Haptic effects from focused acoustic fields

Abstract

To resolve an issue related to the calibration of optical cameras in transducer-based mid-air haptic systems, the magnification of the motion induced on an optical camera by an acoustic field modulated at specific frequencies reveals very small temporal variations in video frames. This quantized distortion is used to compare different acoustic fields and to solve the calibration problem in an automatized manner. Further, mechanical resonators may be excited by ultrasound when it is modulated at the resonant frequency. When enough energy is transferred and when operating at the correct frequency, a user in contact with the device can feel vibration near areas of largest displacement. This effect can be exploited to create devices which can produce haptic feedback while not carrying a battery or exciter when in the presence of an ultrasonic source.

Description

FIELD OF THE DISCLOSURE

The present disclosure relates generally to acoustically-driven haptic effects in mid-air haptic systems.

BACKGROUND

A continuous distribution of sound energy, referred to as an “acoustic field”, may be used for a range of applications including haptic feedback in mid-air.

In most applications, haptic feedback is generated by an array of transducers, and a user's gesture is recognized by means of an optical camera. By identifying the user's gesture and focusing the acoustic field onto the user, an action is performed and a specific haptic feedback may be provided as a response. Consider an in-vehicle gesture system as an example scenario. In this application, the array may be embedded in the dashboard, whereas the optical camera, needing to view the interaction space, would then be embedded in the roof of the vehicle interior. Their relative position, generally unknown and subject to variability, is a necessary piece of information to ensure that the acoustic field and its resulting haptic feedback is projected at the correct position in mid-air.

While different standard calibration procedures can be adopted to find the relative position between the array and the RGB camera, they all involve some hardware challenges and/or require active human intervention to perform calibration. Human intervention is difficult to achieve, and in the cases in which manual intervention is needed, makes for expensive and time-consuming solutions. For this reason, it is important to minimize human involvement, which makes calibration techniques that achieve this commercially valuable.

Three standard calibration procedures without human intervention are as follows:

• • 1) Microphones embedded in the camera, or positioned in its proximity, can be used to measure the acoustic field from the array. A minimum of three (or more) transducers at known array-referenced positions can be activated at different timings and the signals are received at the microphone. The signal can be a short pulse, chirp sine wave or modulated signal that encodes known points in time. Since the time-of-flight of more than 3 receivers is recorded, the problem becomes one of multilateration, a surveillance technique based on the measurement of the difference in distance to two stations at known locations by broadcast signals at known times. Weighted least squares optimization finds the minima of a cost function which consists of the sum of the squared residual, leading to the estimation of the relative position of the camera with respect to the array. Once the relative position of the camera is determined, a calibration of the system is obtained.
  • 2) A minimum of three or more receivers embedded in the haptic array can record a signal from a transmitting transducer embedded in the camera or in its proximity. The signal can be a short pulse, chirp sine wave or modulated signal that encodes known points in time. Since the time-of-flight of more than three receivers is recorded, the problem becomes one of multilateration. Weighted least squares optimization finds the minima of a cost function which consists of the sum of the squared residual, leading to the estimation of the relative position of the camera with respect to the array. Once the relative position of the camera is determined, a calibration of the system is obtained.
  • 3) One or more fiducial marks on the array, on its proximity or on the covering material, that are in each case visible to the camera can be captured optically. They can be a recognizable spot, or a distinguishable symbol. By comparing the frames acquired by the optical camera with an exemplar, it would be possible to compute the differences between the actual and the ideal position of the array with respect to the camera, and hence calibrate the system.

Presented herein is an alternative, cheaper and more elegant method to capture the same calibration information using only focused acoustic field and the optical camera. This is achieved by magnifying the sinusoidal motion induced by an acoustic field, produced by the array, on the output of the optical camera system. A focused acoustic field exerts forces on the optical camera which induces small motions of the camera. This results in equally small distortions in the image data captured by the camera system. Various techniques can be used to isolate this distortion and quantify temporal variations in videos and still images. The quantized distortion would then be utilized to compare different acoustic fields and perform the calibration.

