| Obstacle Classification for Mobile Robot Traversability using 2-dimensional Laser Scanning |
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Min-Hee Kim, Kyung-Woon Kwak, Soo-Hyun Kim |
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KAIST |
| 2차원 레이저 스캔을 이용한 로봇의 산악 주행 장애물 판단 |
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김민희, 곽경운, 김수현 |
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한국과학기술원 |
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| Abstract |
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Obstacle detection is much studied by using sensors such as laser, vision, radar and ultrasonic in path planning for UGV(Unmanned Ground Vehicle), but not much reported about its characterization. In this paper not only an obstacle classification method using 2-dimensional LMS(Laser Measurement System) but also a decision making method whether to avoid or traverse the obstacle is proposed. The basic idea of decision making is to classify the characteristics by 2D laser scanned data and intensity data. Roughness features are obtained by range data using a simple linear regression model. The standard deviations of roughness and intensity data are used as measures for decision making by comparing with those of reference data. The obstacle classification and decision making for the UGV can facilitate a short path to the target position and the survivability of the robot. |
| Key Words:
Traversability, Range Feature, Roughness, Intensity |
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