Monitoring and Cordoning Wildfires with an Autonomous Swarm of Unmanned Aerial Vehicles

Unmanned aerial vehicles, or drones, are already an integral part of the equipment used by firefighters to monitor wildfires. They are, however, still typically used only as remotely operated, mobile sensing platforms under direct real-time control of a human pilot. Meanwhile, a substantial body of literature exists that emphasises the potential...

Coverage and Energy Analysis of Mobile Sensor Nodes in Obstructed Noisy Indoor Environment: A Voronoi-Approach

When deploying a wireless sensor network (WSN) identifying optimal locations for the nodes is challenging, especially so if the environment is either (i) unknown or (ii) obstacle-rich. We proposes BISON (Bio-Inspired Self-Organizing Network), a variant of the Voronoi algorithm to address this challenge. Among the features of the approach are the...

The Swarm Is More Than the Sum of Its Drones: A Swarming Behaviour Analysis for the Deployment of Drone-Based Wireless Access Networks in GPS-Denied Environments and Under Model Communication Noise

This chapter reports on a family of nature-inspired algorithms that were successfully used to deploy a drone-based wireless sensor network into (simulated) indoor environments. The algorithms are designed to work in a decentralised manner, with each drone operating autonomously, using only local (subjective) information about a drone’s own...

The Design Challenges of Drone Swarm Control

It is widely recognised that swarms are the likely next step for Unmanned Aerial Vehicle (UAV) or drone technology. Although substantially increased autonomy for navigation, data collection and decision-making is very much part of the “collective artificial intelligence” vision, this expected development raises questions about the most...

Self-Swarming for Multi-Robot Systems Deployed for Situational Awareness

Machine-based situational awareness is a key element to conscious and intelligent interaction with the complex world we live in, be it for the individual unit, a complex dynamical system, or even complex systems. To create this awareness, the frequent gathering of accurate and real-time intelligence data is required to ensure timely, accurate,...

Coverage and Energy Analysis of Mobile Sensor Nodes in Obstructed Noisy Indoor Environment A Voronoi-Approach

When deploying a wireless sensor network (WSN) identifying optimal locations for the nodes is challenging, especially so if the environment is either (i) unknown or (ii) obstacle-rich. We proposes BISON (Bio-Inspired Self- Organizing Network), a variant of the Voronoi algorithm to address this challenge. Among the features of the approach are...

Nature-Inspired Drone Swarming for Real-Time Aerial Data-Collection Under Dynamic Operational Constraints

Unmanned Aerial Vehicles (UAVs) with acceptable performance are becoming commercially available at an affordable cost. Due to this, the use of drones for real-time data collection is becoming common practice by individual practitioners in the areas of e.g., precision agriculture and civil defense such as fire fighting. At the same time, as UAVs...

Long-term memory-induced synchronisation can impair collective performance in congested systems

We investigate the hypothesis that long-term memory in populations of agents can lead to counterproductive emergent properties at the system level. Our investigation is framed in the context of a discrete, one-dimensional road-traffic congestion model: we investigate the influence of simple cognition in a population of rational commuter agents...

Focusing attention in populations of semi-autonomously operating sensing nodes

Cognition and the cognitive processing of sensory information in biological entities is known to occur over multiple layers of processing. In the example of human vision there are a vast number of photo-receptors feeding into various layers of cells which pre-process the original information before it arrives to the brain (as biased data).We...