Multi-UAV trajectory planning for 3D visual inspection of complex structures

Abstract

The application of autonomous UAVs to infrastructure inspection tasks provides benefits in terms of operation time reduction, safety, and cost-effectiveness. This paper presents trajectory planning for three-dimensional autonomous multi-UAV volume coverage and visual inspection of infrastructure based on the Heat Equation Driven Area Coverage (HEDAC) algorithm. The method generates trajectories using a potential field and implements distance fields to prevent collisions and to determine UAVs' camera orientation. It successfully achieves coverage during the visual inspection of complex structures such as a wind turbine and a bridge, outperforming a state-of-the-art method by allowing more surface area to be inspected under the same conditions. The presented trajectory planning method offers flexibility in various setup parameters and is applicable to real-world inspection tasks. Conclusively, the proposed methodology could potentially be applied to different autonomous UAV tasks, or even utilized as a UAV motion control method if its computational efficiency is improved.

Revised abstract, references and captions, 17 pages

References in corpus (3)

• Enhanced discrete particle swarm optimization path planning for UAV vision-based surface inspection
• Constrained multi-agent ergodic area surveying control based on finite element approximation of the potential field
• Distributed Coverage Control of Multi-Agent Systems in Uncertain Environments using Heat Transfer Equations

Cited by in corpus (8)

• A Review on Viewpoints and Path-planning for UAV-based 3D Reconstruction
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• Distributed Control for 3D Inspection using Multi-UAV Systems
• Automated Real-Time Inspection in Indoor and Outdoor 3D Environments with Cooperative Aerial Robots
• Rolling Horizon Coverage Control with Collaborative Autonomous Agents
• Model predictive altitude and velocity control in ergodic potential field directed multi-UAV search
• Ergodic Trajectory Optimization on Generalized Domains Using Maximum Mean Discrepancy
• Invisible Servoing: a Visual Servoing Approach with Return-Conditioned Latent Diffusion