  The process of planning views to observe a scene is known as the Next Best
View (NBV) problem. Approaches often aim to obtain high-quality scene
observations while reducing the number of views, travel distance and
computational cost.
  Considering occlusions and scene coverage can significantly reduce the number
of views and travel distance required to obtain an observation. Structured
representations (e.g., a voxel grid or surface mesh) typically use raycasting
to evaluate the visibility of represented structures but this is often
computationally expensive. Unstructured representations (e.g., point density)
avoid the computational overhead of maintaining and raycasting a structure
imposed on the scene but as a result do not proactively predict the success of
future measurements.
  This paper presents proactive solutions for handling occlusions and
considering scene coverage with an unstructured representation. Their
performance is evaluated by extending the density-based Surface Edge Explorer
(SEE). Experiments show that these techniques allow an unstructured
representation to observe scenes with fewer views and shorter distances while
retaining high observation quality and low computational cost.
