Multi unit deformable controller

First and second resilient deformable spheres each have a pattern such as dots or a grid of lines projected or printed/deposited onto their inner surfaces, a camera positioned to image the pattern. When the spheres are deformed, the patterns are distorted. Distortions in the patterns are mapped to input signals to a computer simulation or other computer program. The spheres may each be attached to respective ends of a hollow tube also bearing the pattern such that not only can the spheres be squeezed, but the assembly also can be twisted to deform the pattern in the tube for further correlation to input signals.

FIELD

The present application relates generally to multi-unit deformable controllers and in particular to deformable computer simulation controllers.

BACKGROUND

As recognized herein, computer programs such as computer simulations such as computer games require user input, and can be made more interesting and enjoyable with the use of delightful input devices.

SUMMARY

An assembly includes first and second hollow resilient deformable spheres defining respective first and second inner surfaces. For each sphere, at least one laser projector is positioned to project a grid onto the inner surface of the respective sphere. Also, for each sphere, at least one sensor is positioned to image the grid such that responsive to the sphere being deformed, the grid is distorted for mapping images of distortions of the grid from the sensor to input signals to a computer program.

The computer program can include a computer simulation such as a computer game.

At least one processor may be programmed with instructions to correlate the distortions of the grids to the input signals.

The sensors can include cameras and/or event detection sensors (EDS).

Each sphere may be formed with an opening configured to engage a support and the sensor and projector are juxtaposed with the opening.

A hollow resilient tube defining first and second ends can be detachably engageable with the first and second spheres.

In another aspect, a computer input device includes a first hollow resilient deformable body defining an inner surface. A pattern is on the inner surface of the first body. A second hollow resilient deformable body defines an inner surface, and a pattern is on the inner surface of the second body. For each body, at least one respective sensor is positioned to image the pattern such that responsive to the body being deformed, the pattern is distorted such that distortions of the pattern imaged by the sensor can be correlated to input signals to a computer program.

In examples, each pattern includes plural spaced-apart dots and/or a grid of lines.

In non-limiting implementations, for each body, a respective projector is positioned to project the respective pattern onto the respective inner surface. In other implementations each respective pattern is printed or deposited on the respective inner surface.

In another aspect, a method includes disposing at least one sensor to image a pattern on an inner surface of a first hollow flexible housing. The method further includes disposing at least one sensor to image a pattern on an inner surface of a second hollow flexible housing, and connecting signals from the sensors representing the patterns to at least one computer program.

The details of the present application, both as to its structure and operation, can be best understood in reference to the accompanying drawings, in which like reference numerals refer to like parts, and in which:

DETAILED DESCRIPTION

This disclosure relates generally to computer ecosystems including aspects of consumer electronics (CE) device networks such as but not limited to computer game networks. A system herein may include server and client components which may be connected over a network such that data may be exchanged between the client and server components. The client components may include one or more computing devices including game consoles such as Sony PlayStation® or a game console made by Microsoft or Nintendo or other manufacturer, virtual reality (VR) headsets, augmented reality (AR) headsets, portable televisions (e.g., smart TVs, Internet-enabled TVs), portable computers such as laptops and tablet computers, and other mobile devices including smart phones and additional examples discussed below. These client devices may operate with a variety of operating environments. For example, some of the client computers may employ, as examples, Linux operating systems, operating systems from Microsoft, or a Unix operating system, or operating systems produced by Apple, Inc., or Google, or a Berkeley Software Distribution or Berkeley Standard Distribution (BSD) OS including descendants of BSD. These operating environments may be used to execute one or more browsing programs, such as a browser made by Microsoft or Google or Mozilla or other browser program that can access websites hosted by the Internet servers discussed below. Also, an operating environment according to present principles may be used to execute one or more computer game programs.

A processor may be a single- or multi-chip processor that can execute logic by means of various lines such as address lines, data lines, and control lines and registers and shift registers.

Referring now toFIG.1, an example system10is shown, which may include one or more of the example devices mentioned above and described further below in accordance with present principles. The first of the example devices included in the system10is a consumer electronics (CE) device such as an audio video device (AVD)12such as but not limited to a theater display system which may be projector-based, or an Internet-enabled TV with a TV tuner (equivalently, set top box controlling a TV). The AVD12alternatively may also be a computerized Internet enabled (“smart”) telephone, a tablet computer, a notebook computer, a head-mounted device (HMD) and/or headset such as smart glasses or a VR headset, another wearable computerized device, a computerized Internet-enabled music player, computerized Internet-enabled headphones, a computerized Internet-enabled implantable device such as an implantable skin device, etc. Regardless, it is to be understood that the AVD12is configured to undertake present principles (e.g., communicate with other CE devices to undertake present principles, execute the logic described herein, and perform any other functions and/or operations described herein).

