Adapting the mapping diffculty for the automatic generation of rescue challenges

This paper focuses on the method and implementation
of a map generator for the USARSim environment, which is
capable of generating indoor environments. The generator adapts
to a difficulty measure, which signifies how difficult the generated
map should be, when mapped by a robot. Both the method of the
procedural generation process as well as the knowledge on the
difficulty measure are explained, followed by the implementation
of the generator. Multiple maps with various difficulties are
generated and mapping runs are simulated by experienced robot
operators. Then the difficulty is assessed by these operators and
compared to the difficulty level of the maps. The rules of the
generator turn out to be able to influence the difficulty of the
maps, but due to the complexities of ’difficulty’ it is difficult to
do this consistently.