  Navigation in cluttered underwater environments is challenging, especially
when there are constraints on communication and self-localisation. Part of the
fully distributed underwater navigation problem has been resolved by
introducing multi-agent robot teams, however when the environment becomes
cluttered, the problem remains unresolved. In this paper, we first studied the
connection between everyday activity of dog walking and the cooperative
underwater obstacle avoidance problem. Inspired by this analogy, we propose a
novel dog walking paradigm and implement it in a multi-agent underwater system.
Simulations were conducted across various scenarios, with performance
benchmarked against traditional methods utilising Image-Based Visual Servoing
in a multi-agent setup. Results indicate that our dog walking-inspired paradigm
significantly enhances cooperative behavior among agents and outperforms the
existing approach in navigating through obstacles.
