KR-20260067419-A - INFRASTRUCTURE SAFETY INSPECTION SYSTEM USING AN AI-BASED GPS SHADED AREA AUTONOMOUS UNMANNED AERIAL VEHICLE.

KR20260067419AKR 20260067419 AKR20260067419 AKR 20260067419AKR-20260067419-A

Abstract

The present invention relates to an infrastructure facility safety inspection system using an artificial intelligence-based autonomous flight unmanned aerial vehicle in GPS blind spots. The infrastructure facility safety inspection system using an artificial intelligence-based GPS blind spot autonomous flight unmanned aerial vehicle according to the present invention includes: a replaceable variable rotor; an optical camera; a thermal imaging camera; a movable lidar sensor; a gyroscope sensor; an accelerometer sensor; a temperature sensor; a 3-axis laser rangefinder; an infrared sensor; an ultrasonic sensor; an RF sensor; an assembled frame; a remote controller capable of controlling the UAV; a controller that performs wired or wireless remote control of equipment and a shooting device; a control system; and a control unit equipped with an algorithm for controlling the artificial intelligence-based GPS blind spot autonomous flight unmanned aerial vehicle.

Inventors

이철희
구태회
김인수

Assignees

주식회사 딥인스펙션

Dates

Publication Date: 20260513
Application Date: 20241104

Claims (10)

Replaceable variable rotor; Optical camera; Thermal imaging camera; Mobile LiDAR sensor; Gyroscope sensor; Accelerometer; Temperature sensor; 3-axis laser rangefinder; Infrared sensor; Ultrasonic sensor; RF sensor; Prefabricated frame; A remote controller capable of controlling a UAV; A controller that performs wired and wireless remote control of equipment and imaging devices; Control system; and A control unit equipped with an algorithm for controlling an AI-based autonomous unmanned aerial vehicle in GPS blind spots. Infrastructure facility safety inspection system using an AI-based autonomous unmanned aerial vehicle for GPS blind spots, including
In paragraph 1, The above control unit analyzes signals received from the mobile lidar sensor, optical camera, and various sensors, and is equipped with a Fused Flow function that intelligently analyzes the position and path of the autonomous unmanned aerial vehicle, performs AI-based 3D point cloud, sensing data, and image analysis, and performs control for obstacle avoidance, collision prevention with obstacles, and direction change based on a Map-Based System. Infrastructure facility safety inspection system using AI-based autonomous unmanned aerial vehicles for GPS blind spots.
In paragraph 1, The above control unit controls commands to display 3D point cloud and positioning data of infrastructure facilities and surrounding conditions on the monitoring equipment screen of the control system, and provides a function to display the predicted movement path of the autonomous unmanned aerial vehicle. Infrastructure facility safety inspection system using AI-based autonomous unmanned aerial vehicles for GPS blind spots.
In paragraph 1, The above variable rotor is provided in a preset number of replaceable types, up to three types, to respond to surrounding environments such as the height, width, and shape of infrastructure facilities including wind speed. Infrastructure facility safety inspection system using AI-based autonomous unmanned aerial vehicles for GPS blind spots.
In paragraph 2, Performing AI-based 3D point cloud, sensing data, and image analysis, and forming a Safety Zone at a certain distance from infrastructure facilities and obstacles to account for the positioning error of the UAV in order to perform obstacle avoidance, collision prevention with obstacles, and control for changing direction, and providing an infographic related to the formed Safety Zone to the user, while simultaneously providing a function for the autonomous unmanned aerial vehicle to return to the starting point without colliding with obstacles in the event of an emergency. Infrastructure facility safety inspection system using AI-based autonomous unmanned aerial vehicles for GPS blind spots.
In paragraph 1, The above control unit explains the reasons for estimating cracks and defects in text based on a Feature Ablation algorithm, and highlights key features serving as the basis for the crack and defect estimation on the image as a heatmap (a contour-shaped heat map). Infrastructure facility safety inspection system using AI-based autonomous unmanned aerial vehicles for GPS blind spots.
In paragraph 1, The above-mentioned AI-based GPS blind spot autonomous unmanned aerial vehicle includes a positioning system dedicated to bridge facilities, comprising a gyroscope, accelerometer, temperature sensor, 3-axis laser rangefinder, 3D LiDAR, a vision camera for obstacle recognition, and a multi-modal map-based algorithm attached for positioning under the bridge. Infrastructure facility safety inspection system using AI-based autonomous unmanned aerial vehicles for GPS blind spots.
In paragraph 1, Includes a multi-modal map-based 3D simulator for performing sub-functions including collision prevention with bridges, localization and mapping, obstacle avoidance, and path planning for the above-mentioned AI-based autonomous flight unmanned aerial vehicle in GPS blind spots. Infrastructure facility safety inspection system using AI-based autonomous unmanned aerial vehicles for GPS blind spots.
In paragraph 8, The above 3D simulator includes the function of setting the locations of the approach point, obstacles, start, and destination of the AI-based GPS blind spot autonomous flight unmanned aerial vehicle, and the function of uploading the entire 2D/3D map to implement Sim-to-Real generalization. Infrastructure facility safety inspection system using AI-based autonomous unmanned aerial vehicles for GPS blind spots.
In paragraph 1, The above control unit performs control using a deep learning algorithm that outputs the turning angle and collision status of the UAV using a single 2D color image as input in a GPS blind spot. Infrastructure facility safety inspection system using AI-based autonomous unmanned aerial vehicles for GPS blind spots.

