Self-organised multi agent system for search and rescue operations
2010
Autonomous multi-agent systems perform inadequately in time critical missions, while they tend to
explore exhaustively each location of the field in one phase with out selecting the pertinent strategy. This
research aims to solve this problem by introducing a hierarchy of exploration strategies. Agents explore
an unknown search terrain with complex topology in multiple predefined stages by performing pertinent
strategies depending on their previous observations. Exploration inside unknown, cluttered, and confined
environments is one of the main challenges for search and rescue robots inside collapsed buildings. In
this regard we introduce our novel exploration algorithm for multi–agent system, that is able to perform
a fast, fair, and thorough search as well as solving the multi–agent traffic congestion.
Our simulations have been performed on different test environments in which the complexity of the
search field has been defined by fractal dimension of Brownian movements. The exploration stages are
depicted as defined arenas of National Institute of Standard and Technology (NIST). NIST introduced
three scenarios of progressive difficulty: yellow, orange, and red. The main concentration of this research
is on the red arena with the least structure and most challenging parts to robot nimbleness.
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