Refine
Year of publication
- 2024 (8)
- 2023 (25)
- 2022 (15)
- 2021 (24)
- 2020 (33)
- 2019 (44)
- 2018 (24)
- 2017 (33)
- 2016 (28)
- 2015 (32)
- 2014 (13)
- 2013 (26)
- 2012 (13)
- 2011 (23)
- 2010 (24)
- 2009 (24)
- 2008 (19)
- 2007 (31)
- 2006 (32)
- 2005 (41)
- 2004 (23)
- 2003 (21)
- 2002 (23)
- 2001 (23)
- 2000 (18)
- 1999 (18)
- 1998 (16)
- 1997 (16)
- 1996 (8)
- 1995 (10)
- 1994 (12)
- 1993 (9)
- 1992 (10)
- 1991 (8)
- 1990 (15)
- 1989 (9)
- 1988 (9)
- 1987 (7)
- 1986 (1)
- 1985 (10)
- 1984 (6)
- 1983 (8)
- 1982 (3)
- 1979 (1)
- 1978 (1)
- 1977 (2)
Institute
- Fachbereich Luft- und Raumfahrttechnik (799) (remove)
Document Type
- Article (375)
- Conference Proceeding (213)
- Book (107)
- Part of a Book (43)
- Patent (19)
- Report (14)
- Doctoral Thesis (10)
- Conference: Meeting Abstract (7)
- Other (3)
- Conference Poster (2)
Keywords
- Karosseriebau (6)
- Strömungsmaschine (6)
- Turbine (6)
- avalanche (6)
- solar sail (5)
- car body construction (4)
- hydrogen (4)
- snow (4)
- Eisschicht (3)
- GOSSAMER-1 (3)
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.