Hostname: page-component-cd9895bd7-hc48f Total loading time: 0 Render date: 2024-12-27T07:55:39.548Z Has data issue: false hasContentIssue false
  • English
  • Français

Marsupial teams of robots: deployment of miniature robots for swarm exploration under communication constraints

Published online by Cambridge University Press:  15 January 2014

Micael S. Couceiro ,
David Portugal ,
Rui P. Rocha  and
Nuno M. F. Ferreira
Micael S. Couceiro*
Affiliation:
Institute of Systems and Robotics (ISR), University of Coimbra, Coimbra, Portugal RoboCorp, Engineering Institute of Coimbra (ISEC), Coimbra, Portugal
David Portugal
Affiliation:
Institute of Systems and Robotics (ISR), University of Coimbra, Coimbra, Portugal
Rui P. Rocha
Affiliation:
Institute of Systems and Robotics (ISR), University of Coimbra, Coimbra, Portugal
Nuno M. F. Ferreira
Affiliation:
RoboCorp, Engineering Institute of Coimbra (ISEC), Coimbra, Portugal
*
*Corresponding author. E-mail: micaelcouceiro@isr.uc.pt
Get access Rights & Permissions [Opens in a new window]

Summary

Mobile Ad hoc Networks have attracted much attention in the last years, since they allow the coordination and cooperation between agents belonging to a multi-robot system. However, initially deploying autonomously a wireless sensor robot network in a real environment has not taken the proper attention. Moreover, maintaining the connectivity between agents in real and complex environments is an arduous task since the strength of the connection between two nodes (i.e., robots) can change rapidly in time or even disappear. This paper compares two autonomous and realistic marsupial strategies for initial deployment in unknown scenarios, in the context of swarm exploration: Random and Extended Spiral of Theodorus. These are based on a hierarchical approach, in which exploring agents, named scouts, are autonomously deployed through explicit cooperation with supporting agents, denoted as rangers. Experimental results with a team of heterogeneous robots are conducted using both real and virtual robots. Results show the effectiveness of the methods, using a performance metric based on dispersion. Conclusions drawn in this work pave the way for a whole series of possible new approaches.

Keywords

Marsupial robotsSwarm roboticsCommunication constraintsFault-toleranceInitial deployment
Type
Articles
Information
Robotica , Volume 32 , Issue 7 , October 2014 , pp. 1017 - 1038
Copyright
Copyright © Cambridge University Press 2014 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

