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Path Planning and Obstacle Avoidance of Formation Flight.

Yi-Sin Yang¹, Jih-Gau Juang¹

¹Department of Communications, Navigation and Control Engineering, National Taiwan Ocean University, Keelung 20224, Taiwan.

Sensors (Basel, Switzerland)

|April 26, 2025

Summary

This study enhances drone control for riverbank inspections using improved path planning and obstacle avoidance. Multiple drones ensure efficient, safe navigation through complex environments.

Keywords:

A* algorithm UAV formation flight genetic algorithm leader–follower algorithm obstacle avoidance path planning reinforcement Q-learning

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Area of Science:

Robotics and Automation
Artificial Intelligence
Environmental Monitoring

Background:

Riverbank inspections are crucial for environmental monitoring but challenging due to complex terrains.
Traditional inspection methods are time-consuming and potentially hazardous.
Unmanned Aerial Vehicles (UAVs) offer a promising solution for efficient and safe inspections.

Purpose of the Study:

To develop an advanced drone control system for autonomous riverbank inspections.
To enhance path planning and obstacle avoidance algorithms for UAVs operating in dynamic environments.
To improve the efficiency and reduce the time consumption of large-scale inspection tasks using multi-drone systems.

Main Methods:

An improved grid-based A* algorithm for optimal path planning.
Depth cameras and reinforcement Q-learning with a genetic algorithm for real-time obstacle avoidance.
Leader-follower formation flight control for coordinated multi-drone operations.

Main Results:

Successfully demonstrated autonomous navigation and obstacle avoidance in simulated complex riverbank environments.
Achieved efficient inspection coverage of large areas through coordinated multi-drone deployment.
Validated the effectiveness of the enhanced A* algorithm and Q-learning based avoidance system.

Conclusions:

The proposed drone control system significantly improves the feasibility and efficiency of riverbank inspections.
The integration of advanced path planning and obstacle avoidance enables robust UAV operation in challenging conditions.
Multi-drone systems with formation flight capabilities offer a scalable solution for comprehensive environmental monitoring.