UAV Flight Path Control for Dynamic 3D Object Tracking
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Solution Overview
Problem
Existing flight control systems for aerial vehicles require significant manual input and aviation experience, struggle with tracking objects that dynamically change shape, size, or orientation, and are inadequate in environments with obstacles or poor GPS signal reception.
Innovation Solution
A system that uses intuitive human-system interfaces to control aerial vehicles, allowing automatic flight paths defined relative to object parameters, enabling obstacle avoidance and tracking without manual input, even in complex environments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual flight control is used, then the aerial vehicle can be operated with existing control systems, but the operator requires aviation experience and significant manual input
Solution Approach 1:
The patent introduces an intermediary computing device that acts as a mediator between the operator and the aerial vehicle. This device generates control commands based on images captured by the aerial vehicle and automatically adjusts flight parameters, eliminating the need for operators to directly control the vehicle while maintaining simple operation through image-based feedback.
Solution Approach 2:
The system enables the aerial vehicle to perform self-service flight control by automatically adjusting its flight path and parameters based on images captured during flight. The computing device processes images and generates control commands that allow the vehicle to autonomously navigate and track targets without continuous manual intervention.
2Extent of automation
If automatic flight control is implemented, then manual input is reduced, but the system struggles to track objects that dynamically change shape, size, or orientation
Solution Approach 1:
The patent implements dynamic tracking by continuously analyzing images captured during flight and automatically adjusting flight parameters based on the target object's changing characteristics. The system adapts to dynamic changes in shape, size, or orientation by processing real-time image data and modifying control commands accordingly, enabling reliable tracking of moving or transforming objects.
Solution Approach 2:
The system employs feedback mechanisms where images captured by the aerial vehicle are processed by a computing device that generates control commands based on the analyzed visual information. This closed-loop feedback allows the system to automatically adjust to changing target characteristics and maintain accurate tracking without manual intervention.
3Reliability
If complex flight trajectories are used to navigate around obstacles, then obstacle avoidance is improved, but manual control becomes more difficult
Solution Approach 1:
The aerial vehicle performs self-service obstacle avoidance by automatically analyzing the environment through captured images and generating control commands that navigate around obstacles. The system independently handles complex trajectory adjustments without requiring manual input from the operator, maintaining both safety and ease of operation.
Solution Approach 2:
The computing device acts as an intermediary that processes environmental information from images and generates appropriate control commands for obstacle avoidance. This mediator handles the complexity of navigating around obstacles while presenting a simple interface to the operator, eliminating the need for manual control of complex avoidance maneuvers.
4Adaptability or versatility
If GPS-based control is used, then flight paths can be predefined, but the system fails in environments with poor GPS signal reception
Solution Approach 1:
The patent replaces GPS-based positioning with a vision-based control system that uses images captured by the aerial vehicle for navigation and target tracking. This substitution eliminates dependence on GPS signals, enabling reliable operation in environments with poor or no GPS reception while maintaining adaptability to various operational environments.
Solution Approach 2:
The computing device serves as an intermediary that processes image data to determine position and generate control commands, replacing the GPS system as the primary navigation reference. This mediator enables the system to operate reliably in GPS-denied environments by using visual information from captured images for positioning and path planning.
Data Source
AI summary
A system for controlling a movable object includes a controller in communication with an analyzer and configured to obtain one or more parameters of a target object, obtain signals indicating one or more motion characteristics of the movable object and one or more motion path parameters, determine a motion path for the movable object to travel based on the one or more parameters of the target object and the one or more motion path parameters, and control the movable object to travel along the motion path based on the one or more motion characteristics of the movable object. The motion path is a three-dimensional (3D) motion path defined based on a contour of the target object. A change in a shape, geometry, or orientation of the contour of the target object results in a corresponding change of the 3D motion path.