A Physarum-Inspired Decision-Making Strategy for Multisource Task Searching of Mobile Robots
Joint Authors
Jiang, Laihao
Mo, Hongwei
Xu, Lifang
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-14, 14 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-09-21
Country of Publication
Egypt
No. of Pages
14
Main Subjects
Abstract EN
In the real world, there are many different kinds of sources, such as light, sound, and gas, distributed randomly over an area.
Source search can be carried out by robotic system in applications.
However, for a single robot, the multisource search has been receiving relatively little attention compared to single-source search.
For multisource task searching, a single robot has a high travel cost and is easy to trap a source which has been located before.
In order to overcome these shortages, two multisource search algorithms inspired by the foraging behavior of Physarum polycephalum are proposed in this paper.
First, a Physarum-inspired Strategy (PS) is designed based on the gradient climbing characteristic of Physarum polycephalum during foraging.
The PS is simple and effective to let a mobile robot traverse all sources.
Then, an extension algorithm named Physarum-inspired Decision-making Strategy (PDS) is proposed based on PS.
Therein the synthetical field gradient model is established by introducing decision-making factor to obtain more accurate gradient information estimation.
The PDS also introduces an obstacle avoidance model.
Various simulation results obtained in the multisource environments show that the performance of PDS is better than other algorithms.
American Psychological Association (APA)
Jiang, Laihao& Mo, Hongwei& Xu, Lifang. 2020. A Physarum-Inspired Decision-Making Strategy for Multisource Task Searching of Mobile Robots. Complexity،Vol. 2020, no. 2020, pp.1-14.
https://search.emarefa.net/detail/BIM-1141331
Modern Language Association (MLA)
Jiang, Laihao…[et al.]. A Physarum-Inspired Decision-Making Strategy for Multisource Task Searching of Mobile Robots. Complexity No. 2020 (2020), pp.1-14.
https://search.emarefa.net/detail/BIM-1141331
American Medical Association (AMA)
Jiang, Laihao& Mo, Hongwei& Xu, Lifang. A Physarum-Inspired Decision-Making Strategy for Multisource Task Searching of Mobile Robots. Complexity. 2020. Vol. 2020, no. 2020, pp.1-14.
https://search.emarefa.net/detail/BIM-1141331
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1141331