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Autonomous Robots
Erschienen in: Autonomous Robots 4/2017

04.06.2016

Decentralized simultaneous multi-target exploration using a connected network of multiple robots

verfasst von: Thomas Nestmeyer, Paolo Robuffo Giordano, Heinrich H. Bülthoff, Antonio Franchi

Erschienen in: Autonomous Robots | Ausgabe 4/2017

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Abstract

This paper presents a novel decentralized control strategy for a multi-robot system that enables parallel multi-target exploration while ensuring a time-varying connected topology in cluttered 3D environments. Flexible continuous connectivity is guaranteed by building upon a recent connectivity maintenance method, in which limited range, line-of-sight visibility, and collision avoidance are taken into account at the same time. Completeness of the decentralized multi-target exploration algorithm is guaranteed by dynamically assigning the robots with different motion behaviors during the exploration task. One major group is subject to a suitable downscaling of the main traveling force based on the traveling efficiency of the current leader and the direction alignment between traveling and connectivity force. This supports the leader in always reaching its current target and, on a larger time horizon, that the whole team realizes the overall task in finite time. Extensive Monte Carlo simulations with a group of several quadrotor UAVs show the scalability and effectiveness of the proposed method and experiments validate its practicability.
Vorheriger Artikel Multi-resolution map building and loop closure with omnidirectional images
Nächster Artikel A confidence-based roadmap using Gaussian process regression

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Fußnoten
1
More complex sensing models could also be taken into account, see Robuffo Giordano et al. (2013) for a discussion in this sense.
 
2
By online we mean that the targets are generated at runtime, thus precluding the presence of a preliminary phase in which the robots may plan in advance the multi-target exploration action. Indeed, if all the targets are known beforehand, one could still apply our method but other planning strategies might potentially lead to better solutions.
 
3
The two routines can run at two different frequencies, typically slower for the planning loop and faster for the motion control loop.
 
4
Presence of a ‘prime traveler’ can be easily assessed in a distributed way by, e.g., flooding (Lim and Kim 2001) on a low frequency.
 
