- Title
- Agoraphilic navigation algorithm in dynamic environment with obstacles motion tracking and prediction
- Creator
- Hewawasam, Hasitha; Ibrahim, Yousef; Kahandawa, Gayan; Choudhury, Tanveer
- Date
- 2022
- Type
- Text; Journal article
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/184751
- Identifier
- vital:16569
- Identifier
-
https://doi.org/10.1017/S0263574721000588
- Identifier
- ISBN:0263-5747 (ISSN)
- Abstract
- This paper presents a new algorithm to navigate robots in dynamically cluttered environments. The proposed algorithm uses basic concepts of space attraction (hence the term Agoraphilic) to navigate robots through dynamic obstacles. The new algorithm in this paper is an advanced development of the original Agoraphilic navigation algorithm that was only able to navigate robots in static environments. The Agoraphilic algorithm does not look for obstacles (problems) to avoid but rather for a free space (solutions) to follow. Therefore, it is also described as an optimistic navigation algorithm. This algorithm uses only one attractive force created by the available free space. The free-space concept allows the Agoraphilic algorithm to overcome inherited challenges of general navigation algorithms. However, the original Agoraphilic algorithm has the limitation in navigating robots only in static, not in dynamic environments. The presented algorithm was developed to address this limitation of the original Agoraphilic algorithm. The new algorithm uses a developed object tracking module to identify the time-varying free spaces by tracking moving obstacles. The capacity of the algorithm was further strengthened by the new prediction module. Future space prediction allowed the algorithm to make decisions considering future growing/diminishing free spaces. This paper also includes a bench-marking study of the new algorithm compared with a recently published APF-based algorithm under a similar operating environment. Furthermore, the algorithm was validated based on experimental tests and simulation tests. © 2022 Cambridge University Press. All rights reserved.
- Publisher
- Cambridge University Press
- Relation
- Robotica Vol. 40, no. 2 (2022), p. 329-347
- Rights
- All metadata describing materials held in, or linked to, the repository is freely available under a CC0 licence
- Rights
- Copyright © 2022 Cambridge University Press.
- Subject
- 4007 Control engineering, mechatronics and robotics; 4009 Electronics, sensors and digital hardware; 4002 Automotive engineering; Agoraphilic algorithm; Artificial potential field; Mobile robot navigation; Moving obstacles; Object tracking; Path planning
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