Refine
Year of publication
- 2023 (237) (remove)
Document Type
- Bachelor Thesis (93)
- Article (68)
- Conference Proceeding (30)
- Part of a Book (22)
- Book (10)
- Master's Thesis (2)
- Patent (2)
- Preprint (2)
- Talk (2)
- Contribution to a Periodical (1)
- Habilitation (1)
- Other (1)
- Part of Periodical (1)
- Report (1)
- Administrative publication (1)
Keywords
- Corporate Design (6)
- Editorial (6)
- Illustration (6)
- Typografie (6)
- Nachhaltigkeit (5)
- Produktdesign (5)
- Fotografie (4)
- Publikation (4)
- Design (3)
- Erscheinungsbild (3)
- Information extraction (3)
- Kinder (3)
- Künstliche Intelligenz (3)
- Museum (3)
- Natural language processing (3)
- nachhaltig (3)
- Animation (2)
- Architektur (2)
- Associated liquids (2)
- Bacillaceae (2)
Institute
- Fachbereich Gestaltung (95)
- Fachbereich Medizintechnik und Technomathematik (38)
- Fachbereich Elektrotechnik und Informationstechnik (23)
- ECSM European Center for Sustainable Mobility (21)
- Fachbereich Luft- und Raumfahrttechnik (20)
- Fachbereich Wirtschaftswissenschaften (17)
- Fachbereich Chemie und Biotechnologie (14)
- Fachbereich Energietechnik (14)
- INB - Institut für Nano- und Biotechnologien (12)
- Fachbereich Maschinenbau und Mechatronik (10)
- IfB - Institut für Bioengineering (9)
- Nowum-Energy (7)
- MASKOR Institut für Mobile Autonome Systeme und Kognitive Robotik (6)
- Fachbereich Bauingenieurwesen (5)
- Kommission für Forschung und Entwicklung (3)
- Solar-Institut Jülich (3)
- FH Aachen (2)
- Fachbereich Architektur (2)
- Institut fuer Angewandte Polymerchemie (2)
- Arbeitsstelle fuer Hochschuldidaktik und Studienberatung (1)
This work proposes a hybrid algorithm combining an Artificial Neural Network (ANN) with a conventional local path planner to navigate UAVs efficiently in various unknown urban environments. The proposed method of a Hybrid Artificial Neural Network Avoidance System is called HANNAS. The ANN analyses a video stream and classifies the current environment. This information about the current Environment is used to set several control parameters of a conventional local path planner, the 3DVFH*. The local path planner then plans the path toward a specific goal point based on distance data from a depth camera. We trained and tested a state-of-the-art image segmentation algorithm, PP-LiteSeg. The proposed HANNAS method reaches a failure probability of 17%, which is less than half the failure probability of the baseline and around half the failure probability of an improved, bio-inspired version of the 3DVFH*. The proposed HANNAS method does not show any disadvantages regarding flight time or flight distance.