Ultrasonic Gesture Calibration for Reliable Vehicle Tailgate Opening
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Solution Overview
Problem
Existing vehicle systems for gesture-controlled opening of areas closed by movable components, such as trunk lids or tailgates, suffer from unreliable detection due to false positives and user intention misinterpretation, especially when using capacitive or ultrasonic sensors.
Innovation Solution
A method for calibrating an ultrasound-based gesture recognition algorithm by determining and storing a parameter value based on sensor signals during a user's gesture movement, accounting for person-specific characteristics to enhance recognition reliability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a small target area is used for capacitive sensor detection, then false-positive detection is reduced, but the user must enter a relatively small target area which reduces reliability in recognizing user intention
Solution Approach 1:
The system dynamically adjusts the target area size and detection sensitivity based on user calibration data. During calibration, the system learns the specific movement patterns of each user and adapts the detection parameters accordingly, allowing the target area to be effectively larger for recognized users while maintaining false-positive rejection
Solution Approach 2:
The system changes detection parameters (sensitivity thresholds, time profiles, movement characteristics) based on calibrated user data. By storing and comparing against user-specific parameter profiles, the system can distinguish between intentional gestures and false triggers, resolving the contradiction between detection accuracy and operational convenience
2Measurement precision
If ultrasonic sensors are used for gesture recognition, then time-dependent gesture characterization is possible, but movements may not be recognized as gestures since details differ depending on the person or user
Solution Approach 1:
The system performs preliminary calibration where users perform sample gestures that are stored as reference profiles. This preliminary action captures each user's specific movement characteristics, allowing the system to later recognize variations of these gestures without requiring exact parameter matching
Solution Approach 2:
The system uses feedback from calibrated user gestures to adjust recognition thresholds and parameters. By continuously comparing new gestures against stored user profiles and learning from the feedback, the system adapts to individual user movement patterns while maintaining consistent gesture recognition
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
The method increases the reliability of gesture recognition by personalizing the algorithm to individual user movements, reducing false positives and improving the accuracy of detecting intended gestures.
Implementation Method 1
a time-dependent first sensor signal is generated by means of an ultrasonic sensor (5) while a first person performs a gesture movement in a field of view of the ultrasonic sensor (5)
Data Source
AI summary
According to a method for calibrating a gesture recognition algorithm for the gesture-controlled opening of an area of a vehicle (1) closed by a movable component (3), a gesture recognition algorithm is provided in a computer-readable format which is adapted to recognize a predetermined gesture as a function of a time-dependent sensor signal of an ultrasonic sensor (5) of the vehicle (1). A time-dependent first sensor signal is generated by means of the ultrasonic sensor (5) while a first person (8) performs a gesture movement in a field of view of the ultrasonic sensor (5) and a first value of a predetermined parameter of the gesture recognition algorithm is determined and stored as a function of the first sensor signal.