Autonomous UAV Image Capture With Dynamic Subject Tracking
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Solution Overview
Problem
Current UAV systems for image capture require piloting expertise and are prone to crashes due to pilot error, as they necessitate direct control of pitch, roll, yaw, and power adjustments, which can be complex and error-prone.
Innovation Solution
An autonomous UAV system that uses visual inertial odometry, computer vision, and a network of phased array wireless transceivers for localization and navigation, allowing it to adjust its flight path and image capture settings dynamically to maintain a clear line of sight with a subject and avoid obstacles without human intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If direct control of pitch, roll, yaw, and power is used for UAV piloting, then the UAV can be precisely controlled, but the system becomes complex and error-prone requiring expert piloting skills
Solution Approach 1:
The UAV system performs self-navigation and self-image-capture using autonomous algorithms. The system automatically tracks subjects, adjusts flight paths, and captures images without human intervention, eliminating the need for expert piloting while maintaining reliable operation through onboard computer vision and inertial odometry systems
Solution Approach 2:
The patent replaces manual mechanical control (joystick, throttle) with automated software-based control systems. The flight control system uses computer vision algorithms and inertial measurement units to automatically adjust pitch, roll, and yaw, substituting human-operated mechanical controls with electronic automation that reduces complexity and errors
2Reliability
If autonomous navigation systems with computer vision and phased array transceivers are implemented, then piloting errors are eliminated, but the device complexity increases
Solution Approach 1:
The UAV system integrates multiple functions into unified subsystems. The flight control system simultaneously handles navigation, obstacle detection, and image capture coordination. The phased array transceiver serves both communication and localization functions, reducing overall system complexity through multi-functional integration rather than separate dedicated systems
Solution Approach 2:
The patent introduces an autonomous flight controller as an intermediary between the complex navigation algorithms and the actual flight control mechanisms. This intermediary layer processes computer vision data and inertial odometry information, then translates it into simplified control commands for the flight actuators, managing complexity through hierarchical control architecture
3Manufacturing precision
If the UAV dynamically adjusts flight path and image capture settings to maintain clear line of sight, then image quality improves, but the control system becomes more complex
Solution Approach 1:
The system dynamically adjusts both flight path and image capture parameters in real-time based on subject position and environmental conditions. The flight controller continuously modifies altitude, position, and orientation while the image capture system simultaneously adjusts focus, exposure, and framing, creating a coordinated dynamic response that maintains optimal image quality without requiring complex manual intervention
Solution Approach 2:
The autonomous image capture system uses real-time feedback from computer vision algorithms to monitor subject position and image quality metrics. This feedback loop automatically triggers flight path adjustments and camera parameter changes when subjects move or lighting conditions change, maintaining high image quality through continuous automated optimization rather than static pre-configuration
Data Source
AI summary
Methods and systems are disclosed for an unmanned aerial vehicle (UAV) configured to autonomously navigate a physical environment while capturing images of the physical environment. In some embodiments, the motion of the UAV and a subject in the physical environment may be estimated based in part on images of the physical environment captured by the UAV. In response to estimating the motions, image capture by the UAV may be dynamically adjusted to satisfy a specified criterion related to a quality of the image capture.