UAV Structure Scan Planning With Autonomous Docking and Charging
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Solution Overview
Problem
Existing unmanned aerial vehicles (UAVs) face limitations in performing robust, fully autonomous structure scans due to battery life constraints and the need for human intervention during charging, and they struggle with maintaining consistent distance and orientation during imaging, which affects the accuracy and efficiency of structure maintenance detection.
Innovation Solution
Implementing an unmanned aerial vehicle system with automated docking and charging capabilities, visual inertial odometry for localization, and a scan plan execution that adjusts to obstacles, allowing for consistent imaging and extended operation without human intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Duration of action of moving object
If automated docking and charging capabilities are implemented, then operation duration is extended and human intervention is reduced, but device complexity increases
Solution Approach 1:
The UAV system performs self-service through automated docking and charging capabilities. The vehicle autonomously navigates to the docking station, aligns itself, and recharges without human intervention, allowing extended operation periods. This self-service mechanism directly resolves the contradiction by enabling the system to maintain prolonged operational duration while managing its own energy needs.
Solution Approach 2:
The system implements preliminary action by pre-positioning the docking station at strategic locations and pre-planning recharge intervals. The docking infrastructure is established in advance, and the UAV autonomously schedules its return to dock before battery depletion, enabling continuous operation across multiple flight cycles without requiring real-time human decision-making.
2Measurement precision
If visual inertial odometry is used for localization, then positioning accuracy is improved, but computational requirements and processing time increase
Solution Approach 1:
The visual inertial odometry system operates continuously during flight, fusing data from cameras, GPS, and inertial sensors in real-time. This continuous processing maintains constant positioning accuracy without requiring post-flight computation or pausing the UAV for calculations, thereby minimizing processing time loss while maximizing measurement precision throughout the entire mission duration.
Solution Approach 2:
The system replaces traditional mechanical positioning methods with sensor-based visual and inertial measurement systems. By using optical flow, feature tracking, and inertial data fusion instead of purely mechanical or GPS-dependent positioning, the system achieves higher accuracy in challenging environments while processing data streams continuously to avoid time delays.
3Reliability
If scan plan execution adjusts to obstacles dynamically, then scanning reliability is improved, but scanning speed and productivity decrease
Solution Approach 1:
The scan plan execution system dynamically adapts to obstacles by continuously adjusting the UAV's flight path and imaging parameters in real-time. When obstacles are detected, the system recalculates the optimal scanning trajectory around obstructions while maintaining image overlap and coverage requirements. This dynamic adjustment ensures complete and reliable scanning of accessible areas without requiring manual intervention, balancing reliability with maintained productivity through automated path optimization.
Data Source
AI summary
Described herein are systems and methods for structure scan using an unmanned aerial vehicle. For example, some methods include accessing a three-dimensional map of a structure; generating facets based on the three-dimensional map, wherein the facets are respectively a polygon on a plane in three-dimensional space that is fit to a subset of the points in the three-dimensional map; generating a scan plan based on the facets, wherein the scan plan includes a sequence of poses for an unmanned aerial vehicle to assume to enable capture, using image sensors of the unmanned aerial vehicle, of images of the structure; causing the unmanned aerial vehicle to fly to assume a pose corresponding to one of the sequence of poses of the scan plan; capturing one or more images of the structure from the pose.