1.Couceiro, M. S., Rocha, R. P. and Ferreira, N. M. F., “Ensuring Ad Hoc Connectivity in Distributed Search with Robotic Darwinian Swarms,” Proceedings of the IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR2011), Kyoto, Japan (Nov. 1–5, 2011) pp. 284–289.Google Scholar
2.Rybski, P. E., Papanikolopoulos, N. P., Stoeter, S. A., Krantz, D. G., Yesin, K. B., Gini, M., Voyles, R., Hougen, D. F., Nelson, B. and Erickson, M. D., “Enlisting rangers and scouts for reconnaissance and surveillance,” IEEE Robot. Autom. Mag. 7 (4), 14–24 (2000).CrossRefGoogle Scholar
3.Araújo, A., Portugal, D., Couceiro, M. S., Figueiredo, C. and Rocha, R. P., “TRAXBOT: Assembling and Programming of a Mobile Robotic Platform,” Proceedings of the 4th International Conference on Agents and Artificial Intelligence (ICAART'2012), Vilamoura, Algarve, Portugal (Feb. 6–8, 2012) pp. 301–304.Google Scholar
4.Couceiro, M. S., Figueiredo, C. M., Luz, J. M. A., Ferreira, N. M. F. and Rocha, R. P., “A low-cost educational platform for swarm robotics,” Int. J. Robot. Educ. Art 2 (1), 1–15 (2011).Google Scholar
5.Couceiro, M. S., Figueiredo, C. M., Portugal, D., Rocha, R. P. and Ferreira, N. M. F., “Initial Deployment of a Robotic Team – A Hierarchical Approach Under Communication Constraints Verified on Low-Cost Platforms,” IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS'2012), Vilamoura - Algarve, Portugal (Oct. 7–12, 2012) pp. 4614–4619.Google Scholar
6.Murphy, R. R., “Marsupial and shape-shifting robots for urban search and rescue,” IEEE Intell. Syst. Appl. 15, 14–19 (2000).Google Scholar
7.Mei, Y., Lu, Y.-H., Hu, Y. C. and Lee, C. S. G., “Deployment Strategy for Mobile Robots with Energy and Timing Constraints,” Proceedings of the IEEE International Conference on Robotics and Automation (ICRA05), Barcelona, Spain (Apr. 18–22, 2005) pp. 2827–2832.Google Scholar
8.Marquardt, D., “An algorithm for least-squares estimation of nonlinear parameters,” SIAM J. Appl. Math. 11, 431–441 (1963).Google Scholar
9.Correll, N., Bachrach, J., Vickery, D. and Rus, D., “Ad-hoc Wireless Network Coverage with Networked Robots That Cannot Localize,” IEEE International Conference on Robotics and Automation Kobe International Conference Center, Kobe, Japan (May 12–17, 2009) pp. 3878–3885.Google Scholar
10.Lee, G., Nishimura, Y., Tatara, K. and Chong, N. Y., “Three Dimensional Deployment of Robot Swarms,” Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS10), Taipei, Taiwan (Oct. 18–22, 2010) pp. 5073–5078.Google Scholar
11.Groß, R., O'Grady, R., Christensen, A. L. and Dorigo, M., “The Swarm-Bot Experience: Strength and Mobility Through Physical Cooperation,” In: Handbook of Collective Robotics (Kernbach, S., ed.) (Pan Stanford Publishing, 2011) pp. 49–80, Ch. 2.Google Scholar
12.Hattenberger, G., Lacroix, S. and Alami, R., “Formation Flight: Evaluation of Autonomous Configuration Control Algorithms,” Proceedings of the 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems, San Diego, CA, USA (Oct. 29–Nov. 2, 2007) pp. 2628–2633.Google Scholar
13.Niccolini, M., Innocenti, M. and Pollini, L., “Near Optimal Swarm Deployment using Descriptor Functions,” Proceedings of the IEEE International Conference on Robotics and Automation (ICRA10), Anchorage, Alaska, USA (May 3–8, 2010) pp. 4952–4957.Google Scholar
14.Dellaert, F., Balch, T., Kaess, M., Ravichandran, R., Alegre, F., Berhault, M., McGuire, R., Merrill, E., Moshkina, L. and Walker, D., “The Georgia Tech Yellow Jackets: A Marsupial Team for Urban Search and Rescue,” AAAI Mobile Robot Competition Workshop, Edmonton, Alberta, Canada (Jul. 28–Aug. 1, 2002).Google Scholar
15.Howard, A., Mataric, M. J. and Sukhatme, G. S., “Mobile Sensor Network Deployment Using Potential Fields: A Distributed Scalable Solution to the Area Coverage Problem,” Proceedings of the 6th International Symposium on Distributed Autonomous Robotic Systems (DARS02), Fukuoka, Japan (Jun. 25–27, 2002) pp. 299–308.Google Scholar
16.Mei, Y., Lu, Y.-H., Hu, Y. C. and Lee, C. S. G., “Deployment of mobile robots with energy and timing constraints,” IEEE Trans. Robot. 22 (3), 507–521 (2006).Google Scholar
17.Ferworn, A., Hough, G., Manca, R., Antonishek, B., Scholtz, J. and Jacoff, A., “Expedients for Marsupial Operations of USAR Robots,” Proceedings of the IEEE International Workshop on Safety, Security and Rescue Robotics, Gaithersburg, MD, USA (Aug. 22–24, 2006) pp. 1–5.Google Scholar
18.Janssen, M. and Papanikolopoulos, N., “Enabling Complex Behavior by Simulating Marsupial Actions,” Proceedings of the 15th Mediterranean Conference on Control & Automation, Athens, Greece (Jul. 27–29, 2007) pp. 1–6.Google Scholar
19.Murphy, R. R., Ausmus, M., Bugajska, M., Ellis, T., Johnson, T., Kelley, N., Kiefer, J. and Pollock, L., “Marsupial-like mobile robot societies,” Proceedings of the Third Annual Conference on Autonomous Agents, ACM (1999) pp. 364–365.CrossRefGoogle Scholar
20.Ferworn, A., Wright, C., Tran, J., Li, C. and Choset, H., “Dog and Snake Marsupial Cooperation for Urban Search and Rescue Deployment,” Proceedings of the 2012 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR'2012), College Station, Texas, USA (Nov. 2012) pp. 1–5.Google Scholar
21.Howard, A., Mataric, M. and Sukhatme, G., “An Incremental Deployment Algorithm for Mobile Robot Teams,” Proceedings of the 2002 IEEE/RSJ International Conference on Intelligent Robots and Systems, Lausanne, Switzerland (Oct. 2002) pp. 2849–2854.Google Scholar
22.Conner, M., Uyar, M. U., Sahin, C. S., Urrea, E., Hokelek, I., Bertoli, G. and Pizzo, C., “Self-deployment of Mobile Agents in MANETs for Military Applications,” Army Science Conference, Orlando, Florida, USA (2008) pp. 1–8.Google Scholar
23.Bartolini, N., Calamoneri, T., Fusco, E. G., Massini, A. and Silvestri, S., “Snap and Spread: A Self-deployment Algorithm for Mobile Sensor Networks,” Proceedings of the 4th IEEE International Conference on Distributed Computing in Sensor Systems (DCOSS08), Santorini Island, Greece (Jun. 11–14, 2008) pp. 451–456.Google Scholar
24.Alliance, Z.. (2011, Aug.) ZigBee Alliance. [Online]. Available http://www.zigbee.orgGoogle Scholar
25.XBee. (2011, Aug.) XBee™/XBee-PRO™ OEM RF Modules datasheet. [Online]. Available http://ftp1.digi.com/support/documentation/90000982_A.pdfGoogle Scholar
26.Couceiro, M. S., Rocha, R. P. and Ferreira, N. M. F., “A Novel Multi-Robot Exploration Approach based on Particle Swarm Optimization Algorithms,” IEEE International Symposium on Safety, Security and Rescue Robotics (SSRR11), Kyoto, Japan (Nov. 1–5, 2011).Google Scholar
27.Couceiro, M. S., Rocha, R. P., Figueiredo, C. M., Luz, J. M. A. and Ferreira, N. M. F., “Multi-Robot Foraging based on Darwin's Survival of the Fittest,” IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS'12), Vilamoura, Portugal (Oct. 7–12, 2012) pp. 801–806.Google Scholar
28.Couceiro, M. S., Tenreiro Machado, J. A., Rocha, R. P. and Ferreira, N. M. F., “A fuzzified systematic adjustment of the robotic Darwinian PSO,” Robot. Auton. Syst. 60 (12), 1625–1639 (2012).Google Scholar
29.Luca, D. D., Mazzenga, F., Monti, C. and Vari, M., “Performance evaluation of indoor localization techniques based on rf power measurements from active or passive devices,” EURASIP J. Appl. Signal Process. 2006, 1–11 (2006).Google Scholar