https://arxiv.org/pdf/1607.00470.pdf

로봇의 자율주행을 위해 필요한 기술

  • 지도 : SLAM기술 활용 자동 생성
  • 로봇 자세 계측/추정 기능 : GPS, IMU센서, 추측항법(Dead reckoning)
  • 벽, 물체등 장애물 계측 기능 : Lidar, Depth Camera
  • 최적 경로를 계산하고 주행 하는 기능 : A*알고리즘, 포텐셜 필드, 파티클 필드, RRT

SLAM 관련 ROS 패키지

  • gmapping
  • cartographer
  • rtabmap

A majority of SLAM systems share several common components:

  • feature detector that finds point of interest within the image (features),
  • feature descriptor that matches tracks features from one image to the next,
  • optimization backend that uses said correspondences to build a geometry of the scene (map) and find the position of the robot,
  • loop closure detection algorithm that recognizes previously visited areas and adds constraints to the map.
    • loop closure has the most potential to be solved with DL techniques.

출처 : How can Deep Learning help Robotics and SLAM


자율주행을 위한 Localization/VO/VSLAM 개념

results matching ""

    No results matching ""