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
- 학위논문
- 저자정보
- 지도교수
- 박찬식
- 발행연도
- 2016
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이 논문의 연구 히스토리 (3)
2016
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초록· 키워드
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In this paper, a novel reactive navigation method using the Expanded Guide Circle based Multi Guide Circle and selective entry driving is designed and applied to the autonomous mobile robot. The Expanded Guide Circle Method was proposed as a guidance navigation method for mproving the e?ciency of the remote operation using the sensory information. There has been di?culty in applying the expanded Guide Circle to the autonomous driving.
To solve it, the robot motions avoiding obstacles in a 2D plane are analyzed in two motions: avoiding motion or entering motion. And the reactive navgation method with two motions is devised. The real-time local obstacle avoidance method called the Expanded Guide Circle based Multi Guide Circle and Selective Entry Driving is developed to perceive the local environment through the segmented scan data, select a suitable gap by applying a decision process, geometrically compute a safe control command to the direction of the center of a selected gap or the direction of a global goal. This method solves local obstacle avoidance problems by combining the Expanded Guide Circle and the Selectvie Entry Driving.
The proposed method is tested in simulations and experimental tests are performed in environments where single and multi obstacles are. The experimental test platform is a di?erential-type robot. Experimental results show that the tast of obstacle avoidance can be achiedved using the algorithm on the autonomous vehicle platform and verify the validity and the e?ectiveness of the proposed method.
To solve it, the robot motions avoiding obstacles in a 2D plane are analyzed in two motions: avoiding motion or entering motion. And the reactive navgation method with two motions is devised. The real-time local obstacle avoidance method called the Expanded Guide Circle based Multi Guide Circle and Selective Entry Driving is developed to perceive the local environment through the segmented scan data, select a suitable gap by applying a decision process, geometrically compute a safe control command to the direction of the center of a selected gap or the direction of a global goal. This method solves local obstacle avoidance problems by combining the Expanded Guide Circle and the Selectvie Entry Driving.
The proposed method is tested in simulations and experimental tests are performed in environments where single and multi obstacles are. The experimental test platform is a di?erential-type robot. Experimental results show that the tast of obstacle avoidance can be achiedved using the algorithm on the autonomous vehicle platform and verify the validity and the e?ectiveness of the proposed method.
목차
I. 서론 11.1 연구 배경 11.2 관련 연구 51.2.1 Expanded Guide Circle(EGC) 51.2.2 Follow the Gap Method(FGM) 121.2.3 Laser Range 데이터를 이용한 장애물 추출 16II. 수정된 확장 가이드 서클 방법 222.1 확장 가이드 서클을 자율주행에 적용 시 발생하는 문제 232.2 수정된 확장 가이드 서클 알고리즘 26III. 선택적 진입 주행 알고리즘 383.1 LRF 센서의 스캔 데이터 분할 및 간격 정의 403.2 안전하게 진입 가능한 간격 판단 기준 413.3 목적지로 보다 빠르게 수렴하기 위한 간격 판단 기준 43IV. 실험 결과 524.1 시뮬레이션을 통한 타 알고리즘과의 비교 544.2 장애물이 혼재된 실내 환경에서의 로봇 구동 실험 69V. 결론 72참고문헌 73
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