Accordingly, to undertake such principles the AVD12can be established by some, or all of the components shown. For example, the AVD12can include one or more touch-enabled displays14that may be implemented by a high definition or ultra-high definition “4K” or higher flat screen. The touch-enabled display(s)14may include, for example, a capacitive or resistive touch sensing layer with a grid of electrodes for touch sensing consistent with present principles.

The AVD12may also include one or more speakers16for outputting audio in accordance with present principles, and at least one additional input device18such as an audio receiver/microphone for entering audible commands to the AVD12to control the AVD12. The example AVD12may also include one or more network interfaces20for communication over at least one network22such as the Internet, an WAN, an LAN, etc. under control of one or more processors24. Thus, the interface20may be, without limitation, a Wi-Fi transceiver, which is an example of a wireless computer network interface, such as but not limited to a mesh network transceiver. It is to be understood that the processor24controls the AVD12to undertake present principles, including the other elements of the AVD12described herein such as controlling the display14to present images thereon and receiving input therefrom. Furthermore, note the network interface20may be a wired or wireless modem or router, or other appropriate interface such as a wireless telephony transceiver, or Wi-Fi transceiver as mentioned above, etc.

In addition to the foregoing, the AVD12may also include one or more input and/or output ports26such as a high-definition multimedia interface (HDMI) port or a universal serial bus (USB) port to physically connect to another CE device and/or a headphone port to connect headphones to the AVD12for presentation of audio from the AVD12to a user through the headphones. For example, the input port26may be connected via wire or wirelessly to a cable or satellite source26aof audio video content. Thus, the source26amay be a separate or integrated set top box, or a satellite receiver. Or the source26amay be a game console or disk player containing content. The source26awhen implemented as a game console may include some or all of the components described below in relation to the CE device48.

The AVD12may further include one or more computer memories/computer-readable storage media28such as disk-based or solid-state storage that are not transitory signals, in some cases embodied in the chassis of the AVD as standalone devices or as a personal video recording device (PVR) or video disk player either internal or external to the chassis of the AVD for playing back AV programs or as removable memory media or the below-described server. Also, in some embodiments, the AVD12can include a position or location receiver such as but not limited to a cellphone receiver, GPS receiver and/or altimeter30that is configured to receive geographic position information from a satellite or cellphone base station and provide the information to the processor24and/or determine an altitude at which the AVD12is disposed in conjunction with the processor24. The component30may also be implemented by an inertial measurement unit (IMU) that typically includes a combination of accelerometers, gyroscopes, and magnetometers to determine the location and orientation of the AVD12in three dimension or by an event-based sensors such as event detection sensors (EDS). An EDS consistent with the present disclosure provides an output that indicates a change in light intensity sensed by at least one pixel of a light sensing array. For example, if the light sensed by a pixel is decreasing, the output of the EDS may be −1; if it is increasing, the output of the EDS may be a +1. No change in light intensity below a certain threshold may be indicated by an output binary signal of 0.

Continuing the description of the AVD12, in some embodiments the AVD12may include one or more cameras32that may be a thermal imaging camera, a digital camera such as a webcam, an IR sensor, an event-based sensor, and/or a camera integrated into the AVD12and controllable by the processor24to gather pictures/images and/or video in accordance with present principles. Also included on the AVD12may be a Bluetooth® transceiver34and other Near Field Communication (NFC) element36for communication with other devices using Bluetooth and/or NFC technology, respectively. An example NFC element can be a radio frequency identification (RFID) element.

Further still, the AVD12may include one or more auxiliary sensors38(e.g., a pressure sensor, a motion sensor such as an accelerometer, gyroscope, cyclometer, or a magnetic sensor, an infrared (IR) sensor, an optical sensor, a speed and/or cadence sensor, an event-based sensor, a gesture sensor (e.g., for sensing gesture command)) that provide input to the processor24. For example, one or more of the auxiliary sensors38may include one or more pressure sensors forming a layer of the touch-enabled display14itself and may be, without limitation, piezoelectric pressure sensors, capacitive pressure sensors, piezoresistive strain gauges, optical pressure sensors, electromagnetic pressure sensors, etc.