Further, many applications for haptic feedback involve the vibrations originating from a device the user is holding. This can be as simple as a stylus which taps or vibrates to indicate a selection, or a handle meant to simulate a racket in virtual reality which vibrates as the user hits a (virtual) ball. Traditional approaches require an actuator imbedded in the device, a power source such as a battery, and some sort of controller which can activate the feedback at the appropriate time. This increases the cost of the device.

An ultrasonic array for airborne haptic feedback offers enough energy to activate a new class of passive devices. With careful design, a small device can be designed to receive acoustic energy from the array and then vibrate to create haptic feedback without the need for any kind of active circuitry on the device. This saves cost and relieves the need to charge a battery.

SUMMARY

Adjusting the reading of an optical camera with that of a phased array of acoustic transducers is often needed in many applications, and it is herein referred to as the calibration problem.

The magnification of the motion induced on an optical camera by the acoustic field modulated at specific frequencies, can reveal very small temporal variations in video frames. This quantized distortion would then be utilized to compare different acoustic fields and to solve the calibration problem in a complete, automatized way and without the need of human intervention.

The invention to be described has at least the following novel features:

• • 1. Possibility to solve calibration problems between an optical system and a phased array system;
  • 2. Possibility to calibrate the system in an automatized way, with no need of human intervention;
  • 3. A proposed algorithm for motion magnification;
  • 4. Two proposed methods in quantifying distortion produced by the acoustic field; and
  • 5. A proposed method for the machine path and for decision maker.

Further, mechanical resonators can be excited by ultrasound when it is modulated at the resonant frequency. When enough energy is transferred and when operating at the correct frequency, a user in contact with the device can feel vibration near areas of largest displacement. The invention described here exploits this effect to create devices which can produce haptic feedback while not carrying a battery or exciter when in the presence of an ultrasonic source.

BRIEF DESCRIPTION OF THE FIGURES

The accompanying figures, where like reference numerals refer to identical or functionally similar elements throughout the separate views, together with the detailed description below, are incorporated in and form part of the specification, serve to further illustrate embodiments of concepts that include the claimed invention and explain various principles and advantages of those embodiments.

FIG. 1 shows a process of scanning a focused acoustic field and detecting camera vibration.

FIG. 2A shows a motion magnification process.

FIG. 2B shows the application of a Gaussian smoothing on an image.

FIGS. 3A and 3B show graphs of motions of an optical camera.

FIG. 4 show text in various levels of focus.

FIG. 5 shows haptic effects on a bending rod.

FIG. 6 shows haptic effects on a pencil-shaped form factor.

FIG. 7 shows haptic effects on a handle-shaped form factor.

FIG. 8 shows haptic effects on a knife-shaped form factor

FIG. 9 shows haptic effects on an implement designed in the form factor of a tube that is to be grasped like a pen.

FIG. 10 shows an illustration of spatio-temporal modulated haptic implement.

Skilled artisans will appreciate that elements in the figures are illustrated for simplicity and clarity and have not necessarily been drawn to scale. For example, the dimensions of some of the elements in the figures may be exaggerated relative to other elements to help to improve understanding of embodiments of the present invention.

The apparatus and method components have been represented where appropriate by conventional symbols in the drawings, showing only those specific details that are pertinent to understanding the embodiments of the present invention so as not to obscure the disclosure with details that will be readily apparent to those of ordinary skill in the art having the benefit of the description herein.

DETAILED DESCRIPTION

I. Motion Magnification

As previously described, the magnification of the motion induced by the acoustic field on an optical camera can reveal small temporal variations in videos. The optical camera lens or camera chassis is excited with focused acoustic waves modulated at specific frequencies. These frequencies should be within the range of detectable frequencies of the optical camera, i.e., smaller than the sampling frequency of the camera. It is possible to apply different types of modulation (amplitude, frequency, phase) of the carrier to obtain the wanted frequency of excitation. The rationale of this method is to compare the amplified motion gradient produced by focal points at different spatial locations: the arrangement generating the largest gradient would give an estimation of the position of the camera. Once the relative position of the camera is determined, a calibration of the system may be performed.

FIG. 1 shows the steps 50 of scanning a focused acoustic field through space from an acoustic source 102 until the focused acoustic field impinges upon an element of a camera with sufficient amplitude to cause camera vibration to a detectable level 104.

