Cooperative Target Localization with a Communication-Aware Unmanned Aircraft System

This paper presents an approach to generating information-gathering trajectories for a cooperative unmanned aircraft system that takes into account the reliability of multihop networked communication. The algorithms presented here implicitly consider the communication limitations of the aircraft within a path-planning algorithm in which there is a position dependency on both the sensing and communication capabilities of the network. A communication-aware performance metric is derived by combining the extended information filter with a packet- erasure channel model and stochastic model of packet routing. Informative trajectories that maximize this metric are generated by a distributed, hierarchical planning algorithm. Flight results are used to characterize the communication channel model for use in a multivehicle simulation. Finally, simulation studies are used to evaluate the path-planning approach through the specific application of stationary WiFi source localization. These studies show that the approach leads to improved estimation performance relative to path-planning that does not consider communication reliability. Further, the approach leads to the emergence of natural roles whereby some of the aircraft contribute largely to the sensing portion of the objective, while others improve communication reliability by serving mainly as communication relays.

[1]  S.L. Waslander,et al.  Mutual Information Methods with Particle Filters for Mobile Sensor Network Control , 2006, Proceedings of the 45th IEEE Conference on Decision and Control.

[2]  Byron D. Tapley,et al.  Chapter 4 – Fundamentals of Orbit Determination , 2004 .

[3]  Randy A. Freeman,et al.  Decentralized Environmental Modeling by Mobile Sensor Networks , 2008, IEEE Transactions on Robotics.

[4]  M. Abolhasan,et al.  Real-world performance of current proactive multi-hop mesh protocols , 2009, 2009 15th Asia-Pacific Conference on Communications.

[5]  Yasamin Mostofi,et al.  Decentralized Communication-Aware Motion Planning in Mobile Networks: An Information-Gain Approach , 2009, J. Intell. Robotic Syst..

[6]  B. Tapley,et al.  Statistical Orbit Determination , 2004 .

[7]  Eric W. Frew Sensitivity of Cooperative Target Geolocalization to Orbit Coordination , 2007 .

[8]  Stefan Roth,et al.  Covariance Matrix Adaptation for Multi-objective Optimization , 2007, Evolutionary Computation.

[9]  Hugh F. Durrant-Whyte,et al.  Process model, constraints, and the coordinated search strategy , 2004, IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004.

[10]  Joris De Schutter,et al.  A Comparison of Decision Making Criteria and Optimization Methods for Active Robotic Sensing , 2002, Numerical Methods and Application.

[11]  R. Olfati-Saber,et al.  Consensus Filters for Sensor Networks and Distributed Sensor Fusion , 2005, Proceedings of the 44th IEEE Conference on Decision and Control.

[12]  Hugh Durrant-Whyte,et al.  Communication In General Decentralised Filters And The Coordinated Search Strategy , 2004 .

[13]  Paul Scerri,et al.  Transitioning multiagent technology to UAV applications , 2008, AAMAS.

[14]  Yasamin Mostofi,et al.  Communication-aware navigation functions for cooperative target tracking , 2009, 2009 American Control Conference.

[15]  Cory Dixon Controlled mobility of unmanned aircraft chains to optimize network capacity in realistic communication environments , 2010 .

[16]  W. J. Studden,et al.  Theory Of Optimal Experiments , 1972 .

[17]  Eric W. Frew,et al.  Active Sensing by Unmanned Aircraft Systems in Realistic Communication Environments , 2009 .

[18]  Ben Grocholsky,et al.  Information-Theoretic Control of Multiple Sensor Platforms , 2002 .

[19]  Bob E. Schutz,et al.  Orbit Determination Concepts , 2004 .

[20]  Robin J. Evans,et al.  An information theoretic approach to observer path design for bearings-only tracking , 1997, Proceedings of the 36th IEEE Conference on Decision and Control.

[21]  Thomas Bäck,et al.  Evolutionary algorithms in theory and practice - evolution strategies, evolutionary programming, genetic algorithms , 1996 .

[22]  Allison Ryan Information-Theoretic Tracking Control Based on Particle Filter Estimate , 2008 .

[23]  Naomi Ehrich Leonard,et al.  Cooperative Filters and Control for Cooperative Exploration , 2010, IEEE Transactions on Automatic Control.

[24]  R. Olfati-Saber,et al.  Distributed Kalman Filter with Embedded Consensus Filters , 2005, Proceedings of the 44th IEEE Conference on Decision and Control.

[25]  R.M. Murray,et al.  On a decentralized active sensing strategy using mobile sensor platforms in a network , 2004, 2004 43rd IEEE Conference on Decision and Control (CDC) (IEEE Cat. No.04CH37601).

[26]  C. Guestrin,et al.  Near-optimal sensor placements: maximizing information while minimizing communication cost , 2006, 2006 5th International Conference on Information Processing in Sensor Networks.

[27]  H.F. Durrant-Whyte,et al.  A new approach for filtering nonlinear systems , 1995, Proceedings of 1995 American Control Conference - ACC'95.