Literatur
Antonelli, G., Arrichiello, F., Chiaverini, S., & Setola, R. (Aug 2005). A self-configuring MANET for coverage area adaptation through kinematic control of a platoon of mobile robots. In 2005 IEEE/RSJ international conference on intelligent robots and systems (pp. 1332–1337), Edmonton, Canada.
Antonelli, G., Arrichiello, F., Chiaverini, S., & Setola, R. (Mar 2006). Coordinated control of mobile antennas for ad-hoc networks in cluttered environments. In 9th International conference on intelligent autonomous systems, Tokyo, Japan.
Bektas, T. (2006). The multiple traveling salesman problem: An overview of formulations and solution procedures. Omega, 34(3), 209–219.CrossRef
Biagiotti, L., & Melchiorri, C. (2008) Trajectory planning for automatic machines and robots. Springer. ISBN 978-3540856283.
Burgard, W., Moors, M., Stachniss, C., & Schneider, F. (2005). Coordinated multi-robot exploration. IEEE Transactions on Robotics and Automation, 21(3), 376–386.CrossRef
Durham, J. W., Franchi, A., & Bullo, F. (2012). Distributed pursuit-evasion without global localization via local frontiers. Autonomous Robots, 32(1), 81–95.CrossRef
Faigl, J., & Hollinger, G. A. (Sep 2014). Unifying multi-goal path planning for autonomous data collection. In 2013 IEEE/RSJ international conference on intelligent robots and systems (pp. 2937–2942), Chicago, IL.
Fiedler, M. (1973). Algebraic connectivity of graphs. Czechoslovak Mathematical Journal, 23(98), 298–305.MathSciNetMATH
Franchi, A., Freda, L., Oriolo, G., & Vendittelli, M. (2009). The sensor-based random graph method for cooperative robot exploration. IEEE/ASME Transactions on Mechatronics, 14(2), 163–175.CrossRef
Freeman, R. A., Yang, P., & Lynch, K. M. (Jan 2006). Stability and convergenceproperties of dynamic average consensus estimators. In 45thIEEE conference on decision and control (pp. 338–343), San Diego, CA.
Grabe, V., Riedel, M., Bülthoff, H. H., Robuffo Giordano, P., & Franchi, A. (Sep 2013). The TeleKyb framework for a modular and extendible ROS-based quadrotor control. In 6th European conference on mobile robots (pp. 19–25), Barcelona, Spain.
Hollinger, G., & Singh, S. (2012). Multirobot coordination with periodic connectivity: Theory and experiments. IEEE Transactions on Robotics, 28(4), 967–973.CrossRef
Howard, A., Parker, L. E., & Sukhatme, G. S. (2006). Experiments with a large heterogeneous mobile robot team: Exploration, mapping, deployment and detection. The International Journal of Robotics Research, 25(5–6), 431–447.CrossRef
Jensfelt, P., & Kristensen, S. (2001). Active global localization for a mobile robot using multiple hypothesis tracking. IEEE Transactions on Robotics and Automation, 17(5), 748–760.CrossRef
Lächele, J., Franchi, A., Bülthoff, H. H., & Robuffo Giordano, P. (2012). SwarmSimX: Real-time simulation environment for multi-robot systems. In I. Noda, N. Ando, D. Brugali, & J. J. Kuffner (Eds.), 3rd international conference on simulation, modeling, and programming for autonomous robots. Lecture Notes in Computer Science (Vol. 7628, pp. 375–387). Springer.
Lim, H., & Kim, C. (2001). Flooding in wireless ad hoc networks. Computer Communications, 24(3–4), 353–363.CrossRef
Lynch, N. A. (1997). Distributed algorithms. Morgan Kaufmann, ISBN 1558603484.
Masone, C., Franchi, A., Bülthoff, H. H., & Robuffo Giordano, P. (Oct 2012) Interactive planning of persistent trajectories for human-assisted navigation of mobile robots. In 2012 IEEE/RSJ international conference on intelligent robots and systems (pp. 2641–2648), Vilamoura, Portugal.
Mistler, V., Benallegue, A., & M’Sirdi, N. K. (Sep 2001). Exact linearization and noninteracting control of a 4 rotors helicopter via dynamic feedback. In 10th IEEE internationl symposium on robots and human interactive communications (pp. 586–593), Bordeaux, Paris, France.
Mosteo, A. R., Montano, L., & Lagoudakis, M. G. (Nov 2008). Guaranteed-performance multi-robot routing under limited communication range. In 9th international symposium on distributed autonomous robotic systems (pp. 491–502), Tsukuba, Japan.
Murphy, R., Tadokoro, S., Nardi, D., Jacoff, A., Fiorini, P., Choset, H., & Erkmen, A. (2008). Search and rescue robotics. In B. Siciliano & O. Khatib (Eds.), Springer handbook of robotics (pp. 1151–1173). Springer.
Nestmeyer, T., Robuffo Giordano, P., & Franchi, A. (May 2013a). Multi-target simultaneous exploration with continual connectivity.In 2nd international work. on crossing the reality gap—From single tomulti- to many robot systems, at 2013 IEEE international conference on roboticsand automation, Karlsruhe, Germany.
Nestmeyer, T., Robuffo Giordano, P., & Franchi, A. (Oct 2013b). Human-assisted parallel multi-target visiting in a connected topology. In 6th International work. on human-friendly robotics, Rome, Italy.
Olfati-Saber, R., & Murray, R. M. (Jun 2003). Consensus protocols for networks of dynamic agents. In 2003 American control conference (pp. 951–956), Denver, CO.
Olfati-Saber, R., & Murray, R. M. (2004). Consensus problems in networks of agents with switching topology and time-delays. IEEE Transactions on Automatic Control, 49(9), 1520–1533.MathSciNetCrossRef
Pasqualetti, F., Franchi, A., & Bullo, F. (2012). On cooperative patrolling: Optimal trajectories, complexity analysis, and approximation algorithms. IEEE Transactions on Robotics, 28(3), 592–606.CrossRef
Pei, Y., & Mutka, M. W. (May 2012). Steiner traveler: Relay deployment for remote sensing in heterogeneous multi-robot exploration. In 2012 IEEE international conference on robotics and automation (pp. 1551–1556), St. Paul, MN.
Pei, Y., Mutka, M. W., & Xi, N. (May 2010). Coordinated multi-robot real-time exploration with connectivity and bandwidth awareness. In 2010 IEEE international conference on robotics and automation (pp. 5460–5465), Anchorage, AK.
Robuffo Giordano, P., Franchi, A., Secchi, C., & Bülthoff, H. H. (2013). A passivity-based decentralized strategy for generalized connectivity maintenance. The International Journal of Robotics Research, 32(3), 299–323.CrossRef
Stump, E., Jadbabaie, A., & Kumar, V. (May 2008) Connectivity management in mobile robot teams. In 2008 IEEE international conference on robotics and automation (pp. 1525–1530), Pasadena, CA.
Stump, E., Michael, N., Kumar, V., & Isler, V. (2011) Visibility-based deployment of robot formations for communication maintenance. In 2011 IEEE international conference on robotics and automation (pp. 4489–4505), Shanghai, China.
Tardioli, D., Mosteo, A. R., Riazuelo, L., Villarroel, J. L., & Montano, L. (2010). Enforcing network connectivity in robot team missions. The International Journal of Robotics Research, 29(4), 460–480.CrossRef
Yang, P., Freeman, R. A., Gordon, G. J., Lynch, K. M., Srinivasa, S. S., & Sukthankar, R. (2010). Decentralized estimation and control of graph connectivity for mobile sensor networks. Automatica, 46(2), 390–396.MathSciNetCrossRefMATH
Zavlanos, M. M., & Pappas, G. J. (2007). Potential fields for maintaining connectivity of mobile networks. IEEE Transaction on Robotics, 23(4), 812–816.CrossRef
Metadaten
Titel
Decentralized simultaneous multi-target exploration using a connected network of multiple robots
verfasst von
Thomas Nestmeyer
Paolo Robuffo Giordano
Heinrich H. Bülthoff
Antonio Franchi
Publikationsdatum
04.06.2016
Verlag
Springer US
Erschienen in
Autonomous Robots / Ausgabe 4/2017
Print ISSN: 0929-5593
Elektronische ISSN: 1573-7527
DOI
https://doi.org/10.1007/s10514-016-9578-9

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