The AVD12may also include an over-the-air TV broadcast port40for receiving OTA TV broadcasts providing input to the processor24. In addition to the foregoing, it is noted that the AVD12may also include an infrared (IR) transmitter and/or IR receiver and/or IR transceiver42such as an IR data association (IRDA) device. A battery (not shown) may be provided for powering the AVD12, as may be a kinetic energy harvester that may turn kinetic energy into power to charge the battery and/or power the AVD12. A graphics processing unit (GPU)44and field programmable gated array46also may be included. One or more haptics/vibration generators47may be provided for generating tactile signals that can be sensed by a person holding or in contact with the device. The haptics generators47may thus vibrate all or part of the AVD12using an electric motor connected to an off-center and/or off-balanced weight via the motor's rotatable shaft so that the shaft may rotate under control of the motor (which in turn may be controlled by a processor such as the processor24) to create vibration of various frequencies and/or amplitudes as well as force simulations in various directions.

A light source such as a projector such as an infrared (IR) projector also may be included.

In addition to the AVD12, the system10may include one or more other CE device types. In one example, a first CE device48may be a computer game console that can be used to send computer game audio and video to the AVD12via commands sent directly to the AVD12and/or through the below-described server while a second CE device50may include similar components as the first CE device48. In the example shown, the second CE device50may be configured as a computer game controller manipulated by a player or a head-mounted display (HMD) worn by a player. The HMD may include a heads-up transparent or non-transparent display for respectively presenting AR/MR content or VR content.

In the example shown, only two CE devices are shown, it being understood that fewer or greater devices may be used. A device herein may implement some or all of the components shown for the AVD12. Any of the components shown in the following figures may incorporate some or all of the components shown in the case of the AVD12.

Now in reference to the afore-mentioned at least one server52, it includes at least one server processor54, at least one tangible computer readable storage medium56such as disk-based or solid-state storage, and at least one network interface58that, under control of the server processor54, allows for communication with the other illustrated devices over the network22, and indeed may facilitate communication between servers and client devices in accordance with present principles. Note that the network interface58may be, e.g., a wired or wireless modem or router, Wi-Fi transceiver, or other appropriate interface such as, e.g., a wireless telephony transceiver.

Accordingly, in some embodiments the server52may be an Internet server or an entire server “farm” and may include and perform “cloud” functions such that the devices of the system10may access a “cloud” environment via the server52in example embodiments for, e.g., network gaming applications. Or the server52may be implemented by one or more game consoles or other computers in the same room as the other devices shown or nearby.

The components shown in the following figures may include some or all components shown in herein. Any user interfaces (UI) described herein may be consolidated and/or expanded, and UI elements may be mixed and matched between UIs.

Present principles may employ various machine learning models, including deep learning models. Machine learning models consistent with present principles may use various algorithms trained in ways that include supervised learning, unsupervised learning, semi-supervised learning, reinforcement learning, feature learning, self-learning, and other forms of learning. Examples of such algorithms, which can be implemented by computer circuitry, include one or more neural networks, such as a convolutional neural network (CNN), a recurrent neural network (RNN), and a type of RNN known as a long short-term memory (LSTM) network. Support vector machines (SVM) and Bayesian networks also may be considered to be examples of machine learning models. In addition to the types of networks set forth above, models herein may be implemented by classifiers.

As understood herein, performing machine learning may therefore involve accessing and then training a model on training data to enable the model to process further data to make inferences. An artificial neural network/artificial intelligence model trained through machine learning may thus include an input layer, an output layer, and multiple hidden layers in between that that are configured and weighted to make inferences about an appropriate output.

Referring now toFIGS.2and3, a computer input device200includes a first hollow resilient deformable body202defining an inner surface and, as more fully described below, a pattern being on the inner surface of the first body. In the example shown, the body202is shaped as a sphere in the undeformed configuration shown inFIG.2and is sized for convenient gripping by the left hand204of a user, although the body202may be materially biased to undeformed shapes other than spherical, e.g., ovular, elliptical or other oblong, pyramidal, cylindrical, or rectilinear. The device200further includes a second hollow resilient deformable body206that is substantially identical in configuration and operation to the first body202and is configured to be conveniently gripped by the right hand208. As more fully discussed below and as shown inFIG.3, the user can manipulate one or both bodies202,206by deforming them by squeezing to generate input signals to a computer program such as a computer simulation such as a computer game to control presentation of the game according to the input signals.

