Abstract
Autonomous robot deployment is very attracting feature especially inside unknown area. Virtual force (VF) technique appears as one of the prominent approaches to performing multirobot deployment autonomously. However, most of the existing VF-based approaches lack purposeful deployment. In this work, we present a Cooperative Virtual Force Robot Deployment (COVER) technique. Our approach modifies the original VF approach to overcome this problem and considers the mission requirements such as the number of required robots in each locality (e.g., landmarks are distributed, and each needs a specific number of robots in its vicinity). In addition, COVER expedites the deployment process by establishing a cooperative relation between robots and neighboring landmarks. Extensive simulation experiments have been carried out to assess the performance of COVER along with Hungarian deployment method (a centralized approach), the basic virtual force, and full virtual force. A proof of concept experiment using TurtleBot robots is presented as well to show real implementation of COVER. The simulation and experiment results demonstrate the effectiveness of COVER for several performance factors such as total traveled distance, total exchanged messages, and total deployment time.
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Abbreviations
- R, \(R_\mathrm{f}\),\(R_\mathrm{a}\) :
-
Robots, free robot, associated robots
- L :
-
Landmarks
- \(d({L}_{j} )\) :
-
Demand of landmark j
- \(N_{r} (R_i )\) :
-
Neighboring robots of robot \({R}_{i} \)
- \(N_{l} (R_i )\) :
-
Neighbor landmarks of robot \({R}_{i} \)
- \({w}_\mathrm{a}\) :
-
Attractive force
- \({w}_\mathrm{r}\) :
-
Repulsive force
- \({d}_{{ij}}\) :
-
Distance between robot \({R}_{i}\) and robot \({R}_{j} \)
- \({d}_{\mathrm{th}} \) :
-
Distance threshold between robots
- \({\Theta }_{{ij}}\) :
-
Angle between robot \({R}_{i} \) and robot \({R}_{j} \)
- \({c}_{\mathrm{th}}\) :
-
Maximum communication range
- \({F}_{{ij}}\) :
-
Force applied on robot \({R}_{i} \) from robot \({R}_{j} \)
- \({F}_{{ir}} \) :
-
Repulsive force applied on robot \({R}_{i}\) from a landmark
- \({F}_{i}\) :
-
The total force applied on robot i
References
Zou, Y., Chakrabarty, K.: Sensor deployment and target localization based on virtual forces. In: INFOCOM 2003. Twenty-Second Annual Joint Conference of the IEEE Computer and Communications. IEEE Societies, vol. 2. IEEE (2003)
Tan, G.; Jarvis, S.A.; Kermarrec, A.M.: Connectivity-guaranteed and obstacle-adaptive deployment schemes for mobile sensor networks. In: The 28th International Conference on Distributed Computing Systems, 2008. ICDCS ’08, vol. 8, pp. 429–437 (2008)
Costanzo, C.; Loscr’ı, V.; Natalizio, E.; Razafindralambo, T.: Nodes self-deployment for coverage maximization in mobile robot networks using an evolving neural network. Comput. Commun. 35(9), 1047–1055 (2012)
Gupta, M.; Krishna, C.R.; Prasad, D.: SEEDS: scalable energy efficient deployment scheme for homogeneous wireless sensor network. In: The Proceedings of the International Conference on Issues and Challenges in Intelligent Computing Techniques (ICICT), Ghaziabad, India (2014)
Howard, A.; Mataric, M.; Sukhatme, G.: An incremental self-deployment algorithm for mobile sensor networks. Auton. Robots Spec. Issue Intell. Embed. Syst. 13(2), 113–126 (2002)
Erdelj, M.; Razafindralambo, T.; Simplot-Ryl, D.: Covering points of interest with mobile sensors. IEEE Trans. Parallel Distrib. Syst. 24(1), 32–43 (2013)
Li, X.; Frey, H.; Santoro, N.; Stojmenovic, I.: Strictly localized sensor self-deployment for optimal focused coverage. IEEE Trans. Mob. Comput. 10(11), 1520–1533 (2011)
