mobile robots using LRFs, which use three feature types: line, circle, and arc. Using this method we can reduce the number of singular cases that robots couldn't find their pose. Finally we have got simulation results to validate the proposed algorithm.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.1817_1818
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• 2009

Disparity 맵은 스테레오 카메라의 이미지 평면에 동일한 3차원 포인터를 나타내는 픽셀간의 차이를 나타내는 이미지이다. 이는 3차원 정보를 얻기 위하여 생성 한며 생성된 Disparity 맵은 Triangulation을 이용하여 3차원 복원이 가능하다. Disparity 맵은 픽셀의 intensity의 차를 이용하여 구하므로 Repeated Pattern 이나 Textureless 부분에서 많은 에러가 생기는 문제가 있다. 본 논문에서는 이런 문제점을 해결하기 위하여 싱글 카메라와 레이저 레인지 파인더의 캘리브레이션을 통해 알아낸 기하학적인 관계를 이용하여 3차원 정보를 카메라의 이미지 평면으로 역 사영 시켜서 Disparity 맵을 생성하는 알고리즘을 제안한다. 이 방법은 기존의 스트레오 카메라 기반으로 Disparity 맵을 생성하는 경우에 생기는 Repeated Pattern 이나 Textureless 부분의 문제를 해결 할 수 있다는 것을 실험을 통하여 검증 하였다.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.2
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• pp.111-116
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• 2014

Using only laser range finder to detect the obstacles in an environment that contains transparent obstacles can not guarantee autonomous mobile robot from collision problem. To solve this problem, a mobile robot using laser range finder must be used additional sensor device such as sonar sensor that can detect the transparent obstacle. In this paper, a method is addressed to deal with the problem to detect the transparent obstacles within environment only by using laser range finder for mobile robot. In case the recognized transparent obstacle, the proposed algorithm is to localize the transparent obstacle to extract and process the reflected noise. This algorithm ensures autonomous of mobile robot only using laser range finder. The effectiveness of the proposed algorithm is evaluated by the real mobile robot and real laser range finder experiments with three case studies.

• Transactions of the Korean Society of Automotive Engineers
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• v.19 no.4
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• pp.8-15
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• 2011

This paper proposes a real-time navigation algorithm which integrates the artificial potential field (APF) for an unmanned vehicle in the unknown environment. This approach uses repulsive potential function around the obstacles to force the vehicle away and an attractive potential function around the goal to attract the vehicle. In this research, laser range finder is used as range sensor. An obstacle detected by the sensor creates repulsive vector. Differential global positioning system (DGPS) and digital compass are used to measure the current vehicle position and orientation. The measured vehicle position is also used to create attractive vector. This paper proposes a new concept of potential field based navigation which controls unmanned vehicle's speed and steering. The magnitude of repulsive force based on the proposed algorithm is designed not to be over the magnitude of attractive force while the magnitude is increased linearly as being closer to obstacle. Consequently, the vehicle experiences a generalized force toward the negative gradient of the total potential. This force drives the vehicle downhill towards its goal configuration until the vehicle reaches minimum potential and it stops. The effectiveness of the proposed APF for unmanned vehicle is verified through simulation and experiment.