The Cooperative Multi-Agent Formations and Networks project, known by its nickname SWARM-II, focuses on research under four main topics:

1. Network functional health, robustness and capabilities;
2. Development of discrete probability density maps (DPDMs);
3. Time difference of arrival de-interleaving for localization;
4. Development of general tools for cooperative target localization and sensor self-localization, including when GPS is lost, and determination of localization performance.

Each  topic bears on various fundamental research problems driven by certain real life scenarios of DSTO interest as well as more specific DSTO research tasks.

The primary user of the research is Australian Defence. An occasional user and supporter of the project is the US Air Force who has supplied funding through AOARD. However, the work has other potential users, e.g. those with interest in monitoring bushfires or with surveillance tasks.

Key Features

1.Control of Swarms. In areas of defence it is often important for airborne and ground vehicles to maintain a rigid or semi-rigid formation when executing a mission. Methods are being developed for moving a formation from point A to point B while maintaining its shape, even in the presence of disturbances such as wind.

2. Health of Formations. The formation can be characterized by its structure for providing guaranteed performance, e.g. ability to localize an electromagnetic radiation emitter to within a certain accuracy, even in complex (e.g.multiple emitters),  and vulnerable (e.g. wind, GPS denial) environments.  Methods for building in redundancy/robustness are considered. The results of SWARM can also be applied to telecommunications networks and to improve the sensor capabilities.

3. Cooperative Target Localisation. In some circumstances it may be necessary to localise and identify a set of emitters scattered over an area. Each vehicle in a formation using direction-finding sensors can collect data on the possible location of an emitter in relation to itself. Using a team of vehicles to survey the area from different angles, the data is collated and processed to associate signal streams with particular emitters and then to produce an accurate location for each of the emitters.

4. Time-Difference of Arrival De-Interleaving for Localization. This subtopic concerns pulse association or de-interleaving for the removal of multi-path and spurious signals using the signals received by multiple sensors.

Key Research Outcomes and Progress Report

Key Research Outputs

Click here for details about the predecessor project SWARM

Current Research Team (SWARM and SWARM-II)

• Prof. Brian Anderson, NICTA Canberra & The Australian National University
• Dr. Guoqiang Mao, NICTA ATP & The University of Sydney
• Dr. Changbin (Brad) Yu, The Australian National University
• Dr. Adrian N. Bishop, NICTA Canberra
  
• Iman Shames, NICTA Canberra & The Australian National University
• Yiming (Alex) Ji, NICTA Canberra & The Australian National University
• Baoqi Huang, The Australian National University
• Seh Chung Ng, The University of Sydney
• Xiaolei (Eric) Hou, The Australian National University
• Zijie (Geoffrey) Zhang, The University of Sydney
• Mohammad Deghat, The Australian National University
• Alireza Motevallian, The Australian National University
  

External Partners:

• Defence Science and Technology Organisation (DSTO), Electronic Warfare and Radar Division.
  

• Key DSTO Collaborators:
• • Dr. Sam Drake
  • Dr. Hatem Hmam
    

Previous Team Members:

• Dr. Baris Fidan, NICTA Canberra & The Australian National University
• Jason (Xiaoyuan) Ta, NICTA ATP & The University of Sydney

Others Involved and International Collaboration

Selected Publications

S. Drake, B.D.O Anderson and C. Yu, "Causal Association of Electromagnetic Signals using the Cayley Menger Determinant",  Applied Physics Letters, Vol. 95, No. 3, July 2009, http://arxiv.org/abs/0908.3143

I. Shames, B. Fidan and B.D.O. Anderson, "Minimization of the effect of noisy measurements on localization of multi-agent autonomous formations", Automatica, Volume 45, No. 4, pp. 1058-1065, April 2009, http://doi:10.1016/j.automatica.2008.11.018

A.N. Bishop, B. Fidan, B.D.O. Anderson, K. Dogancay and P.N. Pathirana, "Optimality Analysis of Sensor-Target Localization Geometries", Automatica, Vol. 46, No. 3, March 2010, http://doi:10.1016/j.automatica.2009.12.003

X. Ta, G. Mao and B.D.O. Anderson, "On the Phase Transition Width of K-connectivity in Wireless Multi-hop Networks", IEEE Transactions on Mobile Computing, vol. 8, no. 7, pp. 936-949, July 2009, http://dx.doi.org/10.1109/TMC.2008.170

A.N. Bishop, B.D.O. Anderson, B. Fidan, P.N. Pathirana and G. Mao, Bearings-Only Localization Using Geometrically Constrained Optimization. IEEE Trans. On Aerospace and Electronic Systems, Vol. 45, no. 1, pp. 308-320, January 2009, http://dx.doi.org/10.1109/TAES.2009.4805281

B.D.O. Anderson, C. Yu, B. Fidan, J.M. Hendrickx, “Rigid Graph Control Architectures for Autonomous Formations”, IEEE Control System Magazine, 23(2):48-63, Dec 2008, http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4653105

J.M. Hendrickx, C. Yu, B. Fidan, and B.D.O. Anderson, "Rigidity and persistence for ensuring shape maintenance of multi-agent meta formations," Asian Journal of Control, vol. 10, no. 2, pp. 131-143, March 2008, http://www.ajc.org.tw/pages/News/AJC_News.htm

SWARM Related Publications

SWARM-II Related Publications