This approach combines spatial and temporal processing to amplify tiny motion of a video sequence. The process can be divided into five major steps, which are schematically summarized in the form of a flow diagram in FIG. 2A. Steps two and three are fundamental parts of the well-established Canny edge detector algorithm. The method comprises a first step in which each frame of the video is transformed into a grayscale, single-channel image for ease of processing, and a second step in which each frame is smoothed to remove inherent noise. Subsequently, the first derivative of each frame is computed to reveal edges. This has the aim of improving the detection of motion and sharpening the image. Eventually, a temporal bandpass filter is applied to isolate the motion generated by specific frequencies. The extracted signal is linearly amplified and then is added back to the original signal. A spectral interpolation can be used to further enhance subtle temporal changes between frames.

FIG. 2A demonstrates the motion magnification process 100 comprising of the following steps:

• • 1. In step 150, a grayscale transformation of the RGB frame in the case that a full color camera is used, based on one of the common grayscale algorithms (e.g. the Luma algorithm). If a camera that yields output that is a single channel to begin with is used, this step is skipped.
  • 2. In step 120, the application of a Gaussian smoothing for each frame. The Gaussian smoothing operator is a 2-D spatial convolution operator that is used to “blur” images and remove both high-frequency detail and noise in both x and y directions. It uses a kernel that represents the shape of a Gaussian (“bell-shaped”) hump, with the following form:

$G\left(x,y\right)=\frac{1}{\sqrt{2\pi }\sigma }·e^{\left(-x^2+y^2/2{\sigma }^2\right)}$

• • 3. In step 130, the application of a Sobel operator to each frame for the detection of edges. The Sobel operator is again a 2-D spatial convolution operator that performs a gradient measurement on an image and so emphasizes regions of high spatial frequency that correspond to edges. In step 140, the Sobel operator can be obtained as the separable convolution of a Gaussian kernel in the direction(s) in which the edges are not to be detected and a differentiation kernel in the direction that crosses the edges to be detected, as follows:

$G_x=\left[\begin{array}{c}+1\\ +2\\ +1\end{array}\right]\left[\begin{array}{ccc}+1& 0& -1\end{array}\right]=\left[\begin{array}{ccc}+1& 0& -1\\ +2& 0& -2\\ +1& 0& -1\end{array}\right]$

$G_y=\left[\begin{array}{c}+1\\ 0\\ -1\end{array}\right]\left[\begin{array}{ccc}+1& 2& +1\end{array}\right]=\left[\begin{array}{ccc}+1& +2& +1\\ 0& 0& 0\\ -1& -2& -1\end{array}\right]$

for detecting pixels that cross edges in x and y respectively. For each image pixel, the gradient magnitude can be calculated by the formula:G=√{square root over (G_x²+G_y²)}

It is possible to obtain Sobel kernels of size 2ⁿ⁻¹×2ⁿ⁻¹ just by convolving the 3×3 kernel with another smoothing kernel n+1 times.

• • 4. In step 150, the application of a bandpass temporal filter to extract the frequency bands of interest. The motion is magnified by altering some features of the video. The motion magnification is achieved by applying a bandpass temporal filter to the spatially filtered frames of the video. The bandpass filter needs to be chosen according to the frequency that one wants to magnify: it will be a range centered to the value of the carrier/modulation frequency, and in any case lower than the sampling frequency of the camera. The bandpass filtered signal then undergoes a process of linear amplification, before being added back to the original signal, as follows:Ĩ(x,t)=χ·I(x,t)

Where χ is an arbitrarily chosen constant, I(x,t) is the filtered signal and Ī(x,t) is the amplified signal.

• • 5. In step 160, a two-dimensional spectral interpolation of data achieved by zero-padding in the frequency domain. This stage aims at increasing the sampling rate of each frame and subsequently at helping the recognition of motion. By performing interpolation on a frame sequence, the information held by the pixels of the original frames is transmitted at sub-pixel levels, allowing the possibility to perceive tinier movements. As shown in FIG. 2B, this process 200 is achieved by performing a 2D fast Fourier transform (FFT) 220 of the image 210, followed by an appropriate zero padding of the higher frequencies 230 and a 2D inverse FFT 240.

