  Localization between a swarm of AUVs can be entirely estimated through the
use of range measurements between neighboring AUVs via a class of techniques
commonly referred to as sensor network localization. However, the localization
quality depends on network topology, with degenerate topologies, referred to as
low-rigidity configurations, leading to ambiguous or highly uncertain
localization results. This paper presents tools for rigidity-based analysis,
planning, and control of a multi-AUV network which account for sensor noise and
limited sensing range. We evaluate our long-term planning framework in several
two-dimensional simulated environments and show we are able to generate paths
in feasible time and guarantee a minimum network rigidity over the full course
of the paths.
