IEEE Robotics & Automation Magazine - June 2013 - 62

such as localization, collision avoidance, and gas mapping on
a small platform, and, moreover, it allows real-time cooperation among multiple units.
In Figure 15, the software architecture is described, while
in Figure 16(a), a picture of the robot equipped with the aforementioned sensors is depicted. As indicated in Figure 16(b),
results show a good estimate even if a coarse localization, due
to the interdistance between adjacent tags (20 cm), was provided. The reader is referred to [23], where multiple SAETTA
robots concurrently explore a much bigger environment.
Conclusions
In this work, a new small mobile platform has been presented.
The main characteristics of the robot are its low cost and flexibility. The latter one has been demonstrated through both
hardware and software architectures that easily adapt to different contexts, as stated by several examples.
Whenever sophisticated algorithms have to be executed,
high-level tools can be interfaced with the software running
onboard the robot. In fact, the OS installed on the platforms
provides all the needed tools to integrate SAETTA with a
wide range of systems. At the same time, it provides a large set
of drivers to be used with several peripherals.
The platform has been designed to be used in indoor environments: the traction system performs well, and the computational burden results are good for such kind of platforms. At the
same time, the small dimensions and resources of SAETTA
hinder the usage of power-consuming sensors and processors,
especially for long-lasting experiments.
Acknowledgments
A special thanks to Giovanni Micheli for the help provided
in the leader-follower experiments and to Enrico Di Lello for
the visual framework. We thank Alessandro Saffiotti and his
research group for the support provided during the experiments in the PEIS Home at the AASS Research Center,
Örebro, Sweden.
References
[1] A. Martinoli, K. Easton, and W. Agassounon, "Modeling swarm robotic
systems: A case study in collaborative distributed manipulation," Int. J. Robot.
Res., vol. 23, no. 4-5, pp. 415-436, 2004.
[2] J. Mclurkin and J. Smith, "Distributed algorithms for dispersion in indoor
environments using a swarm of autonomous mobile robots," in Proc. 7th Int.
Symp. Distributed Autonomous Robotic Systems (DARS), Tolouse, France,
2004, pp. 545-546.
[3] F. Mondada, L. Gambardella, D. Floreano, and M. Dorigo, "The cooperation of swarm-bots: Physical interactions in collective robotics," IEEE Robot.
Automat. Mag., vol. 12, no. 2, pp. 21-28, 2005.
[4] P. Yang, R. A. Freeman, and K. M. Lynch, "Multi-agent coordination by
decentralized estimation and control," IEEE Trans. Automat. Contr., vol. 53,
no. 11, pp. 2480-2496, Dec. 2008.
[5] R. Sepulchre, D. Paley, and N. E. Leonard, "Stabilization of planar collective motion with limited communication," IEEE Trans. Automat. Contr., vol.
53, no. 3, pp. 706-719, 2008.
[6] M. Karpelson, J. P. Whitney, G.-Y. Wei, and R. J. Wood, "Energetics of flappingwing robotic insects: Towards autonomous hovering flight," in Proc. IEEE/RSJ Int.
Conf. Intelligent Robots and Systems (IROS), Oct. 18-22, 2010, pp. 1630-1637.
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[7] S. Hirose and E. F. Fukushima, "Snakes and strings: New robotic components
for rescue operations," Int. J. Robot. Res., vol. 23, no. 4-5, pp. 341-349, 2004.
[8] S. Bergbreiter and K. S. J. Pister, "Cotsbots: An off-the-shelf platform for
distributed robotics," in Proc. IROS, Las Vegas, 2003, pp. 27-31.
[9] F. Mondada, M. Bonani, X. Raemy, J. Pugh, C. Cianci, A. Klaptocz, S.
Magnenat, J.-C. Zufferey, D. Floreano, and A. Martinoli, "The e-puck, a robot
designed for education in engineering," in Proc. 9th Conf. Autonomous Robot
Systems and Competitions, 2009, vol. 1, no. 1, pp. 59-65.
[10] B. P. Douglass, Real-Time Design Patterns: Robust Scalable Architecture for
Real-Time Systems. Boston, MA: Addison-Wesley Longman, 2002.