It is possible to amplify and compare the magnified motion of the aliased frequencies, in the case of the carrier or the modulation frequency falling outside the range of detectable frequencies. As a rule of thumb, the range of frequencies to magnify should be as wide as possible.

As shown by the accelerometer data, the acoustic field displaces the camera sufficiently to generate a blur in the camera image. This temporally modulated blur is detectable through a contrast detection algorithm. Shown in FIGS. 3A and 3B are the actual motions of an optical camera type “Ausdom 1080p 12 M full HD”, recorded by means of an accelerometer mounted on its body. These figures show that this motion magnification method successfully achieved visible results for sinusoidal displacements with amplitudes up to 2 micrometers peak-to-peak. This is shown as graph 300 in FIG. 3A for a 40 kHz sinusoidal carrier amplitude-modulated at 5 Hz, and as graph 350 in FIG. 3B, when the same carrier is amplitude-modulated at 100 Hz. A focused acoustic field was produced with a root means squared (RMS) pressure of about 1 kilopascal at 20 cm.

II. Still-Frame Contrast Detection

In some applications, measuring contrast in fixed frame images from the motion-tracking camera may provide another method in quantifying distortion produced by the acoustic field.

Contrast-detection algorithms are common in mirrorless cameras and other applications where phase detection is either too expensive or too bulky to implement. Contrast detection functions on the basic concept that a scene which is out of focus tends to blur objects and will cause adjacent pixels to average their values. This reduces contrast. By implementing a function which quantifies the contrast in an image, the camera system can move its lens to a position which maximizes this function and thereby will optimize its focus. FIG. 4 shows an example of a set of images 400 that have varying levels of contrast from the least focused (lowest contrast) 410, to medium focused (middle contrast) 420, to the most focused (highest contrast) 430.

The contrast detection as discussed herein will be used to quantify defocusing caused by the acoustic field. The shutter speed of the camera needs to be comparable to the period of modulation of the sound field. In this way, the image will be blurred by motion of the camera's focusing lens. By comparing the contrast of the standard image without stimulation to the one with acoustic stimulation, one can quantify the effect of the acoustic field and progress towards optimal calibration. Maximum defocusing (minimum contrast) will be correspond to a specific relative orientation and calibration will be possible. The background which is being imaged during calibration needs to be as static as possible to avoid false minimums. Regions with possible changes such as shiny surfaces containing reflections could be excluded from analysis.

Contrast quantifying algorithms include, but are not limited to, summed magnitude difference of adjacent pixels, summed magnitude squared difference of adjacent pixels, and summed magnitude difference of adjacent bins in the intensity histogram. Both grayscale and color information can be used. The ideal algorithmic implementation will depend on the variables including the camera used as well as the environment imaged during calibration.

III. Machine Path and Decision Maker

The final goal of the calibration process is to find the focus produced by phased array systems that maximizes the displacements of the camera apparatus. The decision on the final displacement and on displacement direction is based on the value of the gradient between different frames (or a sensible portion of the frame, e.g. where edges are more pronounced) of a video sequence. A general gradient algorithm for decision making is the following for the motion magnification algorithm:

$\sum _{i=1}^{n-1}\sum _{x=1}^N\sum _{y=1}^M{\check{I}\left(x,y\right)}_n-{\check{I}\left(x,y\right)}_{n+1}$ where n refers to the frame, N is the width of the frame, M is the height of the frame, {hacek over (I)}(x,y)_n is the intensity of the pixel belonging to the x-th row, to the y-th column and to the n-th frame, after the motion magnification is performed (as explained in the previous section of this document). The function of merit for the contrast method is simply an application of the contrast formula deemed most effective in the application.

The machine would ideally scan a portion of space where the camera is believed to exist. The machine could scan this portion of space following a regular pattern, since the space could be discretized in a regular grid of equally distant points with different x, y, z coordinates. Alternatively, the machine could scan the space in a random fashion, following a heuristic approach that resembles the Monte Carlo algorithm for optimization problems. Points to scan are sampled at random from an input probability distribution. For example, if a normal distribution is chosen, the mean could be the expected camera position and the standard deviation is chosen based on the expected variation in position derived from the manufacturing tolerances. The probability distribution would then be updated based on increasing knowledge of the camera location. Finally, the optimum point between the scanned ones is the focus which maximizes the value of the gradient algorithm M or minimizes the contrast.

