Abstract: Systems and methods for developing a game of chance. The game of chance being at least partially developed using specialized artificial intelligence (AI) game design systems or specialized artificial intelligence game design system modules or components which may include different types of machine learning or training techniques, including supervised, unsupervised, reinforced, deep learning and artificial neural networks and/or similar and may include analyzing past game performance utilizing full, partial or estimated prior game performance data for developing slot machine game math models, slot machine game mechanics and associated game programming, slot machine game art and graphics, slot machine animations, slot machine game sound effects, partial or full slot machine game development, slot machine computer code, slot machine game quality assurance diagnosis and editing, slot machine game analytics, slot machine compliance, slot machine help screens, and slot game predictive models, etc.

Abstract: Systems and methods are disclosed for deep brain stimulation. In one implementation, a deep brain stimulation system comprises a neural probe configured for placement within a brain; at least one signal lead; a sensing assembly including at least one sensing micro-electrode and at least one stimulation electrode; and at least one processor assembly configured to: receive at least one sense signal generated in response to interaction between the at least one sensing electrode and one or more electrical signals generated by at least one neuron in the brain; deliver at least one of a library of preset target stimulation patterns; determine a target stimulation pattern based on at least one characteristic of the at least one sense signal; and cause a signal generator to deliver stimulation signals to stimulation electrodes among the at least one stimulating electrode to activate the set of stimulation electrodes according to the target stimulation pattern.

Abstract: Disclosed herein are systems and methods for estimating target ranges, angles of arrival, and speed using optimization procedures. Target ranges are estimated by performing an optimization procedure to obtain a denoised signal, performing a correlation of a transmitted waveform and the denoised signal, and using a result of the correlation to determine an estimate of a distance between the sensor and at least one target. Target angles of arrival are estimated by determining ranges at which targets are located, and, for each range, constructing an array signal from samples of received echo signals, and using the array signal, performing another optimization procedure to estimate a respective angle of arrival for each target of the at least one target. Doppler shifts may also be estimated using another optimization procedure. Certain of the optimization procedures use atomic norm techniques.

Abstract: A hybrid LiDAR system may include a long-range LiDAR subsystem characterized by a first range and a first azimuth angular coverage, and a short-range LiDAR subsystem characterized by a second range and a second azimuth angular coverage, wherein the first range is greater than the second range, and the second azimuth angular coverage is greater than the first azimuth angular coverage.

Abstract: Disclosed herein are multiple-input, multiple-output (MIMO) LiDAR systems in which the fields of view of multiple illuminators (e.g., lasers) overlap and/or fields of view of multiple detectors (e.g., photodiodes) overlap. Some embodiments provide for illuminators that transmit substantially white pulse sequences that are substantially uncorrelated with each other so that they can be distinguished from one another when detected by a single detector.

Abstract: Disclosed and described here are an adapter for a neuromonitoring system for placement of an electrode in a subject and a method for confirming placement of an electrode on an appropriate nerve fiber of a dorsal root ganglion during a dorsal root ganglion stimulation procedure.

Abstract: Systems and methods are disclosed for a neural interface. In one implementation, a neural interface comprises a neural probe configured for placement within a brain; at least one signal lead extending from the neural probe; and a sensing assembly included on the neural probe, where the sensing assembly includes: a plurality of dual-role electrodes positioned on the neural probe, wherein each of the dual-role electrodes is configured to sense electrical signals generated by one or more neurons in the brain and to convey to the at least one signal lead one or more sense signals generated based on the sensed electrical signals, and wherein each of the dual-role electrodes is configured to receive, via the at least one signal lead, a stimulation signal selectively delivered from a stimulus generator.

Abstract: Systems and methods are disclosed for local amplification, multiplexing and analog-to-digital conversion of signals sensed from deep brain regions.

Abstract: Systems and methods are disclosed for deep brain stimulation. In one implementation, a deep brain stimulation system comprises a neural probe configured for placement within a brain; at least one signal lead; a sensing assembly including at least one sensing micro-electrode and at least one stimulation electrode; and at least one processor assembly configured to: receive at least one sense signal generated in response to interaction between the at least one sensing electrode and one or more electrical signals generated by at least one neuron in the brain; deliver at least one of a library of preset target stimulation patterns; determine a target stimulation pattern based on at least one characteristic of the at least one sense signal; and cause a signal generator to deliver stimulation signals to stimulation electrodes among the at least one stimulating electrode to activate the set of stimulation electrodes according to the target stimulation pattern.

Abstract: Disclosed herein are systems and methods for estimating target ranges, angles of arrival, and speed using optimization procedures. Target ranges are estimated by performing an optimization procedure to obtain a denoised signal, performing a correlation of a transmitted waveform and the denoised signal, and using a result of the correlation to determine an estimate of a distance between the sensor and at least one target. Target angles of arrival are estimated by determining ranges at which targets are located, and, for each range, constructing an array signal from samples of received echo signals, and using the array signal, performing another optimization procedure to estimate a respective angle of arrival for each target of the at least one target. Doppler shifts may also be estimated using another optimization procedure. Certain of the optimization procedures use atomic norm techniques.

