Autonomous Drone Flight Path Planning for Object Imaging
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Solution Overview
Problem
Conventional visual inspection methods for manufactured parts are subjective, error-prone, and expensive due to reliance on manual inspectors and manual operation of drones, resulting in unsatisfactory data collection for photogrammetry.
Innovation Solution
A digital-representation-based system for flight path planning that generates an image acquisition plan (IAP) using a digital representation of an object to extract a 2D surface contour, generate a bounding polygon, and create waypoints for autonomous drones or rovers to follow, enabling precise imaging and action performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual inspection by human inspectors with cameras is used, then flexibility and adaptability are maintained, but subjectivity, error-proneness, and high costs occur
Solution Approach 1:
The system enables autonomous drones to self-navigate along pre-planned flight paths and automatically capture images without continuous human intervention. The autonomous mobile device independently executes the image acquisition plan, reducing reliance on manual operation while maintaining inspection quality.
Solution Approach 2:
The system performs preliminary actions by generating comprehensive image acquisition plans before drone execution. The flight path planning, waypoint generation, and camera parameter configuration are all prepared in advance based on digital representations of the objects to be inspected, enabling automated execution without real-time human control.
2Extent of automation
If autonomous flight path planning is implemented, then automation and precision are improved, but system complexity increases
Solution Approach 1:
The system introduces an intermediary image acquisition plan generation system that acts as a mediator between simple digital representation input and complex autonomous drone execution. This intermediary layer translates object digital representations into detailed flight paths and camera commands, enabling autonomous operation without requiring the drone itself to be overly complex.
Solution Approach 2:
The system uses digital representations (copies) of the objects to be inspected to plan flight paths and determine camera positions. By working with digital models rather than directly controlling physical inspection processes, the system achieves high automation while keeping the actual drone hardware relatively simple.
3Measurement precision
If conventional manual drone operation is used, then ease of operation is maintained, but data quality for photogrammetry becomes unsatisfactory
Solution Approach 1:
The system performs preliminary calculation of optimal flight paths, camera positions, and imaging parameters before drone execution. By pre-planning the entire inspection mission based on digital object representations, the system ensures high measurement precision for photogrammetry while reducing the operational complexity during actual execution.
Solution Approach 2:
The system replaces manual mechanical control of drones with automated computational control. Flight paths are calculated algorithmically based on digital representations, and camera parameters are automatically configured, substituting human mechanical operation with computational automation to achieve superior data quality.
Data Source
AI summary
A system and method for digital-representation-based flight path planning for object imaging is disclosed. An example embodiment is configured to: obtain a digital representation of an object; retrieve a dataset of image acquisition configuration parameters; extract a surface contour of the object from the digital representation of the object; generate a bounding polygon adjacent to the surface contour of the object, the bounding polygon being set-off from the surface contour of the object based on a configuration defined in the image acquisition configuration parameters; generate a configurable quantity of waypoints at configurable intervals along the bounding polygon; and generate an Image Acquisition Plan (IAP) from the waypoints, the IAP including, for each waypoint, a waypoint position, control instructions, and imaging instructions.