주행로봇을 위한 접촉식 센서 기반의 지질 특성 추출 및 지질 분류

다국어 초록 (Multilingual Abstract)

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 (Table of Contents)

• 1. 서 론 1
• 2. 접촉식 센서 데이터의 수집 및 분석 4
• 1) 접촉식 센서 데이터를 수집하는 로봇 시스템 설계 4
• 2) 실험 지질 선정 5
• 3) 지질별 수집 데이터 분석 6
• 3. 지질 특성정보 추출 10
• 1) 피크분산을 이용한 지질 특성정보 추출 방법 10
• 2) 센서별 지질 특성 추출결과 12
• 4. 신경망 알고리즘을 이용한 지질 특성 추출방법에 따른 지질 분류 성능비교 16
• 1) 고속 퓨리에 변환 특성정보를 이용한 지질 분류 16
• 2) 피크분산 특성정보를 이용한 지질 분류 18
• 3) 실시간성을 고려한 분류 효율성 비교 20
• 5. 결론 및 추후 연구 23
• 참고문헌 24
• Abstract 26