Safety Net Detection by Optic Flow Processing
| Autor: | Daini, Xavier, Coquet, Charles, Raffin, Romain, Raharijaona, Thibaut, Ruffier, Franck |
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| Přispěvatelé: | Institut des Sciences du Mouvement Etienne Jules Marey (ISM), Aix Marseille Université (AMU)-Centre National de la Recherche Scientifique (CNRS), Laboratoire d'Informatique de Bourgogne [Dijon] (LIB), Université de Bourgogne (UB), Laboratoire de Conception Fabrication Commande (LCFC), Université de Lorraine (UL)-Arts et Métiers Sciences et Technologies, HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM), AID, Kimon Valavanis, Anna Konert, YangQuan Chen, Andrea Monteriù |
| Jazyk: | angličtina |
| Rok vydání: | 2023 |
| Předmět: | |
| Zdroj: | Proceeding of IEEE The 2023 Int´l Conference on Unmanned Aircraft Systems The 2023 Int´l Conference on Unmanned Aircraft Systems, Kimon Valavanis; Anna Konert; YangQuan Chen; Andrea Monteriù, Jun 2023, Warsaw, France. pp.32-39, ⟨10.1109/ICUAS57906.2023.10156597⟩ |
| Popis: | International audience; Drone navigation is an area of study that is receiving more and more attention. Obstacle detection techniques and autonomous guidance are continuously improving, but some types of obstacles are still very difficult to detect with current methods. Safety nets used to separate and secure 2 contiguous spaces are indeed very difficult to detect by Lidar and by image processing based on pattern recognition. The method we propose here separates the Optical Flow detections to identify the presence of a safety net: i) by using the norm of their vector, ii) by matching them to a regression defining a plane (safety net or wall). Our results show that the proposed method detects a net in front of a wall with very few false positives, thanks to a small displacement (at most 5%). Moreover, the distance estimation between the net and the wall as well as the distance between the net and the drone can be estimated with at most 20% error in the worst cases. |
| Databáze: | OpenAIRE |
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