  Underwater navigation is a challenging area in the field of mobile robotics
due to inherent constraints in self-localisation and communication in
underwater environments. Some of these challenges can be mitigated by using
collaborative multi-agent teams. However, when applied underwater, the
robustness of traditional multi-agent collaborative control approaches is
highly limited due to the unavailability of reliable measurements. In this
paper, the concept of a Virtual Elastic Tether (VET) is introduced in the
context of incomplete state measurements, which represents an innovative
approach to underwater navigation in confined spaces. The concept of VET is
formulated and validated using the Cooperative Aquatic Vehicle Exploration
System (CAVES), which is a sim-to-real multi-agent aquatic robotic platform.
Within this framework, a vision-based Autonomous Underwater Vehicle-Autonomous
Surface Vehicle leader-follower formulation is developed. Experiments were
conducted in both simulation and on a physical platform, benchmarked against a
traditional Image-Based Visual Servoing approach. Results indicate that the
formation of the baseline approach fails under discrete disturbances, when
induced distances between the robots exceeds 0.6 m in simulation and 0.3 m in
the real world. In contrast, the VET-enhanced system recovers to
pre-perturbation distances within 5 seconds. Furthermore, results illustrate
the successful navigation of VET-enhanced CAVES in a confined water pond where
the baseline approach fails to perform adequately.