IV. Haptic Effects on Resonators Resulting from Ultrasound

Mechanical resonators can be excited by ultrasound when the ultrasound is modulated at the resonant frequency. When enough energy is transferred and when operating at the correct frequency, a user in contact with the device can feel vibration near areas of largest displacement. The invention described herein exploits this effect to create devices that can produce haptic feedback while not carrying a battery or exciter when in the presence of an ultrasonic source.

To illustrate this principle, a simple resonator may be evaluated having a thin bar of rectangular cross section, with one dimension much smaller than the other two, and one much larger. Along the long dimension forms a series of modes related to the largest length. If the ends are left unclamped, they become anti-nodes and the frequencies supported by the rod are represented by sinusoids satisfying this condition with the displacement normal to the narrowest dimension.

Shown in FIG. 5 is an illustration 500 of a simple bending rod haptic implement. Ultrasound 540 is incident on the right side of the device which creates bulk mechanical vibration 530 that can be felt by a user 510 touching or holding the device. This example illustrates the major features that will need to be adapted for the desired form-factor: a haptic region which the user is in contact with, whose displacement is felt, and a receive region which accepts activation from an ultrasonic source and is mechanically connected to the haptic region forming a resonator.

The lowest order mode will have a node 520 (with zero-displacement) in the center of the rod and large displacement on the ends. In the context of this example, a user may hold onto one end of the rod, leaving the other end exposed.

Ultrasound modulated at the fundamental frequency of the resonator may be directed perpendicular to the rod on the other end. When activated, the rod vibrates, and the user 510 receives haptic feedback. This example neatly divides the device into two regions: a haptic region and a receive region. The haptic region is the area which is in contact with the user and is vibrating to give feedback to the user and is not necessarily always available for reception of ultrasound. The receive region also has large displacement but is designed to be continuously exposed to an ultrasonic source during operation.

This example also illustrates possibilities for multiple-frequency of vibration in the same device: higher-order modes will be at higher frequencies, but the locations of largest-displacement will be similar (the ends). As necessary, the ultrasonic source may be modulated at the desired frequency to change the feedback. Alternatively, multiple frequencies may be excited simultaneously to form sophisticated haptic waveforms. It should be noted that it is not necessary to have maximum displacement in the same location. A design may be implemented to have different frequencies target different locations.

Design of haptic regions may focus on frequency and displacement. Frequencies may be selected to maximize the sensitivity of the nerves targeted. The fingers, for instance, range from 4 Hz to 400 Hz. Resonating at those frequencies for a hand-held device w-ill maximize the sensitivity. Multiple frequencies may be combined to create distinct effects. Displacement is the fundamental attribute that dictates the strength of the haptic and needs to be considered based on the application and strength desired. A textured surface may be present at one or more haptic regions to both attract the user's grip and potentially change the haptic feel.

Design of receive regions should focus on direction of likely ultrasound, exposure, the area of the region, and quality-factor (Q-factor). Ultrasound carries momentum parallel to its direction of propagation. A receive region should be made of a high-acoustic-impedance material to reflect the pressure for maximum impulse transfer. The difference between the incident and reflected momentum vectors will be the imparted momentum to the resonator. A design may maximize the likelihood that this is parallel to the desired resonant mode displacement. This involves orienting the receive region towards the likely direction of incident ultrasound. Multiple receive regions may be included on the same device facing a variety of directions to maximize the likelihood of facing an acoustic array while the user is moving it.

FIG. 6 shows illustrations 900 of a stylus/pen form factor. In this example, the receive region is located at the rear of the implement where it is unlikely to be obstructed by the user. Shown are two variants of the receive region, an oval 920 that receives from only one direction (normal) and a hexagon 910 that can receive from a multitude of normal directions. The incident ultrasound 930 causes mechanical excitation at the ends of the stylus/pen 970, 940, which produces haptic feel at the ends of the stylus/pen 960, 950. This vibration mode shown consists of oscillations only up and down within the plane of the diagram. If a user grasps around the pen perpendicular to this direction, he or she will receive a sheering force instead of the typical pushing force, giving a unique haptic sensation.

