poster

Inverted ant colony optimization for search and rescue in an unknown maze-like indoor environment

Authors:

A. F. IsakovicAuthors Info & Claims

GECCO '18: Proceedings of the Genetic and Evolutionary Computation Conference Companion

Pages 89 - 90

https://doi.org/10.1145/3205651.3205738

Published: 06 July 2018 Publication History

Get Access

Abstract

We demonstrate the applicability of inverted Ant Colony Optimization (iACO) for target search in a complex unknown indoor environment simulated by a maze. The colony of autonomous ants lay repellent pheromones to speed up exploration of the unknown maze instead of reinforcing presence in already visited areas. The role of a target-collocated beacon signal within the maze is evaluated in terms of its utility to guide the search. Variants of iACO were developed, with beacon initialization (iACO-B), and with increased sensing ranges (iACO-R with a 2-step far-sightedness) to quantify the most effective one. The presented models can be implemented with self-organizing wireless sensor networks carried by autonomous drones or vehicles and can offer life-saving services of localizing victims of natural disasters or during major infrastructure failures.

References

[1]

L. Mainetti, L. Patrono, and A. Vilei. Evolution of Wireless Sensor Networks towards the Internet of Things: A survey. In Software, Telecommunications and Computer Networks (SoftCOM), 2011 19th International Conference on, pages 1--6. IEEE, 2011.

Google Scholar

[2]

Y. Li and L. Cai. UAV-assisted dynamic coverage in a heterogeneous cellular system. IEEE Network, 31(4):56--61, 2017.

Digital Library

Google Scholar

[3]

Yugang Liu and Goldie Nejat. Robotic urban search and rescue: A survey from the control perspective. Journal of Intelligent & Robotic Systems, 72(2):147--165, 2013.

Digital Library

Google Scholar

[4]

S. Tjiharjadi and E. Setiawan. Design and implementation of a path finding robot using Flood Fill algorithm.

Google Scholar

[5]

G. Rivera. Path planning for general mazes. Master's thesis, Missouri University of Science and Technology, 2012.

Google Scholar

[6]

F. Bounini, D. Gingras, H. Pollart, and D. Gruyer. Modified Artificial Potential Field method for online path planning applications. In Intelligent Vehicles Symposium (IV), 2017 IEEE, pages 180--185. IEEE, 2017.

Crossref

Google Scholar

[7]

J. A. Sauter, R. Matthews, H. V. D. Parunak, and S. A. Brueckner. Performance of digital pheromones for swarming vehicle control. In Proceedings of the Fourth International Joint Conference on Autonomous Agents and Multiagent Systems, pages 903--910. ACM, 2005.

Digital Library

Google Scholar

[8]

M. Ahuja. Fuzzy Counter Ant Algorithm for maze problem. Master's thesis, University of Cincinnati, 2010.

Google Scholar

[9]

J. Cao. Robot global path planning based on an Improved Ant Colony Algorithm. Journal of Computer and Communications, 4(02):11, 2016.

Crossref

Google Scholar

[10]

T. S. Rappaport et al. Wireless communications: principles and practice, volume 2. Prentice Hall PTR New Jersey, 1996.

Digital Library

Google Scholar

Cited By

View all

Tyagi NSingh JSingh S(2022)A Review of Routing Algorithms for Intelligent Route Planning and Path Optimization in Road NavigationRecent Trends in Product Design and Intelligent Manufacturing Systems10.1007/978-981-19-4606-6_78(851-860)Online publication date: 6-Oct-2022
https://doi.org/10.1007/978-981-19-4606-6_78

Index Terms

Inverted ant colony optimization for search and rescue in an unknown maze-like indoor environment
1. Computing methodologies
  1. Artificial intelligence

Recommendations

Ant colony optimization

Swarm intelligence is a relatively new approach to problem solving that takes inspiration from the social behaviors of insects and of other animals. In particular, ants have inspired a number of methods and techniques among which the most studied and ...
Particle swarm optimizer, ant colony strategy and harmony search scheme hybridized for optimization of truss structures

A heuristic particle swarm ant colony optimization (HPSACO) is presented for optimum design of trusses. The algorithm is based on the particle swarm optimizer with passive congregation (PSOPC), ant colony optimization and harmony search scheme. HPSACO ...
Study on Immunized Ant Colony Optimization
ICNC '07: Proceedings of the Third International Conference on Natural Computation - Volume 04

Ant Colony Optimization (ACO) is a new natural computation method from mimic the behaviors of ant colony.It is a very good combination optimization method. To extend the ant colony optimization, some continuous Ant Colony Optimizations have been ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

GECCO '18: Proceedings of the Genetic and Evolutionary Computation Conference Companion

July 2018

1968 pages

ISBN:9781450357647

DOI:10.1145/3205651

Editor:
Hernan Aguirre
Shinshu University
,
General Chair:
Keiki Takadama
The University of Electro-Communications

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 06 July 2018

Check for updates

Qualifiers

Poster

Funding Sources

UAE ICTFund

Conference

GECCO '18

Sponsor:

SIGEVO

GECCO '18: Genetic and Evolutionary Computation Conference

July 15 - 19, 2018

Kyoto, Japan

Acceptance Rates

Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

1
Total Citations
View Citations
94
Total Downloads

Downloads (Last 12 months)2
Downloads (Last 6 weeks)0

Reflects downloads up to 19 Dec 2024

Other Metrics

View Author Metrics

Citations

Cited By

View all

Tyagi NSingh JSingh S(2022)A Review of Routing Algorithms for Intelligent Route Planning and Path Optimization in Road NavigationRecent Trends in Product Design and Intelligent Manufacturing Systems10.1007/978-981-19-4606-6_78(851-860)Online publication date: 6-Oct-2022
https://doi.org/10.1007/978-981-19-4606-6_78

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Cited By

Index Terms

Recommendations

Ant colony optimization

Particle swarm optimizer, ant colony strategy and harmony search scheme hybridized for optimization of truss structures

Study on Immunized Ant Colony Optimization