A Signal Temporal Logic Approach for Task-Based Coordination of Multi-Aerial Systems: a Wind Turbine Inspection Case Study

2024-09-18

Robotics and Autonomous Systems

AI Summary

To address the challenges of cooperative path planning and task allocation for multi-UAV inspection of wind turbines, this paper proposes a distributed cooperative control framework based on Signal Temporal Logic (STL), explicitly encoding spatiotemporal constraints, energy budgets, and mission deadlines. Innovatively, STL quantitative robustness is integrated into multi-vehicle task coordination to enable verifiable temporal behavior specifications, real-time violation detection, and dynamic rescheduling. The framework combines distributed optimization with Model Predictive Control (MPC) and is validated in a ROS/Gazebo simulation environment. Experimental results demonstrate a 98.2% task completion rate, temporal violation detection latency under 100 ms, and a 37% reduction in communication overhead. The approach significantly enhances reliability, formal verifiability, and resource efficiency of multi-UAV collaborative inspection in complex environments.

Technology Category

• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Constraint Satisfaction and Optimization: Distributed CSP/Optimization
• Multiagent Systems: Multiagent Planning

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments
• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Economics, Online Markets and Human Computation: LLM based quality controls for crowd work

Problem

• Multi-Drone Coordination
• Wind Turbine Inspection
• Path Planning and Task Allocation

Innovation

• Multi-Drone Collaboration
• Optimized Task Allocation
• Adaptive Flight Planning