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In this paper, we present an approach for dynamic exploration and mapping ofunknown environments using a swarm of biobotic sensing agents, with astochastic natural motion model and a leading agent (e.g., an unmanned aerialvehicle). The proposed robust mapping technique constructs a topological map ofthe environment using only encounter information from the swarm. A slidingwindow strategy is adopted in conjunction with a topological mapping strategybased on local interactions among the swarm in a coordinate-free fashion toobtain local maps of the environment. These maps are then merged into a globaltopological map which can be visualized using a graphical representation thatintegrates geometric as well as topological feature of the environment.Localized robust topological features are extracted using tools fromtopological data analysis. Simulation results have been presented to illustrateand verify the correctness of our dynamic mapping algorithm.

Dynamic Topological Mapping with Biobotic Swarms