지도가 필요 없는 (Mapless) 자율 주행 기술은 수 많은 보행 약자들의 지속가능한 사회적 활동을 도울 수 있는 중요한 연구 주제이다. 대표적인 Mapless 주행 기술 중 하나인 Visual teach and Replay (이하 VTR)은 오프로드 환경에서의 성공적인 결과에도 불구하고, 우리의 보행로 환경 시험에서 장거리 주행 및 다중 teach 과정에서 속도 및 성능 저하가 관찰되었다. 우리는 이를 극복하고자, graph 맵 빌딩 및 경로 탐색 등을 최소화하는 경량의 VTR 파이프라인 새롭게 설계 중이다. 또한, 환경 변화에 강인한 딥 피쳐 기반의 탐색 기법을 도입함으로써 single teach만으로도 안정적인 replay가 가능한 시스템을 설계 중이다. 우리는 이 경량의 mapless 주행 기술을 “Lightweight Deep Feature-based Visual Teach and Replay” (이하, LDVTR) 라고 명명하고, 본 논문에서 처음으로 소개한다.
KSP Keywords
Feature-based, deep features
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