Zorbas, D.; Razafindralambo, T.: Wireless sensor network redeployment under the target coverage constraint. In: 2012 5th International Conference on New Technologies, Mobility and Security (NTMS), pp. 1–5 (2012)
Senouci, M.R.; Mellouk, A.; Assnoune, K.; Bouhidel, F.: Movement-assisted sensor deployment algorithms: a survey and taxonomy. IEEE Commun. Surv. Tutor. 17(4), 2493–2510 (2015)
Wang, G.; Cao, G.; Porta, T.L.: Movement-assisted sensor deployment. Proc. IEEE INFOCOM 4(6), 2469–2479 (2004)
Wang, G.; Cao, G.; Berman, P.; La Porta, T.F.: Bidding protocols for deploying mobile sensors. IEEE Trans. Mob. Comput. 6(5), 563–576 (2007)
Senouci, M.R.; Mellouk, A.; Assnoune, K.: Localized movement-assisted sensor deployment algorithm for hole detection and healing. IEEE Trans. Parallel Distrib. Syst. 25(5), 1267–1277 (2014)
Farahani, B.J.; Ghaffarian, H.; Fathy, M.: A fuzzy based priority approach in mobile sensor network coverage. Int. J. Recent Trends Eng. 2(1), 138–143 (2009)
Shu, H.; Liang, Q.: Fuzzy optimization for distributed sensor deployment. Communications Society, pp. 1903–1908 (2005)
Suen, Y.: A genetic-algorithm based mobile sensor network deployment algorithm. J. Chem. Inf. Model. 53(9), 1689–1699 (2013)
Yu, X.: A faster convergence artificial bee colony algorithm in sensor deployment for wireless sensor networks. Int. J. Distrib. Sens. Netw. 2013 (2013)
Baroudi, U.; Sallam, G.; Al-shaboti, M.; Younis, M.: GPS-free robots deployment technique for rescue operation based on landmark’s criticality. In: International Wireless Communications and Mobile Computing Conference (IWCMC) (2015)
Sallam, G.; Baroudi, U.: COVER: a cooperative virtual force robot deployment technique. In: The 14th IEEE International Conference on Ubiquitous Computing and Communications (IUCC 2015) (2015)
Kuhn, H.: The Hungarian method for the assignment problem. Nav. Res. Logist. Quart. 2(1–2), 83–97 (1955)
Wei Wang, X.H.: Research on sensor network self-deployment with virtual attractive and repulsive forces. Int. J. Adv. Inf. Sci. Serv. Sci. 5(6), 1031–1037 (2013)
Yu, X.; Huang, W.; Lan, J.; Qian, X.: A novel virtual force approach for node deployment in wireless sensor network. In: 2012 IEEE 8th International Conference on Distributed Computing in Sensor Systems, no. 2011, pp. 359–363 (2012)
Garetto, M.; Gribaudo, M.; Chiasserini, C.-F.; Leonardi, E.: A distributed sensor relocatlon scheme for environmental control. In: IEEE Internatonal Conference on Mobile Adhoc and Sensor Systems, vol. 2007, pp. 1–10 (2007)
Zhang, Y.; Wei, Z.: On deployment optimization strategy for hybrid wireless sensor networks. In: The 26th Chinese Control and Decision Conference (2014 CCDC), pp. 1875–1880 (2014)
Roselin, J.; Latha, P.: Energy balanced dynamic deployment optimization to enhance reliable lifetime of wireless sensor network. Int. J. Eng. Technol. (IJET) 5(4), 3450–3460 (2013)
Li, S.; Xu, C.; Pan, W.; Pan, Y.: Sensor deployment optimization for detecting maneuvering targets. In: 2005 7th International Conference on Information Fusion, p. 7 (2005)
Acknowledgements
The authors would like to acknowledge the support provided by the National Plan for Science, Technology and Innovation (MAARIFAH)—King Abdulaziz City for Science and Technology through the Science & Technology Unit at King Fahd University of Petroleum & Minerals (KFUPM), the Kingdom of Saudi Arabia, award Project No. 11-ELE2147-4.
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Sallam, G., Baroudi, U. Cooperative Robot Deployment: Simulation and Real Experimental Analysis. Arab J Sci Eng 44, 1843–1854 (2019). https://doi.org/10.1007/s13369-018-3102-9
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DOI: https://doi.org/10.1007/s13369-018-3102-9