In search and rescue operations, the primary, urgent, and critical task is to locate people trapped under debris in collapsed buildings. Mobile robots are expected to facilitate the acquisition of information about a disaster site and the detection of victims. In this paper, we investigate the strategy for exploring the space under debris using multiple mobile robots. To establish a baseline, we first evaluate the performance of simple and primitive mobility algorithms, such as random walk and depth-first search, across various scenarios with different debris densities. We then consider combinations of these primitive algorithms, which allow mobile robots to adapt to the local surrounding conditions. Through simulation evaluation, we find that a stochastic algorithm contributes to fast exploration by multiple mobile robots, regardless of debris density, while a deterministic algorithm is effective when used by a single agent.

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