A Swarm Robotic Exploration Strategy Based on an Improved Random Walk Method
An environment can be searched far more efficiently if the appropriate search strategy is used. Because of the limited individual abilities of swarm robots, namely, local sensing and low processing power, random searching is the main search strategy used in swarm robotics. The random walk methods th...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2019-01-01
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| Series: | Journal of Robotics |
| Online Access: | http://dx.doi.org/10.1155/2019/6914212 |
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| _version_ | 1832562772115718144 |
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| author | Bao Pang Yong Song Chengjin Zhang Hongling Wang Runtao Yang |
| author_facet | Bao Pang Yong Song Chengjin Zhang Hongling Wang Runtao Yang |
| author_sort | Bao Pang |
| collection | DOAJ |
| description | An environment can be searched far more efficiently if the appropriate search strategy is used. Because of the limited individual abilities of swarm robots, namely, local sensing and low processing power, random searching is the main search strategy used in swarm robotics. The random walk methods that are used most commonly are Brownian motion and Lévy flight, both of which mimic the self-organized behavior of social insects. However, both methods are somewhat limited when applied to swarm robotics, where having the robots search repeatedly can result in highly inefficient searching. Therefore, by analyzing the characteristics of swarm robotic exploration, this paper proposes an improved random walk method in which each robot adjusts its step size adaptively to reduce the number of repeated searches by estimating the density of robots in the environment. Simulation experiments and experiments with actual robots are conducted to study the effectiveness of the proposed method and evaluate its performance in an exploration mission. The experimental results presented in this paper show that an area is covered more efficiently using the proposed method than it is using either Brownian motion or Lévy flight. |
| format | Article |
| id | doaj-art-d6be98fb135b405c9bf6b9f49353d0c2 |
| institution | Kabale University |
| issn | 1687-9600 1687-9619 |
| language | English |
| publishDate | 2019-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Robotics |
| spelling | doaj-art-d6be98fb135b405c9bf6b9f49353d0c22025-02-03T01:21:55ZengWileyJournal of Robotics1687-96001687-96192019-01-01201910.1155/2019/69142126914212A Swarm Robotic Exploration Strategy Based on an Improved Random Walk MethodBao Pang0Yong Song1Chengjin Zhang2Hongling Wang3Runtao Yang4School of Control Science and Engineering, Shandong University, Jinan 250061, ChinaSchool of Mechanical, Electrical and Information Engineering, Shandong University at Weihai, Weihai 264209, ChinaSchool of Control Science and Engineering, Shandong University, Jinan 250061, ChinaSchool of Control Science and Engineering, Shandong University, Jinan 250061, ChinaSchool of Mechanical, Electrical and Information Engineering, Shandong University at Weihai, Weihai 264209, ChinaAn environment can be searched far more efficiently if the appropriate search strategy is used. Because of the limited individual abilities of swarm robots, namely, local sensing and low processing power, random searching is the main search strategy used in swarm robotics. The random walk methods that are used most commonly are Brownian motion and Lévy flight, both of which mimic the self-organized behavior of social insects. However, both methods are somewhat limited when applied to swarm robotics, where having the robots search repeatedly can result in highly inefficient searching. Therefore, by analyzing the characteristics of swarm robotic exploration, this paper proposes an improved random walk method in which each robot adjusts its step size adaptively to reduce the number of repeated searches by estimating the density of robots in the environment. Simulation experiments and experiments with actual robots are conducted to study the effectiveness of the proposed method and evaluate its performance in an exploration mission. The experimental results presented in this paper show that an area is covered more efficiently using the proposed method than it is using either Brownian motion or Lévy flight.http://dx.doi.org/10.1155/2019/6914212 |
| spellingShingle | Bao Pang Yong Song Chengjin Zhang Hongling Wang Runtao Yang A Swarm Robotic Exploration Strategy Based on an Improved Random Walk Method Journal of Robotics |
| title | A Swarm Robotic Exploration Strategy Based on an Improved Random Walk Method |
| title_full | A Swarm Robotic Exploration Strategy Based on an Improved Random Walk Method |
| title_fullStr | A Swarm Robotic Exploration Strategy Based on an Improved Random Walk Method |
| title_full_unstemmed | A Swarm Robotic Exploration Strategy Based on an Improved Random Walk Method |
| title_short | A Swarm Robotic Exploration Strategy Based on an Improved Random Walk Method |
| title_sort | swarm robotic exploration strategy based on an improved random walk method |
| url | http://dx.doi.org/10.1155/2019/6914212 |
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