지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 발행연도
- 2012.9
- 수록면
- 171 - 181 (11page)
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초록· 키워드
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Outdoor mobile robots are faced with various terrain types having different characteristics. To run safely and carry out the mission, mobile robot should recognize terrain types, physical and geometric characteristics and so on. It is essential to control appropriate motion for each terrain characteristics. One way to determine the terrain types is to use non-contact sensor data such as vision and laser sensor. Another way is to use contact sensor data such as slope of body, vibration and current of motor that are reaction data from the ground to the tire. In this paper, we presented experimental results on terrain classification using contact sensor data. We made a mobile robot for collecting contact sensor data and collected data from four terrains we chose for experimental terrains. Through analysis of the collecting data, we suggested a new method of terrain feature extraction considering physical characteristics and confirmed that the proposed method can classify the four terrains that we chose for experimental terrains. We can also be confirmed that terrain feature extraction method using Fast Fourier Transform (FFT) typically used in previous studies and the proposed method have similar classification performance through back propagation learning algorithm. However, both methods differ in the amount of data including terrain feature information. So we defined an index determined by the amount of terrain feature information and classification error rate. And the index can evaluate classification efficiency. We compared the results of each method through the index. The comparison showed that our method is more efficient than the existing method.
목차
Abstract
1. 서론
2. 접촉식 센서 데이터의 수집 및 분석
3. 지질 특성정보 추출
4. 신경망 알고리즘을 이용한 지질 특성 추출 방법에 따른 지질 분류 성능비교
5. 결론
참고문헌
참고문헌 (14)
참고문헌 신청
1. [학술대회논문] - Liang Lu / 2009 / Terrain Surface Classification for Autonomous Ground Vehicles Using a 2D Laser Stripe‐Based Structured Light Sensor / IEEE/RSJ International Conference on Intelligent Robots and Systems
2. [학술대회논문] - Seung‐Youn Lee / 2011 / A Terrain Classification Method for UGV Autonomous Navigation Based on SURF / International Conference on Ubiquitous Robots and Ambient Intelligence(URAI)
3. [학술대회논문] - Peyman Moghadam / 2009 / Online, Self‐Supervised Vision‐Based Terrain Classification in Unstructured Environments / IEEE International Conference on Systems
5. [학술지(정기간행물)] - E. Ray / 2009 / Estimation of Terrain Forces and Parameters for Rigid‐Wheeled Vehicles / IEEE Transactions on Robotics
6. [학술지(정기간행물)] - Valentin Ivanov / 2009 / Fuzzy evaluation of tyre‐surface interaction parameters / Journal of Terramechanics
2. [학술대회논문] - Seung‐Youn Lee / 2011 / A Terrain Classification Method for UGV Autonomous Navigation Based on SURF / International Conference on Ubiquitous Robots and Ambient Intelligence(URAI)
3. [학술대회논문] - Peyman Moghadam / 2009 / Online, Self‐Supervised Vision‐Based Terrain Classification in Unstructured Environments / IEEE International Conference on Systems
5. [학술지(정기간행물)] - E. Ray / 2009 / Estimation of Terrain Forces and Parameters for Rigid‐Wheeled Vehicles / IEEE Transactions on Robotics
6. [학술지(정기간행물)] - Valentin Ivanov / 2009 / Fuzzy evaluation of tyre‐surface interaction parameters / Journal of Terramechanics
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UCI(KEPA) : I410-ECN-0101-2020-559-001258951