Swarms and Network Intelligence in Search

1. Front Matter

   Pages i-ix

   PDF

2. Introduction to Swarm Search

   • Yaniv Altshuler, Alex Pentland, Alfred M. Bruckstein

   Pages 1-14

3. Cooperative “Swarm Cleaning” of Stationary Domains

   • Yaniv Altshuler, Alex Pentland, Alfred M. Bruckstein

   Pages 15-49

4. Swarm Search of Expanding Regions in Grids: Lower Bounds

   • Yaniv Altshuler, Alex Pentland, Alfred M. Bruckstein

   Pages 51-89

5. Swarm Search of Expanding Regions in Grids: Upper Bounds

   • Yaniv Altshuler, Alex Pentland, Alfred M. Bruckstein

   Pages 91-127

6. The Search Complexity of Collaborative Swarms in Expanding \(\mathbf{Z}^{2}\) Grid Regions

   • Yaniv Altshuler, Alex Pentland, Alfred M. Bruckstein

   Pages 129-153

7. Collaborative Patrolling Swarms in Stochastically Expanding Environments

   • Yaniv Altshuler, Alex Pentland, Alfred M. Bruckstein

   Pages 155-185

8. The Cooperative Hunters – Efficient and Scalable Drones Swarm for Multiple Targets Detection

   • Yaniv Altshuler, Alex Pentland, Alfred M. Bruckstein

   Pages 187-205

9. Optimal Dynamic Coverage Infrastructure for Large-Scale Fleets of Reconnaissance UAVs

   • Yaniv Altshuler, Alex Pentland, Alfred M. Bruckstein

   Pages 207-238

This book offers a comprehensive analysis of the theory and tools needed for the development of an efficient and robust infrastructure for the design of collaborative patrolling unmanned aerial vehicle (UAV) swarms, focusing on its applications for tactical intelligence drones. It discusses frameworks for robustly and near-optimally analyzing flocks of semi-autonomous vehicles designed to efficiently perform the ongoing dynamic patrolling and scanning of pre-defined “search regions”. It discusses the theoretical limitations of such systems, as well as the trade-offs between the systems’ various economic and operational parameters.


Current UAV systems rely mainly on human operators for the design and adaptation of drones’ flying routes. However, recent technological advances have introduced new systems, comprised of a small number of self-organizing vehicles, manually guided at the swarm level by a human operator.

With the growing complexity o
f such man-supervised architectures, it is becoming increasingly harder to guarantee a pre-defined level of performance. The use of large scale swarms of UAVs as a combat and reconnaissance platform therefore necessitates the development of an efficient optimization mechanism of their utilization, specifically in the design and maintenance of their patrolling routes.

The book is intended for researchers and engineers in the fields of swarms systems and autonomous drones. 

• Computational Intelligence
• Network Intelligence
• Swarm Intelligence
• Computational Complexity
• Collaborative Patrolling
• Autonomous Decentralized Systems

“The book is a solid attempt to formally characterize the properties of domains and the swarms of robots operating in them. The algorithms are often described with figures that show sample environments and how the operations progress over time. This provides a good understanding of how the algorithms work.” (M. Gini, Computing Reviews, January, 2019)​

• MIT Media Lab, Massachusetts Institute of Technology, Cambridge, USA

  Yaniv Altshuler, Alex Pentland

• Computer Science Department, Israeli Institute of Technology (Technion), Haifa, Israel

  Alfred M. Bruckstein

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