다중 LiDAR 기반 조류 충돌 방지 분산 협업 대응 시스템

서영욱¹ ; 이병하¹ ; 왕세영¹ ; 조태현¹ ; 고기성²^{, *}

1청주대학교 항공기계공학과 학부생
2청주대학교 항공기계공학과 조교수

Multi-LiDAR-Based Distributed Collaborative Response System for Bird Strike Prevention

Yeonguk Seo¹ ; Byeongha Lee¹ ; Seyeong Wang¹ ; Taehyun Cho¹ ; Gisung Ko²^{, *}

1Undergraduate student researcher, Department of Aerospace and Mechanical Engineering, Cheongju University
2Assistant professor, Department of Aerospace and Mechanical Engineering, Cheongju University

Correspondence to: *Gisung Ko 298, Daeseong-ro, Cheongwon-gu, Cheongju-si, 28503, Republic of Korea Tel: +82-43-229-7842 E-mail: kogilove03@cju.ac.kr

초록

본 연구에서는 조류 충돌 예방을 위해 다중 라이다·짐벌 카메라·순찰 로봇을 연동한 분산 협업 조류 탐지·대응 시스템을 제안하고 가상환경(Gazebo)에서 검증하였다. 라이다 융합 기반 DBSCAN·칼만필터로 조류를 탐지·추적하고 비전으로 재확인하였으며, 추격 제어기로 PN(비례항법유도)·pure pursuit·슬라이딩 모드 제어(SMC)를 비교하였다. 그 결과 SMC가 거리·조향 부드러움·재현성에서 우수해 최종 채택되었고, 실주행 궤적으로 근접 추격 유지를 확인하였다.

Abstract

This paper proposes a distributed collaborative bird detection and response system integrating multiple LiDARs, a gimbal camera, and a patrol robot, validated in Gazebo. LiDAR-fused DBSCAN clustering and a Kalman filter detect and track birds, as confirmed visually via a gimbal camera. Proportional navigation, pure pursuit, and sliding mode control (SMC) were compared as pursuit controllers, and SMC was adopted for its superior distance, smoothness, and repeatability, with RViz2 trajectories confirming close pursuit.

Keywords:

Bird Strike Prevention, Multi-LiDAR Fusion, Object Tracking, Sliding Mode Control, DBSCAN Clustering

키워드:

조류 충돌 방지, 다중 라이다 융합, 객체 추적, 슬라이딩 모드 제어, DBSCAN 클러스터링

Acknowledgments

이 논문은 2026년도 한국해군과학기술학회 하계학술대회 발표 논문임.

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