Work

Intelligent path planning for civil infrastructure inspection with multi-rotor aerial vehicles

Year: 2024

Type: article

Abstract: This paper presents the development of algorithms for high-level control and intelligent path planning of multi-rotor aerial vehicles (MAVs) in the tasks of inspecting civil infrastructure. After revisiting the multicopter modeling, we describe the hierarchy of high-level control for MAVs and develop optimization algorithms for generating optimal paths and enabling automatic flight during inspection tasks, making use of the digital twin technology. A co-simulation framework is then established to simulate and evaluate inspection mission scenarios, integrating these essential components. Real-world examples from built infrastructure illustrate this concept. An advantage of this approach is its ability to rigorously test, validate, verify, and evaluate MAV operations under abnormal conditions without requiring physical implementation or field tests. This significantly reduces testing efforts throughout the development cycle, ensuring optimal cooperation, safety, smoothness, fault tolerance, and energy efficiency. The methodology is validated through simulations and real-world inspection of a monorail bridge.

Source: Construction Robotics

DOI: 10.1007/s41693-024-00135-9

Authors: Lanh V. Nguyen, Trung H. Le, Ignacio Torres Herrera, Ngai M. Kwok, Quang P. Ha

Institutions: University of Technology Sydney, Western Sydney University

Language: English

Topic: Robotic Path Planning Algorithms

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: hybrid

Estimated APC paid: $3,090