[11] R. Olfati-Saber, J. A. Fax, and R. M. Murray, "Consensus and cooperation in networked multi-agent systems," in Proc. IEEE, vol. 95, no. 1, pp. 215-233, Jan. 2007.
[12] K. LeBlanc and A. Saffiotti, "Multirobot object localization: A fuzzy fusion
approach," IEEE Trans. Syst., Man Cybern. B, vol. 39, no. 5, pp. 1259-1276, 2009.
[13] D. P. Bovet and M. Cesati Ph, Understanding the Linux Kernel, 3rd ed.
Sebastopol, CA: O'Reilly Media, Nov. 2005.
[14] A. D. Luca and G. Oriolo, "Local incremental planning for nonholonomic
mobile robots," in Proc. 1994 Int. Conf. Robotics and Automation, 1994, pp. 104-110.
[15] A. Doucet, N. De Freitas, and N. Gordon, "Particle filters-A theoretical
perspective," in Sequential Monte Carlo Methods in Practice, A. Doucet, N. de
Freitas, and N. Gordon, Eds. New York: Springer-Verlag, 2001, ch. 2, pp. 17-38.
[16] M. Di Rocco and G. Ulivi, "An efficient implementation of particle filter
using compass data," in Proc. 7th IFAC Symp. Intelligent Autonomous Vehicles,
2010, pp. 90-96.
[17] M. Quigley, K. Conley, B. P. Gerkey, J. Faust, T. Foote, J. Leibs, R. Wheeler,
and A. Y. Ng, "ROS: An open-source robot operating system," in Proc. ICRA
Workshop on Open Source Software, 2009, pp. 1-8.
[18] G. Grisetti, C. Stachniss, and W. Burgard, "Improved techniques for grid
mapping with Rao-Blackwellized particle filters," IEEE Trans. Robotics, vol.
23, no. 1, pp. 34-46, Feb. 2007.
[19] A. Franchi, G. Oriolo, and P. Stegagno, "Mutual localization in a multirobot system with anonymous relative position measures," in Proc. IEEE/RSJ Int.
Conf. Intelligent Robots and Systems, St. Louis, MO, Nov. 2009, pp. 3974-3980.
[20] A. Saffiotti, M. Broxvall, M. Gritti, K. Leblanc, R. Lundh, and J. Rashid,
"The PEIS-ecology project: Vision and results," in Proc. IEEE Int. Conf.
Intelligent Robots and Systems (IROS) and IROS-08 Workshop on Network
Robot Systems, 2008, pp. 2329-2335.
[21] I. Horswill, "Analysis of adaptation and environment," Artif. Intell., vol.
73, no. 1-2, pp. 1-30, 1995.
[22] A. J. Lilienthal, M. Reggente, M. Trincavelli, J. L. Blanco, and J. Gonzalez,
"A statistical approach to gas distribution modelling with mobile robots the
kernel DM+V algorithm," in Proc. IEEE/RSJ Int. Conf. Intelligent Robots and
Systems (IROS), Oct. 11-15, 2009, pp. 570-576.
[23] M. Di Rocco, M. Reggente, and A. Saffiotti, "Gas source localization in
indoor environments using multiple inexpensive robots and stigmergy," in
Proc. IEEE/RSJ Int. Conf. Intelligent Robots and Systems (IROS), San Francisco,
CA, 2011, pp. 5007-5014.

Maurizio Di Rocco, Robotics Lab, Department of Automation
and Computer Science, DIA, Roma Tre University, Via Della
Vasca Navale 79, 00146, Rome, Italy. E-mail: dirocco@dia.
uniroma3.it.
Francesco La Gala, INSEAN, Via di Vallerano 139, 00128,
Rome, Italy. E-mail: f.lagala@insean.it.
Giovanni Ulivi, Robotics Lab, Department of Automation and
Computer Science, DIA, Roma Tre University, Via Della Vasca
Navale 79, 00146, Rome, Italy. E-mail: ulivi@uniroma3.it.
http://www.uniroma3.it
Table of Contents for the Digital Edition of IEEE Robotics & Automation Magazine - June 2013
