Szczegóły publikacji
Opis bibliograficzny
Enhanced point cloud integration with time-separated LiDAR scans from a quadruped robot / Joanna KOSZYK, Bartosz HYLA, Łukasz AMBROZIŃSKI // W: MMAR 2025 [Dokument elektroniczny] : 29th international conference on Methods and Models in Automation and Robotics : 26–29 August 2025, Międzyzdroje, Poland : technical papers : on line proceedings. — Wersja do Windows. — Dane tekstowe. — Piscataway : IEEE, cop. 2025. — ( International Conference on Methods and Models in Automation and Robotics ; ISSN 2835-2815 ). — USB ISBN: 979-8-3315-2648-1. — Print on Demand(PoD) ISBN: 979-8-3315-2650-4. — e-ISBN: 979-8-3315-2649-8. — S. 89–93. — Wymagania systemowe: Adobe Reader. — Bibliogr. s. 92–93, Abstr. — Publikacja dostępna online od: 2025-09-15
Autorzy (3)
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 162282 |
|---|---|
| Data dodania do BaDAP | 2025-09-11 |
| Tekst źródłowy | URL |
| DOI | 10.1109/MMAR65820.2025.11151009 |
| Rok publikacji | 2025 |
| Typ publikacji | materiały konferencyjne (aut.) |
| Otwarty dostęp |  |
| Wydawca | Institute of Electrical and Electronics Engineers (IEEE) |
| Konferencja | International Conference on Methods and Models in Automation and Robotics 2025 |
| Czasopismo/seria | International Conference on Methods and Models in Automation and Robotics |
Abstract
Comprehensive 3D representation of the environment is significant in various applications, including robotic navigation and structural monitoring. Data collection through stationary scanners of large-scale scenes can be timeconsuming, thus, mobile platforms can facilitate scanning process. In dynamic environments, features might change throughout the day. Additionally, mobile scanners are prone to mapping errors. In this paper, we introduce a time-separated point cloud fusion algorithm to enhance point cloud integration. Point clouds are collected at different points in the day with use of a walking mobile platform. The measurements from evening and morning are fused and further integrated with a historical point cloud through semantic segmentationbased algorithm.
