3 accepted papers
This letter presents a framework for planning and perception for multi-robot exploration in large and unstructured three-dimensional environments. We employ a Gaussian mixture model for global mapping to model complex environment geometries while maintaining a small memory footprint which enables di
Occupancy mapping is fundamental for active perception systems to enable reasoning about known and unknown regions of the environment. The majority of occupancy mapping approaches enforce an <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">a priori</i
This letter presents a robust Gaussian mixture model registration technique to enable mapping and navigation in dark, complex, unstructured domains such as caves and mines. Subterranean environments are often unmapped and challenged by low-lighting conditions and communication constraints. Prior wor