인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
DBpia AI
AI 에이전트
AI 아이디어
AI 리더
AI 뷰어
Citeasy
크롬 서지관리 다운로드
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.
학술저널
Full-text XML
오류 신고하기해당 페이지 내 제목·저자·목차·페이지정보가 잘못된 경우 알려주세요!
피인용 0
초록·키워드
In swarm control research, the two most important issues are collision avoidance among moving objects and vehicle-to-vehicle communication (V2V communication). Leader-Follower method, the commonly used in swarm control, has problems about these two function. Data loss in communication or a failure of the leader can cause the entire formation to become uncontrollable. To resolve this problem, this paper suggests the variable Leader-Follower method and collision avoidance process based on the Velocity Obstacle method. Instead of fixing a leader, it selects the leader using an allocation algorithm based on the navigation situation. Also, each ship except the leader, in the swarm choose new ideal point using formation matrix that contains the distance from each ship to ideal points. To avoid static and dynamic obstacles, each ships in the swarm make local path using Velocity Obstacle method(VO) with Quadrangle Ship Domain (QSD). If there is no collision risk, they follow the global path; Otherwise, they plans the local path that can avoid collisions with other vessels and obstacles. To validate the algorithm proposed in this paper, navigation simulations are conducted in the simulation environment based on a MMG type manoeuvring model. It is confirmed that the follower can maintain their formation by formation control and appropriate leader was selected based on the current situation by path following control. The collision avoidance simulation with static, dynamic and complex obstacles ensured that the vessels in the swarm can avoid the collision and they can find the optimum formation.
본문·목차
인공지능 문자 인식 모델을 통해 추출된 텍스트로, 일부 오타나 오류가 포함될 수 있으나 지속적으로 개선 중입니다.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
최근 본 자료 전체보기
UCI(KEPA) : I410-151-25-02-092728472