Abstract: Disclosed herein are light detection and ranging (LiDAR) systems. In some embodiments, a LiDAR system comprises a plurality of N illuminators, each of the plurality of N illuminators configured to illuminate a respective one of a plurality of N illuminator fields-of-view (FOVs); a detector comprising at least one focusing component and at least one detector array, wherein the detector is configured to observe a detector FOV that overlaps at least a first illuminator FOV of the plurality of N illuminator FOVs; and at least one processor configured to cause a first illuminator of the plurality of N illuminators to emit an optical pulse to illuminate the first illuminator FOV, obtain a signal representing at least one reflected optical pulse detected by the detector, and determine a position of at least one target using the signal.

Abstract: Disclosed herein are light detection and ranging (LiDAR) systems and methods of using them. In some embodiments, a LiDAR system comprises an array of optical components and at least one processor coupled to it. The array comprises n1 illuminators configured to illuminate a point in space, and n2 detectors configured to observe the point in space, wherein n1×n2>2 and the illuminators and n2 detectors are situated in a non-collinear arrangement. The at least one processor is configured to determine a first time-of-flight set corresponding to a first location of the LiDAR system at a first time; determine a second time-of-flight set corresponding to a second location of the LiDAR system at a second time; and solve an optimization problem to estimate a position of the target, wherein the optimization problem minimizes a cost function that takes into account the first time-of-flight set and the second time-of-flight set.

Abstract: A robotic system is provided, which automatically changes settings on an audio system. The audio system (e.g., an instrument amplifier, effect processor, etc.) typically includes one or more controls that impact the operation of the audio system. Correspondingly, the robotic system includes a device interface coupled to a control sequencer. The device interface adapts to one or more controls of the audio system that are to be changed. In this regard, the device interface includes one or more control couplers. Each control coupler is adapted to a corresponding control of the audio system to be changed. The control sequencer provides a control sequence to the device interface that causes the control coupler(s) to vary the settings on the audio system. In practical applications, a combination of sequence values of the control sequence can represent a sufficiently high number of samples to determine a responsive behavior of the audio system.

Abstract: Disclosed herein are techniques relating to a light detection and ranging (LiDAR) system that includes a first optical array including a first active area, a second optical array including a second active area, wherein the first active area and the second active area are separated by a distance, and at least one optical component configured to laterally-shift a virtual image corresponding to at least one of the first optical array or the second optical array, thereby reducing a gap in a field of view (FOV) of the LiDAR system. The at least one optical component may be reflective, refractive, diffractive, or a combination of reflective, refractive, and/or diffractive. The at least one optical component may include one or more prisms and/or one or more mirrors. The optical arrays can be emitter arrays (e.g., lasers) or detector arrays (e.g., photodiodes). The techniques described herein can be used to combine more than two optical arrays.

Abstract: Disclosed herein are optical systems (e.g., LiDAR systems) and methods with improved eye safety. In some embodiments, a system includes a first light emitter configured to illuminate a first field of view (FOV) using light emitted at a first wavelength and a second light emitter configured to illuminate a second FOV using light emitted at a second wavelength. The second FOV is wider than the first FOV, and the first FOV extends to a further distance from the system than the second FOV. The system also includes a sensor configured to detect reflections off of targets within the second FOV, and at least one processor configured to execute one or more machine executable instructions.

Abstract: Disclosed herein are systems and methods for estimating target ranges, angles of arrival, and speed using optimization procedures. Target ranges are estimated by performing an optimization procedure to obtain a denoised signal, performing a correlation of a transmitted waveform and the denoised signal, and using a result of the correlation to determine an estimate of a distance between the sensor and at least one target. Target angles of arrival are estimated by determining ranges at which targets are located, and, for each range, constructing an array signal from samples of received echo signals, and using the array signal, performing another optimization procedure to estimate a respective angle of arrival for each target of the at least one target. Doppler shifts may also be estimated using another optimization procedure. Certain of the optimization procedures use atomic norm techniques.

Abstract: Methods for submitting an insurance claim for damaged motor vehicle glass are provided that can include: receiving a plurality of images associated with motor vehicle glass at processing circuitry; performing image processing operations on each of the plurality of images to determine one or more of glass damage, glass type, and/or claim fraud; and submitting an insurance claim for motor vehicle glass repair or replace based on the glass type or damage, or flagging the claim as fraud. The present disclosure also provides a non-transitory computer readable storing instruction that when executed by a processor, causes a computer system to perform the following method.

Abstract: Disclosed herein are systems, devices, and methods that may be used for autonomous driving and/or in autonomous vehicles. Some embodiments use an integrated wide-aperture multi-band radar subsystem and leverage the unique propagation properties of multiple bands and/or multiple sensor technologies to significantly improve detection and understanding of the scenery and, in particular, to see around corners to identify non-line-of-sight targets. In some embodiments, at least one processor of the system is capable of jointly processing return (reflected) signals in multiple bands to provide high accuracy in a variety of conditions (e.g., weather). The disclosed radar subsystem can be used alone or in conjunction with another sensing technology, such as, for example, LiDAR and/or cameras.

Abstract: Disclosed herein are systems and methods for estimating target ranges, angles of arrival, and speed using optimization procedures. Target ranges are estimated by performing an optimization procedure to obtain a denoised signal, performing a correlation of a transmitted waveform and the denoised signal, and using a result of the correlation to determine an estimate of a distance between the sensor and at least one target. Target angles of arrival are estimated by determining ranges at which targets are located, and, for each range, constructing an array signal from samples of received echo signals, and using the array signal, performing another optimization procedure to estimate a respective angle of arrival for each target of the at least one target. Doppler shifts may also be estimated using another optimization procedure. Certain of the optimization procedures use atomic norm techniques.