Swarming in forestry environments: collective exploration and network deployment
Micael S. Couceiro, David Portugal
- Year
- 2018
- Citations
- 10
Abstract
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.
Keywords
Related papers
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
A new optimizer using particle swarm theory
R.C. Eberhart, James Kennedy
2002