Abstract: Systems and methods enable an autonomous vehicle to perform an iterative task of transferring material from a source location to a destination location, such as moving dirt from a pile, in a more efficient manner, using a combination of reinforcement learning techniques to select a motion path for a particular iteration and visual servo control to guide the motion of the vehicle along the selected path. Lifting, carrying, and depositing of material by the autonomous vehicle can also be managed using similar techniques.

Abstract: The present disclosure relates generally to identification of drivable surfaces in connection with autonomously performing various tasks at industrial work sites and, more particularly, to techniques for distinguishing drivable surfaces from non-drivable surfaces based on sensor data. A framework for the identification of drivable surfaces is provided for an autonomous machine to facilitate it to autonomously detect the presence of a drivable surface and to estimate, based on sensor data, attributes of the drivable surface such as road condition, road curvature, degree of inclination or declination, and the like. In certain embodiments, at least one camera image is processed to extract a set features from which surfaces and objects in a physical environment are identified, and to generate additional images for further processing. The additional images are combined with a 3D representation, derived from LIDAR or radar data, to generate an output representation indicating a drivable surface.

Abstract: The present disclosure relates generally to the operation of autonomous machinery for performing various tasks at various industrial work sites, and more particularly to the volumetric estimation and dimensional estimation of a pile of material or other object, and the use of multiple sensors for the volumetric estimation and dimensional estimation of a pile of material or other object at such work sites. An application and a framework is disclosed for volumetric estimation and dimensional estimation of a pile of material or other object using at least one sensor, preferably a plurality of sensors, on an autonomous machine (e.g., robotic machines or autonomous vehicles) in various work-site environments applicable to various industries such as, construction, mining, manufacturing, warehousing, logistics, sorting, packaging, agriculture, etc.

Abstract: In one aspect, In one aspect, a method for data transfer and processing communications is provided. The method includes the step of providing a machine-to-everything (M2X) application layer on each machine of the plurality of machines. The method includes the step of providing a plurality of communication nodes on each machine for communication between the plurality of machines with every other machine, the plurality of machines and any infrastructure at a work site, and a plurality of communication nodes communicating using the at least one application layer. The method includes the step of providing a communication processing system for receiving a data transfer and processing communications. The communication processing system includes a plurality of processing stations, one or more multiple data management protocols, a plurality of network protocols, a plurality of databases and plurality of data processing network architectures.

Abstract: The present disclosure relates generally to identification of drivable surfaces in connection with autonomously performing various tasks at industrial work sites and, more particularly, to techniques for distinguishing drivable surfaces from non-drivable surfaces based on sensor data. A framework for the identification of drivable surfaces is provided for an autonomous machine to facilitate it to autonomously detect the presence of a drivable surface and to estimate, based on sensor data, attributes of the drivable surface such as road condition, road curvature, degree of inclination or declination, and the like. In certain embodiments, at least one camera image is processed to extract a set features from which surfaces and objects in a physical environment are identified, and to generate additional images for further processing. The additional images are combined with a 3D representation, derived from LIDAR or radar data, to generate an output representation indicating a drivable surface.

Abstract: The present disclosure relates generally to the operation of autonomous machinery for performing various tasks at various industrial work sites, and more particularly to the volumetric estimation and dimensional estimation of a pile of material or other object, and the use of multiple sensors for the volumetric estimation and dimensional estimation of a pile of material or other object at such work sites. An application and a framework is disclosed for volumetric estimation and dimensional estimation of a pile of material or other object using at least one sensor, preferably a plurality of sensors, on an autonomous machine (e.g., robotic machines or autonomous vehicles) in various work-site environments applicable to various industries such as, construction, mining, manufacturing, warehousing, logistics, sorting, packaging, agriculture, etc.

Abstract: In one aspect, In one aspect, a method for data transfer and processing communications is provided. The method includes the step of providing a machine-to-everything (M2X) application layer on each machine of the plurality of machines. The method includes the step of providing a plurality of communication nodes on each machine for communication between the plurality of machines with every other machine, the plurality of machines and any infrastructure at a work site, and a plurality of communication nodes communicating using the at least one application layer. The method includes the step of providing a communication processing system for receiving a data transfer and processing communications. The communication processing system includes a plurality of processing stations, one or more multiple data management protocols, a plurality of network protocols, a plurality of databases and plurality of data processing network architectures.

Abstract: Systems and methods enable an autonomous vehicle to perform an iterative task of transferring material from a source location to a destination location, such as moving dirt from a pile, in a more efficient manner, using a combination of reinforcement learning techniques to select a motion path for a particular iteration and visual servo control to guide the motion of the vehicle along the selected path. Lifting, carrying, and depositing of material by the autonomous vehicle can also be managed using similar techniques.

Abstract: A station that generates data packets to be transmitted by the station such that the data packets spend a minimum amount of time in a buffer prior to transmission. The method includes receiving a specification for a connected discontinuous reception (C-DRX) cycle, the specification indicating when a plurality of onDurations of the C-DRX cycle occurs, the onDurations having a predetermined interval therebetween, receiving data at a known time relative to the C-DRX cycle, determining a modification to a conversion process that converts the data to data packets such that the data packets are stored in a buffer at a subframe immediately preceding one of the onDurations subsequent to the known time, performing the conversion process based upon the modification and storing the data packets at the subframe immediately preceding the one of the onDurations. In one embodiment, the data is raw audio data and the data packets are audio packets.

