Abstract
We consider the path planning problem of mobile networked agents (e.g., robots) that have to travel towards assigned target locations. Robots’ path planners have to optimally balance potentially conflicting goals: keep the traveled distance within an assigned maximum value while, at the same time, let the robot reliably and effectively communicate with other robots in the multi-robot network, and reduce the risk of collisions. We propose a solution approach based on the integration of two components: a link quality predictor based on supervised learning, and a path optimizer, based on a mathematical programming formulation. The predictor is built offline and yields spatial predictions of the expected communication quality of the wireless links in terms of packet reception rate. Exploiting shared information about planned trajectories, these spatial predictions are used online by the robots to build time-dependent spatial maps of communication quality, to iteratively assess the best path to follow considering both local and prospective links, and to plan paths accordingly. To deal robustly with dynamic environments, path planning is implemented as a multi-stage scheme using a receding horizon strategy. The framework is evaluated in realistic simulation scenarios, showing the effectiveness of using the spatial predictor for the effective online planning of network-aware trajectories.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Feo Flushing, E., Nagi, J., Di Caro, G.A.: A mobility-assisted protocol for supervised learning of link quality estimates in wireless networks. In: Proceedings of the International Conference on Computing, Networking and Communications (ICNC), pp. 137–143 (2012)
Di Caro, G.A., Kudelski, M., Feo Flushing, E., Nagi, J., Ahmed, I., Gambardella, L.: On-line supervised incremental learning of link quality estimates in wireless networks. In: Proceedings of the 12th IEEE/IFIP Annual Mediterranean Ad Hoc Networking Workshop (Med-Hoc-Net), pp. 69–76 (2013)
Kudelski, M., Gambardella, L., Di Caro, G.A.: A mobility-controlled link quality learning protocol for multi-robot coordination tasks. In: Proceedings of the IEEE ICRA, pp. 5024–5031 (2014)
Kuwata, Y., How, J.P.: Cooperative distributed robust trajectory optimization using receding horizon MILP. IEEE Trans. Control Syst. Technol. 19(2), 423–431 (2011)
Hsieh, M.A., Cowley, A., Kumar, V., Taylor, C.J.: Maintaining network connectivity and performance in robot teams. J. Field Robot. 25(1–2), 111–131 (2008)
Rooker, M.N., Birk, A.: Multi-robot exploration under the constraints of wireless networking. Control Eng. Pract. 15(4), 435–445 (2007)
Hollinger, G.A., Singh, S.: Multirobot coordination with periodic connectivity: theory and experiments. IEEE Trans. Robot. 28(4), 967–973 (2012)
Tardioli, D., Mosteo, A.R., Riazuelo, L., Villarroel, J.L., Montano, L.: Enforcing network connectivity in robot team missions. Int. J. Robot. Res. 29(4), 460–480 (2010)
Ghaffarkhah, A., Mostofi, Y.: Path planning for networked robotic surveillance. IEEE Trans. Signal Process. 60(7), 3560–3575 (2012)
Thunberg, J., Ögren, P.: A mixed integer linear programming approach to pursuit evasion problems with optional connectivity constraints. Auton. Rob. 31(4), 333–343 (2011)
Gil, S., Feldman, D., Rus, D.: Communication coverage for independently moving robots. In: Proceedings of IEEE/RSJ IROS, pp. 4865–4872 (2012)
Yan, Y., Mostofi, Y.: Robotic router formation in realistic communication environments. IEEE Trans. Robot. 28(4), 810–827 (2012)
Grøtli, E.I., Johansen, T.A.: Path planning for UAVs under communication constraints using SPLAT! and MILP. J. Intel. Robot. Syst. 65(1–4), 265–282 (2011)
Fink, J., Ribeiro, A., Kumar, V.: Robust control of mobility and communications in autonomous robot teams. IEEE Access 1, 290–309 (2013)
Malmirchegini, M., Mostofi, Y.: On the spatial predictability of communication channels. IEEE Trans. Wireless Commun. 11(3), 964–978 (2012)
Lindhe, M., Johansson, K.H.: Adaptive exploitation of multipath fading for mobile sensors. In: Proceedings of the IEEE ICRA, pp. 1934–1939 (2010)
Feo Flushing, E., Kudelski, M., Nagi, J., Gambardella, L., Di Caro, G.A.: Poster abstract: link quality estimation - a case study for on-line supervised learning in wireless sensor networks. In: Langendoen, K., Hu, W., Ferrari, F., Zimmerling, M., Mottola, L. (eds.) Real-World Wireless Sensor Networks. LNEE, vol. 281, pp. 97–101. Springer, Heidelberg (2014)
Vansteenwegen, P., Souffriau, W., Van Oudheusden, D.: The orienteering problem: a survey. Eur. J. Oper. Res. 209(1), 1–10 (2011)
NS-3. Discrete-event network simulator for Internet systems (2013). http://www.nsnam.org
Acknowledgments
This research has been partially funded by the Swiss National Science Foundation (SNSF) Sinergia project SWARMIX, project number CRSI22_133059.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Di Caro, G.A., Feo Flushing, E., Gambardella, L.M. (2015). Use of Time-Dependent Spatial Maps of Communication Quality for Multi-robot Path Planning. In: Garcia Pineda, M., Lloret, J., Papavassiliou, S., Ruehrup, S., Westphall, C. (eds) Ad-hoc Networks and Wireless. ADHOC-NOW 2014. Lecture Notes in Computer Science(), vol 8629. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-46338-3_18
Download citation
DOI: https://doi.org/10.1007/978-3-662-46338-3_18
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-662-46337-6
Online ISBN: 978-3-662-46338-3
eBook Packages: Computer ScienceComputer Science (R0)