- Title
- A depth-based hybrid approach for safe flight corridor generation in memoryless planning
- Creator
- Nguyen, Thai; Murshed, Mamzur; Choudhury, Tanveer; Keogh, Kathleen; Kahandawa Appuhamillage, Gayan; Nguyen, Linh
- Date
- 2023
- Type
- Text; Journal article
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/197234
- Identifier
- vital:18826
- Identifier
-
https://doi.org/10.3390/s23167206
- Identifier
- ISSN:1424-8220 (ISSN)
- Abstract
- This paper presents a depth-based hybrid method to generate safe flight corridors for a memoryless local navigation planner. It is first proposed to use raw depth images as inputs in the learning-based object-detection engine with no requirement for map fusion. We then employ an object-detection network to directly predict the base of polyhedral safe corridors in a new raw depth image. Furthermore, we apply a verification procedure to eliminate any false predictions so that the resulting collision-free corridors are guaranteed. More importantly, the proposed mechanism helps produce separate safe corridors with minimal overlap that are suitable to be used as space boundaries for path planning. The average intersection of union (IoU) of corridors obtained by the proposed algorithm is less than 2%. To evaluate the effectiveness of our method, we incorporated it into a memoryless planner with a straight-line path-planning algorithm. We then tested the entire system in both synthetic and real-world obstacle-dense environments. The obtained results with very high success rates demonstrate that the proposed approach is highly capable of producing safe corridors for memoryless local planning. © 2023 by the authors.
- Publisher
- Multidisciplinary Digital Publishing Institute (MDPI)
- Relation
- Sensors Vol. 23, no. 16 (2023), p.
- Rights
- All metadata describing materials held in, or linked to, the repository is freely available under a CC0 licence
- Rights
- https:// creativecommons.org/licenses/by/ 4.0/
- Rights
- Copyright © 2023 by the authors
- Rights
- Open Access
- Subject
- 4008 Electrical engineering; 4009 Electronics, sensors and digital hardware; 4606 Distributed computing and systems software; Depth sensing; Drones; Memoryless planning; Safe flight corridor; UAV
- Full Text
- Reviewed
- Funder
- This research was supported by an Australian Government Research Training Program (RTP) Scholarship.
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