Description

Infrastructure Safety Inspection System Using an AI-Based GPS-Shaded Area Autonomous Unmanned Aerial Vehicle The present invention relates to an infrastructure facility safety inspection system using an artificial intelligence-based autonomous flight unmanned aerial vehicle in GPS blind spots. This invention was derived from research conducted with the support of the 2023 Daejeon-type Convergence New Industry Creation Special Zone Technology Demonstration Leading Project "Demonstration of a Subscription Service for Safety Inspection of XAI-based Infrastructure Facilities" (Research period: December 5, 2023 – November 4, 2024), funded by Daejeon Metropolitan City and the Daejeon Science & Industry Promotion Agency. According to conventional technology, an unmanned aerial vehicle (UAV) uses four or six rotors to approach the surface of the superstructure and substructure of a bridge facility and inspect the exterior of the bridge facility. However, when flying in a GPS blind spot under the bridge superstructure, the autonomous flight function does not operate and the performance of the obstacle detection function is degraded, leading to problems such as the unmanned aerial vehicle colliding with the surface of the bridge superstructure and substructure or degrading image quality. FIG. 1 illustrates a positioning system dedicated to the lower part of a bridge structure, comprising an IMU (inertial navigation unit), a gyroscope sensor, a temperature sensor, a 3-axis laser rangefinder, a 3D LiDAR, a vision camera for obstacle recognition, and a multi-modal map-based artificial intelligence algorithm attached to the UAV body for positioning of the UAV according to an embodiment of the present invention. FIG. 2 is a system configuration diagram of an intelligent unmanned aerial vehicle device for a bridge facility according to an embodiment of the present invention. FIG. 3 illustrates an intelligent robot camera dedicated to bridge facilities according to an embodiment of the present invention. FIG. 4 is a configuration diagram of a subscription-based artificial intelligence-based infrastructure facility safety inspection platform, such as bridge facilities, according to an embodiment of the present invention. FIG. 5 is a UI of a subscription-based artificial intelligence-based infrastructure facility safety inspection platform, such as bridge facilities, according to an embodiment of the present invention. FIG. 6 is a configuration diagram of an explainable artificial intelligence model according to an embodiment of the present invention. Figure 7 is an image output result of a Feature Ablation explainable artificial intelligence model according to an embodiment of the present invention (Center: correct answer, Right: output result). FIG. 8 is a configuration diagram of a Feature Ablation explainable artificial intelligence model and a data processing/visualization process according to an embodiment of the present invention. FIG. 9 is an image output result of a Feature Ablation explainable artificial intelligence model according to an embodiment of the present invention (Center: correct answer, Right: output result). Figure 10 is a feature ablation visualization process according to an embodiment of the present invention. FIG. 11 is a block diagram showing a computer system for implementing a method according to an embodiment of the present invention. FIG. 12 illustrates a process for outputting the positioning, turning angle, and collision status of a UAV in a GPS denied zone according to an embodiment of the present invention, using various sensing data as input. FIG. 13 illustrates a conceptual diagram of a deep learning algorithm that outputs the turning angle and collision status of a UAV using a single image as input in a GPS shadow area according to an embodiment of the present invention. The aforementioned objectives of the present invention, as well as other objectives, advantages, and features, and the methods for achieving them, will become clear from the embodiments described in detail below together with the accompanying drawings. However, the present invention is not limited to the embodiments disclosed below but can be implemented in various different forms, and the following embodiments are provided merely to easily inform those skilled in the art of the purpose, structure, and effects of the invention, and the scope of the rights of the present invention is defined by the description in the claims. Meanwhile, the terms used in this specification are for describing the embodiments and are not intended to limit the invention. In this specification, the singular form includes the plural form unless specifically stated otherwise in the text. As used in this specification, "comprises" and/or "comprising" do not exclude the presence or addition of one or more other components, steps, actions, and/or elements to the mentioned components, steps, actions, and/or elements. FIG. 1 illustrates a positioning