Abstract
This paper presents a decentralized mobility control algorithm for the formation and maintenance of an optimal cascaded communication chain between a lead sensor-equipped robot and a control station, using a team of robotic vehicles acting as communication relays in an unknown and dynamic RF environment. The gradient-based controller presented uses measurements of the signal-to-noise ratio (SNR) field of neighbor communication links, as opposed to relative position between nodes, as input into a localized performance function. By using the SNR field as input into the control system, the controller is reactive to unexpected and unpredictable changes in the RF environment that is not possible with range-based controllers. Since the operating environment is not known a priori to deployment of a robotic sensor network, an adaptive model-free extremum seeking (ES) algorithm, that uses the motion of the relays to estimate the performance function gradient, is presented to control the motion of 2D nonholonomic vehicles acting as communication relays using the gradient-based controller. Even without specific knowledge of the SNR field, simulations show that the ES decentralized chaining controller using measurements of the SNR field, will drive a team of robotic vehicles to locations that achieve the global objective of maximizing capacity of a cascaded communication chain, even in the presence of an active jamming source.
Similar content being viewed by others
Notes
\(\frac{\partial c}{\partial S} > 0\).
\(D_{\theta }^{i} (\cdot )\) denotes the i th directional derivative of J w.r.t. θ.
References
Ariyur K, Krstic M (2002) Multivariable extremum seeking feedback: analysis and design. In: Fifteenth international symposium on mathematical theory of networks and systems, Notre Dame, 12–16 August 2002
Ariyur KB, Krstic M (2003) Real-time optimization by extremum-seeking control. Wiley, New York
Basu P, Redi J (2004) Movement control algorithms for realization of fault-tolerant ad hoc robot networks. IEEE Netw 18(4):36
Beard RW, Stepanyan V (2003) Synchronization of information in distributed multiple vehicle coordinated control. In: IEEE conference on decision and control, IEEE, Maui, December 2003
Brown TX, Argrow B, Dixon C, Doshi S, Thekkekunnel R-G, Henkel D (2004) Ad hoc uav ground network (augnet). In: AIAA 3rd “Unmanned unlimited” technical conference, AIAA, Chicago, 20–23 September 2004
Clarke FH (1975) Generalized gradients and applications. Trans Am Math Soc 205:247–262, April
Cortes J, Martinez S, Karatas T, Bullo F (2004) Coverage control for mobile sensing networks. In: IEEE transactions on robotics and automation. IEEE, Piscataway, May 2002, pp 1327–1332
Dubins LE (1957) On curves of minimal length with a constraint on average curvature, and with prescribed initial and terminal positions and tangents. Am J Math 79(3):497–516, July
Frew EW, Lawrence D (2005) Cooperative stand-off tracking of moving targets by a team of autonomous aircraft. In: AIAA guidance, navigation, and control conference, San Francisco, August 2005
Gerkey BP, Mailler R, Morisset B (2006) Commbots: distributed control of mobile communication relays. In: Proc. of the AAAI workshop on auction mechanisms for robot coordination (AuctionBots). Boston, July 2006, p 5157
Goldenberg D, Lin J, Morse AS, Rosen BE, Yang YR (2004) Towards mobility as a network control primitive. In: Mobihoc ’04. ACM, Tokyo, 24–26 May 2004
Indiveri G (1999) Kinematic time-invariant control of a 2d nonholonomic vehicle. In: 38th Conference on decision and control (CDC’99), Phoenix, December 1999
Kramer G, Gastpar M, Gupta P (2005) Cooperative strategies and capacity theorems for relay networks. IEEE Trans Inf Theory 51(9):3037–3063, September
Krstic M, Wang HH (2000) Stability of extremum seeking feedback for general nonlinear dynamic systems. Automatica 36:595–601
Martinez S, Cortes J, Bullo F (2007) Motion coordination with distributed information. IEEE Control Syst Mag 27(4):75–88, August
Olfati-Saber R, Murray RM (2003) Flocking with obstacle avoidance: cooperation with limited information in mobile networks. In: Conference on decision and control (CDC), Maui, December 2003
Pezeshkian N, Nguyen HG, Burmeister A (2007) Unmanned ground vehicle radio relay deployment system for non-line-of-sight operations. In: IASTED robotics and applications (RA 2007), Würzburg, 29–31 August 2007
Rappaport TS, Na C, Chen J (2004) Application throughput measurements and predictions using site-specific information. In: IEEE 802.11 plenary session, IEEE doc. 802.110-04-1473-00-000t, 17 November. IEEE, Piscataway
Sweeney J, Brunette T, Grupen YYR (2002) Coordinated teams of reactive mobile platforms. In: International conference on robotics and automation, IEEE, Washington, DC, 11–15 May 2002
Taub B, Schilling DL (1986) Principles of communication systems. McGraw-Hill, New York
Yang L, Passino KM, Polycarpou M (2003) Stability analysis of m-dimensional asynchronous swarms with a fixed communication topology. IEEE Trans Automat Contr 48(1; analyzed. Such stability analysis is of fundamental importance):76–95, December
Zajkowski T, Dunagan S, Eilers J (2006) Small uas communications mission. In: Eleventh biennial USDA forest service remote sensing applications conference, Salt Lake City, 24–28 April 2006
Zhang C, Arnold D, Ghods N, Siranosian A, Krstic M (2006) Source seeking with nonholonomic unicycle without position measurement—part i: tuning of forward velocity. In: 45th IEEE conference on decision and control, San Diego, 13–15 December 2006
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Dixon, C., Frew, E.W. Maintaining Optimal Communication Chains in Robotic Sensor Networks using Mobility Control. Mobile Netw Appl 14, 281–291 (2009). https://doi.org/10.1007/s11036-008-0102-0
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11036-008-0102-0