A multiple criteria decision support system for autonomous underwater vehicle mission planning and control

Abstract

The growing use of autonomous air, surface, ground and underwater systems is continually demonstrating new military and commercial possibilities and applications. The state of the art in the planning and control of autonomous underwater vehicles (AUVs) is largely precarious because AUVs provide infrequent feedback, operate autonomously for long periods of time and yet have little knowledge of their dynamic environment. Consequently, mission planning and control is typically conducted based on human expert knowledge of vehicle capabilities, some level of observed environmental conditions and ad hoc optimisation with little assistance from computers. While the human expert offers a significant ability to mentally process data, the result typically lacks numeric and quantitative analysis of alternatives. Navigation of AUVs in the complex ocean environment involves time dependent dynamics, resulting in a problem that is computationally prohibitive for the use of brute force optimisation techniques. Although some research has been conducted for specific types of missions, and 'greedy' global-optimisation approaches have been investigated, no systematic and coherent approach to the requirement exists. We propose a dynamic multiple criteria decision support system that considers dynamic and episodic ocean phenomenon to provide reasonable and in-context recommendations with respect to the stated objective and subjective mission goals. Multi-criteria decision analysis, analytic network process and fuzzy sets are used in the model to reduce the vehicle routing solution space and maximise time-on station in adverse environments. The proposed system can be an added hierarchical layer on the top of a mission planning system currently under development by the United States Navy.

A Comprehensive Review of Path Planning Algorithms for Autonomous Underwater Vehicles

“…•Energy optimal paths are obtained by exploiting ocean currents •Less susceptible to "large local minima" when the "cost surface" is complex •Computational complexity increases for higher dimensional problems Unpredictable Dynamic MCDA [94,95] Energy optimal Poor Moderate…”

Cloud-Based Multi-Robot Path Planning in Complex and Crowded Environment with Multi-Criteria Decision Making Using Full Consistency Method

“…In reality, there are usually more such factors. Dynamic decision support system (DSS) for mission planning and control of autonomous underwater vehicles (AUVs) in complex environments with real-world operational constraints is proposed in [31]. The component of DSS that is intended to reduce the AUV path solution space in complex environments is based on a MCDM while using the analytic network process (ANP) and fuzzy logic.…”

A Multi-Criteria Decision Support System for a Routing Problem in Waste Collection

“…Later, in 2010, Tavana and Bourgeois [38] focused on the problem of operational planning and navigation of autonomous underwater vehicles. A dynamic multiple criteria support system was developed and the authors employed MCDA methods, along with other methodologies, to assist in mission planning carried out by the United States Navy.…”