Task Coordination and Trajectory Optimization for Multi-Aerial Systems via Signal Temporal Logic: A Wind Turbine Inspection Study

TL;DR

This paper introduces a novel method for task allocation and trajectory planning in multi-aerial drone systems for wind turbine inspection, utilizing Signal Temporal Logic to ensure safety, feasibility, and adaptability to unexpected events.

Contribution

It develops an STL-based optimization framework with event-triggered replanning and robustness scoring, advancing cooperative drone inspection capabilities.

Findings

Validated through MATLAB and Gazebo simulations.

Demonstrated effective handling of unexpected events.

Achieved safe and feasible trajectories in real-world scenarios.

Abstract

This paper presents a method for task allocation and trajectory generation in cooperative inspection missions using a fleet of multirotor drones, with a focus on wind turbine inspection. The approach generates safe, feasible flight paths that adhere to time-sensitive constraints and vehicle limitations by formulating an optimization problem based on Signal Temporal Logic (STL) specifications. An event-triggered replanning mechanism addresses unexpected events and delays, while a generalized robustness scoring method incorporates user preferences and minimizes task conflicts. The approach is validated through simulations in MATLAB and Gazebo, as well as field experiments in a mock-up scenario.