FIG. 7 shows illustrations 1000 of a potential handle-like haptic implement. This could be used to mimic the feel of a racket or bat for VR/AR applications. Shown are two variants of the receive region—an oval 1010 that is sensitive only to its normal direction and a multi-faceted receiver 1020 that can couple to ultrasound from a number of normal directions. The incident ultrasound 1040 causes the user 1030 to feel haptic effects.

The area of reflection integrates the available momentum transfer. If focused ultrasound is used, scaling the size of the receive region to match the expected focus waist will maximize the possible coupling. This is shown in FIG. 8 where an illustration 800 demonstrates the receive region is integrated seamlessly into the device by using any flat surface such as the edge of a knife 810. The incident ultrasound 820 is applied to the knife edge, causing mechanical excitation on the opposite edge 840 of the knife and producing haptic feel on both edges 830, 850.

Furthermore, Q-factor relates to the time the resonator takes to ring up and ring down. This is influenced by the materials used (metal versus plastic versus rubber, etc.) as well as the attachment points and grip of the user. A large Q-factor (slow ring up and down) makes the device maximally sensitive to incident ultrasound but at the cost of precision—it will take more time to activate and deactivate the haptic. In that time, the user could move the implement away from the intended region of haptic feedback. A low-Q device can be very precise but will suffer from limited max amplitude when compared to the high-Q device. With sufficient ultrasonic energy, a low-Q device can be made both precise and strong enough for strong feedback. If ultrasonic energy is limited in the intended environment, a high-Q device will likely work better. If well characterized, a high-Q device will have a predictable phase response to ultrasonic stimulus and could be driven out of phase to stop haptics to improve ring down.

FIG. 9 shows an illustration 600 of a passive haptic implement designed in the form factor of a tube that is to be grasped like a pen from the outer diameter 610 and designed to hold a stylus or pen. The pen/stylus 650 is inserted in the tube and secured along vibratory nodes 640. A receive area for the incident ultrasound 630 may protrude from the device. When a user grasps the implement, the pen/stylus could be used as normal. When the haptic implement is excited with ultrasound, there is a flexing of the implement 630 a haptic effect would be felt by the user.

Most resonators will have some points of little-to-no movement frequently called “nulls” or “nodes” 640. These can serve as opportunities for attachment to other devices without losing energy into that device. The device is designed to have radial flexing modes to provide haptic and receive regions. Between these regions, nodes will exist which could provide an opportunity for attachment to a stylus or pen down the axis of the tube. The attachment may be designed to allow the stylus to slip in and out but still gripped securely enough to allow use. The sharper the contact point and the precision of the contact with the null minimizes the effect on the haptics.

Excitation through modulation may be achieved with amplitude or spatio-temporal modulation. Amplitude modulation varies the pressure magnitude versus time, effectively turning it on and off at a given frequency or frequencies. Spatio-temporal modulation achieves the same stimulus at a given point by steering the intensity of the field away and then back again at the desired frequency. An amplitude modulated field may effectively activate a haptic region by simply being directed towards it, but by its nature eschews half of its power through modulation.

The receive region may also be activated via spatiotemporal modulation by directing the field away from the receive region and back again. While away it could be used for direct mid-air haptics on the user or some other purpose.

Alternatively, a haptic implement may be designed with two receive regions nearby each other but designed to be driven out of phase. FIG. 10 shows an illustration of a possible spatiotemporal modulation excited haptic implement. For the first half of the vibratory cycle 700, the acoustic field 720 is directed to the end of the implement 710. For the second half of the cycle 750 the acoustic field 740 is directed to the middle of the implement 730. This allows continuous, full-power excitation of the implement. In this way, the ultrasound may be directed at one, transitioned to the second, and then back again. This allows for the full power of the ultrasound source to be utilized at all times. In another arrangement, the two haptic regions to be excited out of phase can be driven simultaneously with two amplitude modulated fields whose modulation is out of phase. This also allows for maximum utilization of available ultrasonic power.

