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Agoraphilic navigation algorithm in dynamic environment with obstacles motion tracking and prediction

Published online by Cambridge University Press:  28 May 2021

H. S. Hewawasam Open the ORCID record for H. S. Hewawasam [Opens in a new window] ,
M. Yousef Ibrahim ,
Gayan Kahandawa  and
T. A. Choudhury
H. S. Hewawasam*
Affiliation:
School of Science, Engineering and Information Technology, Federation University Australia, Gippsland, Australia
M. Yousef Ibrahim
Affiliation:
School of Science, Engineering and Information Technology, Federation University Australia, Gippsland, Australia
Gayan Kahandawa
Affiliation:
School of Science, Engineering and Information Technology, Federation University Australia, Gippsland, Australia
T. A. Choudhury
Affiliation:
School of Science, Engineering and Information Technology, Federation University Australia, Gippsland, Australia
*
*Corresponding author. Email: h.hewawasam@federation.edu.au
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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.

Keywords

agoraphilic algorithmpath planningobject trackingmobile robot navigationartificial potential fieldmoving obstacles
Type
Article
Information
Robotica , Volume 40 , Issue 2 , February 2022 , pp. 329 - 347
Copyright
© The Author(s), 2021. Published by Cambridge University Press

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