UAV Gesture Control Using Image and Depth Sensing
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Solution Overview
Problem
Traditional methods for controlling movable devices like UAVs require additional devices, which can be inconvenient and difficult for users to learn, lacking intuitive control mechanisms.
Innovation Solution
A system that uses an image-collection component and a distance-measurement component to identify gestures from human body movements, generating instructions for the device without the need for additional controlling devices, utilizing machine learning processes to analyze and verify gestures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If traditional remote control devices are used to control movable devices, then control functionality is achieved, but device portability and ease of operation deteriorate due to the size and complexity of the controlling device
Solution Approach 1:
The movable device performs gesture recognition and control interpretation functions that traditionally required separate remote control devices. The system uses its own image collection component, distance measurement component, and processing units to detect and interpret gestures, making the device self-sufficient and eliminating the need for external controllers.
Solution Approach 2:
The patent extracts the control functionality from separate remote control devices and integrates it directly into the movable device. By embedding the image collection component, distance measurement component, and gesture recognition processing within the movable device itself, the system removes the need for external controlling devices while maintaining full control capabilities.
2Ease of operation
If traditional remote control devices are used to control movable devices, then control functionality is achieved, but user learning time and operational intuitiveness deteriorate
Solution Approach 1:
The patent replaces mechanical remote control interfaces with natural human gestures captured by image and distance sensing systems. Instead of requiring users to learn mechanical controller operations, the system interprets natural body movements and gestures, making the control interface intuitive and immediately understandable without training.
Solution Approach 2:
The system changes the control interface parameter from mechanical button/stick operations to natural gesture parameters. By detecting gesture characteristics such as body part positions, movement trajectories, and spatial relationships, the system translates natural human movements into control commands, eliminating the need for users to adapt to non-intuitive mechanical controls.
3Measurement precision
If single-type sensing components are used for gesture recognition, then system simplicity is maintained, but measurement precision and gesture identification accuracy deteriorate
Solution Approach 1:
The patent merges multiple sensing modalities within the movable device: an image collection component (camera) for capturing visual gesture information and a distance measurement component for obtaining depth data. By combining these different sensing types, the system achieves more accurate and reliable gesture recognition than either component could provide alone, while the integrated design keeps the overall system manageable.
Solution Approach 2:
The patent adds a depth dimension to gesture recognition by incorporating distance measurement component data alongside traditional 2D image data. This creates a 3D spatial understanding of gestures, allowing the system to accurately distinguish between gestures that may appear similar in 2D but differ in spatial positioning, significantly improving measurement precision.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables intuitive and straightforward control of movable devices like UAVs by eliminating the need for additional controlling devices, improving user experience and convenience through gesture recognition.
Implementation Method 1
generating an image corresponding to the operator by the image-collection component
Implementation Method 2
the distance-measurement component can be a distance-sensing or depth-sensing camera that can be used to measure distance based on a distance sensor (e.g., a time of flight (ToF) sensor)
Data Source
AI summary
Methods and associated systems and apparatus for controlling a moveable device are disclosed herein. The moveable device includes an image-collection component and a distance-measurement component. A representative method includes generating an image corresponding to the operator and generating a first set of distance information corresponding to the operator. The method identifies a portion of the image in the generated image and then retrieves a second set of distance information from the first set of distance information based on the identified image portion corresponding to the operator. The method then identifies a gesture associated with the operator based on the second set of distance information. The method then further generates an instruction for controlling the moveable device based on the gesture.