Descriptions of haptic implements thus far presume displacement normal to the surface of the implement and into the user. In another arrangement, a passive implement may be designed which contains oscillations not entirely normal to the user contact. This provides a unique haptic experience relative to normal-oriented motion. As an example, a simple rod with the aspect ratio of a pencil could be designed with a flexing mode down its length (as in FIG. 6). When a flat is cut into one end as a receive region and oriented “up” and the flat is activated with ultrasound oriented “down,” this will cause displacement confined to a plane along the length of the rod and the up-down direction. If grasped along the sides of this imaginary plane, the user's fingers will experience displacement perpendicular to the skin. If another flat is provided perpendicular to the first, it may be activated at the same frequency yet provide a unique haptic to the first activation region.

Implements may be designed to be adjustable in their form. By rotating one end of the device through a joint (held mechanically or magnetically) the user may change the nature of the resonator. This may change the location of the haptic or receive regions. It may also affect the Q-factor, amplitude or resonant frequency. Besides rotation, the user may adjust a joint or any other form of mechanical connector.

In regions with limited but steerable ultrasound, optimal coupling may be achieved by steering and/or focusing the ultrasound directly at the receive region of the haptic implement. In this application, tracking the receive regions efficiently may be necessary and can be designed into the implement. Options for tracking include, but are not limited to:

• • Visual or IR fiducials placed on the implement that are designed to be recognized and tracked by a camera system. This can take the form of a simple sticker or as sophisticated as a retroreflector which will light up when exposed to incident light.
  • A specific acoustic reflecting shape contained on the implement which forms a recognizable reflection. The reflected acoustic signal would be recorded with microphones placed in the area which would identify and track the implement. This can be as simple as a flat reflector or some shape which forms a structured reflection field.
  • A powered element within the implement that provides tracking information. This may be a Bluetooth or some similar wireless protocol. Tracking information may be determined with a pickup mic to detect the receive ultrasound. It may be a vibration pickup to measure the haptic receive. The element can emit light or some other form of electromagnetic radiation which is picked up with external receivers. Alternatively, it can pick up and interpret tracking information provided by scanning base stations or similar structured information. Accelerometer data may be captured and transmitted as well.

Mechanical vibration may be harvested to power electronics using piezoelectric materials. By bonding a piezo film or crystal strategically to the implement, they could be hidden from view and not significantly affect haptics. In another arrangement, they could be used to aggressively change (or even completely stop) haptics by modulating their power draw. The power delivery could in this case, be independent of haptics. The energy can be temporarily stored and used to power any number of electronics on the device including but not limited to: displays, tracking emission/reception, and radios.

Example form factors include:

• • A rod intended to emulate a pen or scalpel.
  • A tube which is designed to have a stylus inserted.
  • A larger tube or rod meant to emulate the size and shape the handle of a racket, golf club, or bat (as in FIG. 7).
  • A glove with resonators placed in various places such as the back of the hand which are not as sensitive to traditional mid-air haptics.
  • A face mask.
  • A full-body suit with many different resonators matched to the specific locations on the body.
  • A game piece, figurine, model, or toy.

Further description of these embodiments may be as follows:

• • 1. A method to provide haptic feedback comprising:
  • a. A device with at least one mechanical resonance frequency;
  • b. A receive surface designed to receive acoustic energy modulated at that frequency;
  • c. Once acoustic energy is received, vibrates at another location on the device; and
  • d. This second (haptic) location can be in contact with a user to provide haptic feedback.
  • 2. The method as in paragraph 1 where the device has multiple resonant frequencies
  • 3. The method as in paragraph 2 where the different resonant frequencies have unique second (haptic) locations.
  • 4. The method as in paragraph 2 where the different resonant frequencies have unique receive regions.
  • 5. The method as in paragraph 1 where the device is attached to another device through mechanical nodes.
  • 6. The method as in paragraph 1 where there are multiple receive locations for the same frequency which are out of phase.
  • 7. The method as in paragraph 1 where the Q-factor of the resonator may be manipulated by the user.
  • 8. The method as in paragraph 1 where the Q-factor of the resonator may be manipulated by the acoustic field.
  • 9. The method as in paragraph 1 where the displacement of the second (haptic) region is designed to be perpendicular (sheer) to the contact of the user.
  • 10. The method as in paragraph 1 where the receive region is tracked using electromagnetic waves.
  • 11. The method as in paragraph 1 where the receive region is tracked by reflected acoustic energy.
  • 12. The method as in paragraph 1 where the receive region is tracked using a signal emitted from a control device on the implement.
  • 13. The method as in paragraph 1 where energy is harvested from the vibration of the implement.
  • 14. The method as in paragraph 13 where the energy is harvested using an attached piezoelectric material.
  • 15. The method as in paragraph 13 where the energy is used to power electronics embedded in the implement.

