Abstract
This paper introduces a new multi-objective optimization approach in the field of terrain coverage. With the help of the multi-objective online terrain coverage model, a decentralized autonomous swarm is able to cover an unknown environment. This innovative terrain coverage model has a high impact on autonomous vehicle applications because it considers conflicting objective functions during the coverage process. This important improvement opens up new possibilities for real world applications. The design methodology is based on combining an auction based algorithm with a multiple ant colony optimization route planning algorithm. Experimental analysis is performed on the presented online terrain coverage model which includes the multi-objective route optimization and also a single-objective route optimization. The analysis shows that a multi-objective approach can reduce the repeated coverage and therefore the total coverage time.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Alaya, I., Solnon, C., Ghedira, K. (2007). Ant colony optimization for multi-objective optimization problems. In Proceedings of the 19th ICTAI, 450–457.
Dorigo, M. (1992). Optimization, learning and natural algorithms. Ph.D. thesis, Politecnico di Milano, Italy.
Kumar, V., Rus, D., & Singh, S. (2004). Robot and sensor networks for first responders. IEEE Pervasive Computing, 3(4), 24–33.
Lim, J., & Choo, D. (1998). Sonar based systematic exploration method for an autonomous mobile robot operating in an unknown environment. Robotica, 16(6), 659–667.
Pirzadeh, A., & Snyder, W. (1990). A unified solution to coverage and search in explored and unexplored terrains using indirect control. In ICRA (Vol. 3, pp. 2113–2119).
Preuß, M. (2011). Terrain coverage: Modelle und Algorithmen. Master’s thesis, University of the German Federal Armed Forces, Munich.
Sariel, S., Balch, T., & Erdogan, N. (2008). Naval mine countermeasure missions. IEEE RAM, 15(1), 45–52.
van Evert, F., van der Heijden, G., Lotz, L., Polder, G., Lamaker, A., de Jong, A., et al. (2006). A mobile field robot with vision-based detection of volunteer potato plants in a corn crop. Weed Technology, 20(4), 853–861.
Zheng, X., Koenig, S., Kempe, D., & Jain, S. (2010). Multirobot forest coverage for weighted and unweighted terrain. IEEE T-RO, 26, 1018–1031.
Zlot, R., Stentz, A., Dias, M., & Thayer, S. (2002). Multi-robot exploration controlled by a market economy. IEEE ICRA, 3, 3016–3023.
Acknowledgments
The author would like to thank Silja Meyer-Nieberg and Stefan Pickl for many valuable discussions and comments on this paper.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this paper
Cite this paper
Preuß, M. (2014). A Multi-Objective Online Terrain Coverage Approach. In: Huisman, D., Louwerse, I., Wagelmans, A. (eds) Operations Research Proceedings 2013. Operations Research Proceedings. Springer, Cham. https://doi.org/10.1007/978-3-319-07001-8_47
Download citation
DOI: https://doi.org/10.1007/978-3-319-07001-8_47
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-07000-1
Online ISBN: 978-3-319-07001-8
eBook Packages: Business and EconomicsBusiness and Management (R0)