In the example shown, each body202,206is formed with a respective opening210,212that is configured to engage a respective end of a hollow resilient tube214. By turning one body202,206clockwise and holding the other body stationary or turning the other body206,202counterclockwise, the user can twist the tube214which may also result in generation of input signals to the computer program. The user can also flex the tube to generate input signals. By “flex” is meant bend the tube. The bodies202,206may be detached from the tube214and operated separately as free-standing input devices. If desired, the tube214may be mounted for rotational movement on a stem216with rotational motion being sensed by, e.g., an IMU in the device200and converted to yet further input signals to the computer program.

Now refer toFIG.4which illustrates further details of the body202, it being understood that the other body206may be configured identically to the body202shown inFIG.4. For each body202, at least one respective sensor such as an imager400is positioned to image the pattern inside the body such that responsive to the body being deformed, the pattern is distorted such that distortions of the pattern imaged by the sensor can be correlated to input signals to a computer program.

FIG.4illustrates that the tube214may include various sensing and processing components for imaging the interior of the body202. The imager400may be a red-green-blue (RGB) camera or infrared (IR) camera or event detection sensor (EDS) receiving light through a lens402representing the interior of the body202. For example, the imager400may be 480×480 camera or structured light camera (EDS) or a monochrome IR camera.

The images from the imager400may be processed by one or more processors404and stored on one or more computer storage media406. The images may be transmitted through a communication interface408to one or more sources of computer simulations such as one or more servers410and one or more computer game consoles412to control presentation of the simulations according to the images. Without limitation, the interface408may be, e.g., a universal serial bus (USB) interface, an Ethernet interface, or other wired or wireless interface such as a Wi-Fi interface or Bluetooth interface.

In some examples, one or more inertial measurement units (IMU)414may be provided in the tube214to sense motion imparted by manipulations of the body202such that the object with tube can essentially operate as a joystick-like device. Furthermore, a protrusion416may be provided on the body202and may be rocked by hand around its base where it joins the body202in joystick fashion to deform the body202and hence distort the pattern within the body, which distortions may be imaged and mapped to joystick-like commands.

The pattern on the interior of the body202, discussed further below, may be printed, or deposited, e.g., as IR-reflective ink or paint, onto the interior. Or, a projector418, e.g., in the tube214, may project the pattern through the opening420between the tube interior and object interior. The projector418may project RGB light and/or IR light for example onto the interior surface of the body202.

The tube214may contain similar components for the body206near the opposite end of the tube. Note that the operating components inFIG.4may be located in the body itself when it is desired for the body to be detachable for separate use apart from the tube.

FIG.5illustrates that if desired, the curvature500of the lens402may match the curvature502of each body, using the body202as an example.

FIG.6illustrates that one or more capacitive sensors600may be disposed on the outer surface of each body, using the body202as an example. These sensor600may be deposited on the body202as a coating to identify which finger or fingers causes a deformation of the body202.

FIG.7illustrates that visible indicia700may be printed or otherwise formed on the exterior of each body, using the body202as an example, to guide the user in what part of the object to squeeze to input a particular command. In the example shown, the indicia700are direction arrows, indicating the depressing the object at, for instance, the right-pointing arrow inFIG.7will result in a move right command being input to a computer simulation. Other indicia can include “shoot weapon” indicia, “character jump” indicia, and so on. Other indicia may include indications as to whether the body is intended for the left or right hand when detached from the tube214.

Turning to examples of the pattern that may be printed, deposited, projected, or otherwise formed on the interior of the bodies and using the body202as an example,FIG.8illustrates that a grid of lines800may be formed on the interior of the body202. When the body202is not deformed, the grid800is not distorted, and the grid appears as shown in the top row ofFIG.8with spaces between grid lines being constant.

On the other hand, when the body is deformed by, for example, a person squeezing it, the grid800is distorted as shown in the bottom row ofFIG.8. A distorted grid may be evidenced by a greater spacing between grid lines in areas of the object being expanded by squeezing and less spacing between grid lines in areas of the object not being expanded by squeezing.

