Phased-Array Driving for Mid-Air Haptics
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Solution Overview
Problem
Existing phased array systems for mid-air haptics and acoustic levitation face challenges in creating consistent haptic experiences due to changes in control point behavior when moved dynamically, and existing optimization methods are inefficient and limited in scalability and strength, failing to effectively utilize vector components of sound waves for haptic feedback.
Innovation Solution
The development of a method that uses eigensystem solutions and complex-valued linear systems to optimize acoustic field control, incorporating psychohaptic modeling for dynamic range reduction and efficient complex-valued multiplication, enabling the creation of stable trap points and vector-controlled haptic feedback by leveraging the BKM algorithm for efficient hardware implementation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If control points are moved dynamically through space in existing phased array systems, then spatial flexibility is improved, but haptic consistency deteriorates due to changes in control point behavior and counter-intuitive haptic function changes
Solution Approach 1:
The system dynamically adjusts control point parameters including amplitude, phase, and spatial position in real-time to maintain consistent haptic perception as control points move through space. The eigensystem solver continuously recalculates optimal transducer coefficients to compensate for changes in control point behavior during movement.
Solution Approach 2:
The patent modifies multiple parameters simultaneously including pressure amplitude, particle velocity vector direction, and phase relationships to maintain consistent haptic effects. The system solves for complex-valued transducer coefficients that account for both magnitude and phase changes required to preserve haptic consistency during dynamic control point movement.
2Reliability
If existing non-linear optimization systems are used to create trap points, then acoustic levitation capability is achieved, but system efficiency deteriorates due to expensive and time-consuming optimization processes
Solution Approach 1:
The patent replaces traditional iterative non-linear optimization algorithms with an analytical eigensystem solution approach. By formulating the acoustic field control problem as an eigenvalue problem, the system obtains direct solutions for optimal transducer coefficients without requiring time-consuming iterative optimization, significantly improving computational efficiency while maintaining accurate trap point creation.
Solution Approach 2:
The system pre-calculates eigensystem solutions and stores them for rapid retrieval and application. By preparing optimization solutions in advance through eigendecomposition of the system matrix, the patent enables fast computation of trap point parameters when needed, eliminating the need for real-time iterative optimization during actual acoustic levitation operations.
3Reliability
If existing optimization methods are used, then trap points can be created, but trap strength deteriorates due to failure to properly utilize vector components of sound waves
Solution Approach 1:
The patent extends optimization from scalar pressure control to vector-based control by solving for complex-valued coefficients that independently control both amplitude and phase of acoustic waves. This allows precise manipulation of particle velocity vectors to create stronger, more stable trap points by properly utilizing the vector components of sound waves including directional energy flow and momentum transfer.
Solution Approach 2:
The system transitions from scalar pressure optimization to vector field optimization by incorporating directional information through complex-valued transducer coefficients. This adds the dimension of phase control and vector direction to the optimization problem, enabling creation of stronger trap points through coherent superposition of acoustic wave vectors rather than simple scalar pressure addition.
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
This approach allows for consistent haptic experiences across dynamic control points, enhances the strength and scalability of acoustic levitation, and improves the effectiveness of mid-air haptics by accurately manipulating vector components of sound waves, leading to more immersive and reliable haptic feedback.
Implementation Method 1
A continuous distribution of sound energy, which we will refer to as an 'acoustic field', can be used for a range of applications including haptic feedback in mid-air.
Implementation Method 2
it has been shown that a general non-linear optimization system can be used to produce trap points in the air
Implementation Method 3
The minimum size and maximum power of the control points created by the device are dependent on the array layout, geometry and relative location of the control point or points to be created
Data Source
AI summary
Various techniques for driving phased array systems are described, specifically intended for acoustic phased arrays with applications to mid-air haptics, parametric audio, acoustic levitation and acoustic imaging, including a system: 1) that is capable of mitigating the effect of the changes in the air to provide a consistent haptic experience; 2) that produces trap points in air; 3) that defines phased-array optimization in terms of vectors for the production of more consistent haptic effects; 4) that defines one or more control points or regions in space via a controlled acoustic field; 5) that uses a reduced representation method for the construction of acoustic basis functions; 6) that performs efficient evaluation of complex-valued functions for a large quantity of throughput; 7) that generates a Krylov sub-space of a matrix; and 8) that maximizes an objective described by different control points and/or regions to those used to create the acoustic basis functions.