Sim-in-Real: Digital Twin Based UAV Inspection Process

Zhang, Jihan; Wang, Ruoyu; Yang, Guidong; Liu, Kangcheng; Gao, Chuanxiang; Yu, Zhengquan; Chen, Xi; Chen, Ben M.

doi:10.1109/icuas54217.2022.9836043

Cited by 9 publications

(1 citation statement)

References 23 publications

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“…UAVs have great potential to perform various tasks such as mapping [1] [2], inspection [3][4] [5], search and rescue [6] [7], and others. Most of the tasks require the UAV to achieve a higher level of autonomy and this matter is very challenging especially for a small sized UAV due to its weight and size constraints.…”

Section: Introductionmentioning

confidence: 99%

Safe Avoidance Region Detection for Unmanned Aerial Vehicle Using Cues from Expansion of Feature Points

Bin Ramli,

Sutjipto,

Sulaeman

et al. 2024

Engineering Headway

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Develop an obstacle detection system for Unmanned Aerial Vehicle (UAV) especially for small UAV is challenging. A robust system should be able to not only detect obstacles but the free region for the avoidance path as well. Besides, the configuration of the obstacles in the operating environment should never be disregard. In this paper, expansion cues from the detected feature points with the help of convex hull will be used to categorize the regions in the image frame. A micro LIDAR sensor is used as the initial detector of obstacle and queue for image capturing by the camera. Next, ORB algorithm is applied to find the obstacle regions and free space regions. This is done through the principal of object size changes and distance relationship in an image perspective. The proposed system was evaluated through series of experiments in a real environment which consist of different configuration of obstacles. The experiments show the proposed system was able to find the safe avoidance region regardless of the configuration of the obstacles in the operating environment. Keywords: Expansion cue; ORB; Feature points; Safe avoidance region

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Section: Introductionmentioning

confidence: 99%

Safe Avoidance Region Detection for Unmanned Aerial Vehicle Using Cues from Expansion of Feature Points

Bin Ramli,

Sutjipto,

Sulaeman

et al. 2024

Engineering Headway

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

Nguyen,

Le,

Torres Herrera

et al. 2024

Constr Robot

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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.

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Digital-PV: A digital twin-based platform for autonomous aerial monitoring of large-scale photovoltaic power plants

Kolahi,

Esmailifar,

Moradi Sizkouhi

et al. 2024

Energy Conversion and Management

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Sim-in-Real: Digital Twin Based UAV Inspection Process

Cited by 9 publications

References 23 publications

Safe Avoidance Region Detection for Unmanned Aerial Vehicle Using Cues from Expansion of Feature Points

Safe Avoidance Region Detection for Unmanned Aerial Vehicle Using Cues from Expansion of Feature Points

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

Digital-PV: A digital twin-based platform for autonomous aerial monitoring of large-scale photovoltaic power plants

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