Or, a regular dot pattern802may be formed on the interior of the body202, with all dots being equidistant from neighboring dots as other dots and arranged in rows as shown, their sizes being constant, in the undistorted configuration shown in the top row ofFIG.8. In contrast, when distorted the spacing between adjacent dots in areas of the object being expanded by squeezing can lengthen, the size of the dots in such areas expanded, relative to dots in areas of the object not being expanded by squeezing.

At804inFIG.8an irregular pattern is shown in which in the undistorted configuration (top row), dots or other symbols may be randomly arranged on the inside surface, with the image of the pattern in the undistorted configuration being learned by one or more machine learning (ML) models. Distortions of the irregular pattern804results in some of the parts of the pattern being displaced relative to their undistorted locations and/or sizes as shown in the bottom row ofFIG.8. Regardless of the type of pattern, ML models can be used to correlate images of distortions of the pattern to input commands to control presentation of a computer simulation such as a computer game.

Note that the pattern also may appear on the outside of the body202. Note further that for each pattern, an origin may be defined relative to which the distortion of each pixel may be established in the distorted configuration. In one non-limiting example, the origin may be the location of the surface of the sphere in the center of the image from a camera positioned with its optical axis co-linear with the axis of the shaft.

FIG.9illustrates the device200with both bodies202,206attached to the tube214, schematically showing the projector418and imager400for imaging the interior of the left-hand body202and a projector900and imager902for imaging the interior of the right-hand body206. The tube214also may include one or more sensors904for sensing position and orientation of the tube as well as twisting of the tube214. Without limitation, the one or more sensors904may include IMUs, GPS receivers, force sensors for sensing twist, piezo-based sensors for sensing twist, and imagers for imaging a pattern in the inside of the tube to detect distortions therein, all of which sensors may produce outputs to be mapped to input commands.

FIG.10illustrates further. At block1000, images of the interior of a body202/206and/or tube214in various states of distortion and undistortion are input to a ML model such as a convolutional neural network (CNN), along with ground truth indication of a computer simulation input command for each image. The model is trained at block1002on the training set input at block1000. Note that when non-imager sensors are used in the tube214, the training set includes signals from those sensors in various degrees of twist with ground truth input commands annotated thereto.

The training can result in a mapping table1100shown inFIG.11, in which various distortions1102of a pattern on the interior of the body202caused by a person deforming the object are mapped to respective input commands1104, such as cursor or character up/down commands, shoot weapon commands, and the like.

FIG.11Aillustrates a post-training architecture. Images1110from the imager400inFIG.4of the pattern inside one or both of the hand-grippable bodies202/206(or tube214) are input to a ML model or models1112, trained as discussed above. The ML model(s)1102output computer simulation control commands1114to a computer simulation engine1116such as may be executed by a computer game server or console. The computer simulation engine1116outputs a computer simulation presented according to the commands1114to a display1118such as any display disclosed herein for presentation of the computer simulation thereof.

FIG.12illustrates example logic that commences at block1200by receiving images of distortions of the patterns inside the bodies202,206and if desired camera/sensor indications of twist of the tube214at block1202. These inputs to the ML model produce outputs of the ML model at block1204that are computer program input signals such as computer game input commands. The commands are input at block1206to a computer simulation engine executed y, e.g., a server or game console to control presentation of the simulation according to the commands output at block1204.

FIG.13illustrates a UI1300that may be presented on any display herein to allow a user to define which simulation commands are to be correlated to specific distortions. For example, a distortion caused by forefinger pressure indicated at1302(as detected by, e.g., the capacitive sensors described herein and provided to the ML model) may be mapped to a command input by the user into a field1304, in the example shown, a shoot command. At1306a second type of distortion may be mapped to a second field1308, and so on, allowing the user to define the commands to be input from various manipulations of the bodies202/206/tube214.

In example embodiments, the material of the bodies202/206and if desired tube214may be translucent and the projector may be an IR projector. In such an example, the pattern projected onto the inside surface of the object can be tracked in virtual reality (VR) using an external camera. Imaged spaces between the gamer's fingers on the object can be used for hand pose/tracking as fingers block light. Also, the IMU inFIG.4may be used to assist in tracking. If desired, stress sensors may be embedded into the device200to measure forces being applied to the object.

While the particular embodiments are herein shown and described in detail, it is to be understood that the subject matter which is encompassed by the present invention is limited only by the claims.