Optimized Waterspace Management and Scheduling Using Mixed-Integer Linear Programming

Abstract

We describe an approach for accomplishing the high-level mission planning required for a heterogeneous team of autonomous vehicles performing mine countermeasure (MCM) survey missions in multiple areas. The high-level mission scheduling and waterspace management requires sequencing the order and location of lower-level MCM tasks to be completed by each vehicle in the heterogeneous team: unmanned surface vessels (USVs) and unmanned underwater vehicles (UUVs). We propose solving this complex sequencing operation by leveraging unique information processing, communication, refueling, and planning windows that form constraints within the system within a formal scheduling optimization framework known as mixed-integer linear programming. We pose the problem using a mixed-integer linear programming optimization framework, compare several complexity reduction heuristics to the full optimization, and include methods to account for relative uncertainty in the duration of planned tasks in such a manner to balance the risk of schedule slips or conservative and sub-optimal schedule.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2016
Accession Number
AD1005254

Entities

People

  • Matthew J. Bays
  • Thomas Wettergren

Organizations

  • Naval Surface Warfare Center

Tags

Communities of Interest

  • Air Platforms
  • Autonomy

DTIC Thesaurus Topics

  • Aircrafts
  • Algorithms
  • Autonomous Systems
  • Computational Complexity
  • Deployment
  • Integer Programming
  • Linear Programming
  • Mathematical Models
  • Monte Carlo Method
  • Multiagent Systems
  • Optimization
  • Standards
  • Unmanned Aerial Vehicles
  • Unmanned Ground Vehicles
  • Unmanned Systems
  • Unmanned Underwater Vehicles
  • Unmanned Vehicles

Readers

  • Naval Mine Countermeasure Systems Development.
  • Parallel and Distributed Computing.
  • Team-Based Human-Centered Cognitive Task Decision Making and Information Performance.

Technology Areas

  • Autonomy
  • Autonomy - Human-Robot Interaction