Landscape maintenance is a pivotal factor to reduce wildfire hazard potential. Being a difficult, time-consuming and generally expensive task, humans often face great difficulties to address the problem effectively. Considering its spatial distribution and exploration capabilities, swarm robotics presents itself as a natural solution to assist humans or other robotic agents in the reconnaissance of forestry environments and identification of fuel accumulation, such as forest debris. In this work, we propose an optimization framework for the exploration problem of forestry environments with a team of swarming robots, which also entails the deployment of a network infrastructure formed by the robots to assist agents during fire-prevention tasks. Experiments show the benefits of employing the multi-robot coordination algorithm described, which provides an effective solution for the exploration task and guarantees a final formation that maximizes network coverage for mission information exchange, considering obstacles density and other interfering factors. Thus, the system proposed might assist human operators with relevant forestry information acquired during exploration and maintain a fail-safe network for communication while agents operate in the field.

Chapter Contents:

• Abstract
• 12.1 Introduction
• 12.2 Related work
• 12.3 Problem definition
• 12.3.1 Collective exploration
• 12.3.2 Network deployment
• 12.4 A swarm optimization solution for the collective exploration and network deployment problems
• 12.4.1 Collective exploration with RDPSO
• 12.4.2 Network deployment with RDPSO
• 12.5 Results
• 12.6 Discussion
• 12.7 Conclusions and future work
• Acknowledgment
• References

Inspec keywords: fires; wildfires; mobile robots; multi-robot systems; forestry

Other keywords: great difficulties; landscape maintenance; swarm robotics; fire-prevention tasks; network deployment; forestry environments; robotic agents; human operators; multirobot coordination algorithm; collective exploration; wildfire hazard potential; generally expensive task; relevant forestry information; exploration problem; effective solution; swarming robots; natural solution; difficult time-consuming; pivotal factor; network infrastructure; exploration task; network coverage; fail-safe network; spatial distribution; humans

Subjects: Mobile robots; Optimisation techniques; Combinatorial mathematics; Robotics