INDOOR MAPPING: EXPERIENCES WITH LIDAR SLAM


Creative Commons License

Suleymanoglu B., Soycan M., Toth C.

24th ISPRS Congress on Imaging Today, Foreseeing Tomorrow, Nice, Fransa, 6 - 11 Haziran 2022, cilt.43-B1, ss.279-285 identifier identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Cilt numarası: 43-B1
  • Doi Numarası: 10.5194/isprs-archives-xliii-b1-2022-279-2022
  • Basıldığı Şehir: Nice
  • Basıldığı Ülke: Fransa
  • Sayfa Sayıları: ss.279-285
  • Anahtar Kelimeler: Indoor Mapping, UGV, LiDAR, SLAM, Sensor Fusion, SIMULTANEOUS LOCALIZATION
  • Yıldız Teknik Üniversitesi Adresli: Evet

Özet

Indoor mapping is gaining more interest in both research as well as in emerging applications. Building information systems (BIM) and indoor navigation are probably the driving force behind this trend. For accurate mapping, the platform trajectory reconstruction, or in other words sensor orientation, is essential to reduce or even eliminate for extensive ground control. Simultaneous localization and mapping (SLAM) is the computation problem of how to simultaneously estimate the platform/sensor trajectory while reconstructing the object space; usually, a real-time operation is assumed. Here we investigate the performance of two LiDAR SLAM tools based on using indoor data, acquired by a remotely controlled robot sensor platform. All comparisons were performed on similar datasets using appropriate metrics and encouraging results were obtained as a consequence of initial test studies yet further research is needed to analyse these tools and their accuracy comprehensively