Naval Mine Countermeasure Missions
IEEE robotics & automation magazine
U ndersea operations using autonomous underwater vehicles (AUVs) provide a different and in some ways a more challenging problem than tasks for unmanned aerial vehicles and unmanned ground vehicles. In particular, in undersea operations, communication windows are restricted, and bandwidth is limited. Consequently, coordination among agents is correspondingly more difficult. In traditional approaches, a central planner initially assigns subtasks to a set of AUVs to achieve the team goal.
... those initial task assignments may become inefficient during real-time execution because of the real-world issues such as failures. Therefore, initial task allocations are usually subject to change if efficiency is a high concern. Reallocations are needed and should be performed in a distributed manner. To provide such flexibility, we propose a distributed auction-based cooperation framework, distributed and efficient multirobot-cooperation framework (DEMiR-CF) , which is an online dynamic task allocation (reallocation) system that aims to achieve a team goal while using resources effectively. DEMiR-CF, with integrated task scheduling and execution capabilities, can also respond to and recover from real-time contingencies such as communication failures, delays, range limitations, and robot failures. It has been implemented and tested extensively in the multirobot multitarget exploration domain  and in complex missions of interrelated and resource constrained tasks  . In this article, we report the performance of the framework against real-world difficulties encountered in multi-AUV coordination for the naval mine countermeasure (MCM) mission obtained through several experiments on the U.S. Navy's Autonomous Littoral Warfare Systems Evaluator-Monte Carlo (ALWSE-MC) simulator  . DEMiR-CF supports a distributed strategy for real-time task execution and is designed to use the advantages of auction-based approaches. Additional precaution routines are integrated into the framework to enhance solution quality. Other works in auction-based coordination research include Mþ , MUR-DOCH , TraderBots  , and the allocation scheme by Lemaire . According to the review given in , existing auction-based systems are not fully capable of replanning task distributions, redecomposing tasks, rescheduling commitments, and replanning coordination during execution. Our approach aims at filling these gaps. We propose an integrated cooperation framework for multirobot task execution and analyze the performance of the precaution routines and solution quality maintenance schemes for single-item auctions in a multi-AUV coordination context  . Experiments are performed in a realistic simulation environment with real-time constraints and events such as AUV failures and limitations, and delays in communication range. Precaution routines embedded into the framework not only recover from failures but also serve to