Abstract: A method of signal processing an input signal in a hearing aid to avoid entrainment, the hearing aid including a receiver and a microphone, the method comprising using an adaptive filter to measure an acoustic feedback path from the receiver to the microphone and adjusting an adaptation rate of the adaptive filter using an output from a filter having an autoregressive portion, the output derived at least in part from a ratio of a predictive estimate of the input signal to a difference of the predictive estimate and the input signal.

Abstract: A station that generates data packets to be transmitted by the station such that the data packets spend a minimum amount of time in a buffer prior to transmission. The method includes receiving a specification for a connected discontinuous reception (C-DRX) cycle, the specification indicating when a plurality of onDurations of the C-DRX cycle occurs, the onDurations having a predetermined interval therebetween, receiving data at a known time relative to the C-DRX cycle, determining a modification to a conversion process that converts the data to data packets such that the data packets are stored in a buffer at a subframe immediately preceding one of the onDurations subsequent to the known time, performing the conversion process based upon the modification and storing the data packets at the subframe immediately preceding the one of the onDurations. In one embodiment, the data is raw audio data and the data packets are audio packets.

Abstract: A method of signal processing an input signal in a hearing aid to avoid entrainment, the hearing aid including a receiver and a microphone, the method comprising using an adaptive filter to measure an acoustic feedback path from the receiver to the microphone and adjusting an adaptation rate of the adaptive filter using an output from a filter having an autoregressive portion, the output derived at least in part from a ratio of a predictive estimate of the input signal to a difference of the predictive estimate and the input signal.

Abstract: A system of signal processing an input signal in a hearing assistance device to avoid entrainment wherein the hearing assistance device including a receiver and a microphone, the method comprising using an adaptive filter to estimate an acoustic feedback path from the receiver to the microphone, generating one or more estimated future pole positions of a transfer function of the adaptive filter, analyzing stability of the one or more estimated pole positions for an indication of entrainment and adjusting the adaptation of the adaptive filter based on the stability.

Abstract: A method of signal processing an input signal in a hearing aid to avoid entrainment, the hearing aid including a receiver and a microphone, the method comprising using an adaptive filter to measure an acoustic feedback path from the receiver to the microphone and adjusting an adaptation rate of the adaptive filter using an output from a filter having an autoregressive portion, the output derived at least in part from a ratio of a predictive estimate of the input signal to a difference of the predictive estimate and the input signal.

Abstract: A system of signal processing an input signal in a hearing aid to avoid entrainment, the hearing aid including a receiver and a microphone, the method comprising using a transform domain adaptive filter including two or more eigenvalues to measure an acoustic feedback path from the receiver to the microphone, analyzing a measure of eigenvalue spread against a predetermined threshold for indication of entrainment of the transform domain adaptive feedback cancellation filter, and upon indication of entrainment of the transform domain adaptive feedback cancellation filter, modulating the adaptation of the transform domain adaptive feedback cancellation filter.

Abstract: Method and apparatus for signal processing an input signal in a hearing assistance device to avoid entrainment, the hearing assistance device including a receiver and a microphone, the system comprising using a gradient adaptive lattice filter including one or more reflection coefficients to measure an acoustic feedback path from the receiver to the microphone of the hearing assistance device.

Abstract: Systems and methods for adaptive feed-forward noise cancellation. The system includes a plurality of reference microphones, an error microphone, a secondary path module, an adaptation controller, and a canceller filter. A finite impulse response (“FIR”) based plant model is converted to an infinite impulse response (“IIR”) based plant model using balanced model reduction. Due to the inherent instability of the adaptive IIR filter, the Schur-Cohn stability test is applied to the denominator coefficients of the IIR filter transfer function to determine the stability of the noise cancellation system. A secondary path of the noise cancellation system is identified in an on-line manner in the secondary path module. If the energy level of the communication signal (e.g., a music signal) is strong, secondary path identification is performed. The adaptation controller controls the updating of the IIR transfer function based on the stability determination and the secondary path.

Abstract: A system of signal processing an input signal in a hearing assistance device to avoid entrainment wherein the hearing assistance device including a receiver and a microphone, the method comprising using an adaptive filter to estimate an acoustic feedback path from the receiver to the microphone, generating one or more estimated future pole positions of a transfer function of the adaptive filter, analyzing stability of the one or more estimated pole positions for an indication of entrainment and adjusting the adaptation of the adaptive filter based on the stability.

Abstract: A system of signal processing an input signal in a hearing assistance device to avoid entrainment wherein the hearing assistance device including a receiver and a microphone, the method comprising using an adaptive filter to estimate an acoustic feedback path from the receiver to the microphone, generating one or more estimated future pole positions of a transfer function of the adaptive filter, analyzing stability of the one or more estimated pole positions for an indication of entrainment and adjusting the adaptation of the adaptive filter based on the stability.

Abstract: Systems and methods for adaptive feed-forward noise cancellation. The system includes a plurality of reference microphones, an error microphone, a secondary path module, an adaptation controller, and a canceller filter. A finite impulse response (“FIR”) based plant model is converted to an infinite impulse response (“IIR”) based plant model using balanced model reduction. Due to the inherent instability of the adaptive IIR filter, the Schur-Cohn stability test is applied to the denominator coefficients of the IIR filter transfer function to determine the stability of the noise cancellation system. A secondary path of the noise cancellation system is identified in an on-line manner in the secondary path module. If the energy level of the communication signal (e.g., a music signal) is strong, secondary path identification is performed. The adaptation controller controls the updating of the IIR transfer function based on the stability determination and the secondary path.