A Dynamic Task Scheduling Method for Multiple UAVs Based on Contract Net Protocol.

Area of Science:

• Robotics and Automation
• Disaster Management
• Operations Research

Background:

• Unmanned aerial vehicles (UAVs) are increasingly vital for disaster relief operations, including communication, supply delivery, and mapping.
• Effective dynamic task scheduling is crucial for managing emergent tasks during disaster response.

Purpose of the Study:

• To develop a multi-constraint mathematical model for dynamic task scheduling of multiple UAVs.
• To address the objectives of maximizing task profit, minimizing time consumption, and balancing task loads across UAVs.
• To propose a novel dynamic task scheduling method using a hybrid contract net protocol.

Main Methods:

• Construction of a multi-constraint mathematical model for multi-UAV dynamic task scheduling.
• Conversion of a multi-objective problem into a single-objective optimization using the weighted sum method.
• Development of a hybrid contract net protocol with buy-sell, swap, and replacement contracts.

Main Results:

• The proposed hybrid contract net protocol effectively handles dynamic task scheduling for multi-UAV systems.
• Simulations demonstrated the method's superiority in scenarios involving emergency tasks, obstacles, and platform failures.
• The approach successfully balances task profit maximization, time minimization, and workload distribution.

Conclusions:

• The novel dynamic task scheduling method enhances the efficiency and effectiveness of UAVs in disaster relief operations.
• The hybrid contract net protocol provides a robust framework for complex, dynamic task allocation in multi-UAV systems.
• This research contributes to optimizing resource management for autonomous systems in critical situations.