UAV Mission Planning Resistant to Weather Uncertainty

Area of Science:

• Robotics and Automation
• Operations Research
• Aerospace Engineering

Background:

• Fleet mission planning for Unmanned Aerial Vehicles (UAVs) is critical for achieving objectives over time.
• Large UAVs present unique challenges including weather variability, collision risks, and energy limitations.
• Existing methods struggle with dynamic environmental factors and complex constraints.

Purpose of the Study:

• To develop a declarative approach for robust UAV fleet mission planning resistant to weather uncertainty.
• To analyze the impact of mission parameters on operational outcomes and customer satisfaction.
• To provide a framework for assessing alternative UAV mission planning strategies.

Main Methods:

• A declarative approach was formulated to address complex mission planning problems.
• The approach was tested using several computational experiments and case studies.
• Analysis focused on the influence of fleet size, travel distance, wind direction, and speed.

Main Results:

• The proposed declarative approach demonstrates resilience against weather uncertainty.
• Computational experiments provide insights into the relationship between mission parameters and operational success.
• The study quantifies the influence of factors like fleet size and wind conditions on mission outcomes.

Conclusions:

• The declarative approach offers a viable solution for complex UAV fleet mission planning under uncertainty.
• Findings enable better assessment of various UAV mission planning strategies.
• Optimized planning can lead to improved operational efficiency and potentially customer satisfaction.