V. Conclusion

While the foregoing descriptions disclose specific values, any other specific values may be used to achieve similar results. Further, the various features of the foregoing embodiments may be selected and combined to produce numerous variations of improved haptic systems.

In the foregoing specification, specific embodiments have been described. However, one of ordinary skill in the art appreciates that various modifications and changes can be made without departing from the scope of the invention as set forth in the claims below. Accordingly, the specification and figures are to be regarded in an illustrative rather than a restrictive sense, and all such modifications are intended to be included within the scope of present teachings.

Moreover, in this document, relational terms such as first and second, top and bottom, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. The terms “comprises,” “comprising,” “has”, “having,” “includes”, “including,” “contains”, “containing” or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises, has, includes, contains a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. An element proceeded by “comprises . . . a”, “has . . . a”, “includes . . . a”, “contains . . . a” does not, without more constraints, preclude the existence of additional identical elements in the process, method, article, or apparatus that comprises, has, includes, contains the element. The terms “a” and “an” are defined as one or more unless explicitly stated otherwise herein. The terms “substantially”, “essentially”, “approximately”, “about” or any other version thereof, are defined as being close to as understood by one of ordinary skill in the art. The term “coupled” as used herein is defined as connected, although not necessarily directly and not necessarily mechanically. A device or structure that is “configured” in a certain way is configured in at least that way but may also be configured in ways that are not listed.

The Abstract of the Disclosure is provided to allow the reader to quickly ascertain the nature of the technical disclosure. It is submitted with the understanding that it will not be used to interpret or limit the scope or meaning of the claims. In addition, in the foregoing Detailed Description, it can be seen that various features are grouped together in various embodiments for the purpose of streamlining the disclosure. This method of disclosure is not to be interpreted as reflecting an intention that the claimed embodiments require more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive subject matter lies in less than all features of a single disclosed embodiment. Thus, the following claims are hereby incorporated into the Detailed Description, with each claim standing on its own as a separately claimed subject matter.

Claims

1. A method comprising: scanning a focused acoustic field through space from an acoustic source until the focused acoustic field impinges upon an element of a camera with sufficient amplitude to cause vibration of the camera to a detectable level; andestimating a relative location of the camera to the acoustic source based on the vibration of the camera.

2. The method as in claim 1, further comprising: detecting a camera imager blur via a contrast detection algorithm.

3. The method as in claim 2, wherein the contrast detection algorithm compares a standard camera image contrast with a vibrating camera image contrast.

4. The method as in claim 3, wherein the contrast detection algorithm further comprises excluding regions with possible changes.

5. The method as in claim 3, further comprising: determining a focus produced by the acoustic source that maximizes camera displacement.

6. The method as in claim 3, wherein the contrast detection algorithm further comprises spatial and temporal processing to amplify the camera imager blur.

7. The method as in claim 2, wherein the focused acoustic field includes a modulated carrier wave.

8. The method as in claim 7, wherein the modulated carrier wave is calibrated to obtain a desired frequency of camera vibration.

9. The method as in claim 1, further comprising: detecting camera motion via a motion magnification algorithm.

10. The method as in claim 9, further comprising: detecting a camera imager blur via a contrast detection algorithm.

11. The method as in claim 10, wherein the contrast detection algorithm compares a standard camera image contrast with a vibrating camera image contrast.

12. The method as in claim 11, wherein the contrast detection algorithm further comprises excluding regions with possible changes.

13. The method as in claim 11, further comprising: determining a focus produced by e acoustic source that maximizes camera displacement.

14. The method as in claim 11, wherein the contrast detection algorithm further comprises spatial and temporal processing to amplify the camera imager blur.

15. The method as in claim 10, wherein the focused acoustic field includes a modulated carrier wave.

16. The method as in claim 15, wherein the modulated carrier wave is calibrated to obtain a desired frequency of camera vibration.