Abstract: A system and method for reverberation reduction is disclosed. A first Deep Neural Network (DNN) produces a first estimate of a target direct-path signal from a mixture of acoustic signals that include the target direct-path signal and a reverberation of the target direct-path signal. A filter modeling a room impulse response (RIR) for the first estimate is estimated. The filter when applied to the first estimate of the target direct-path signal generates a result closest to a residual between the mixture of the acoustic signals and the first estimate of the target direct-path signal according to a distance function. A mixture with reduced reverberation of the target direct-path signal is obtained by removing the result of applying the filter to the first estimate of the target direct-path signal from the received mixture. A second DNN produces a second estimate of the target direct-path signal from the mixture with reduced reverberation.

Abstract: A device for controlling an operation of a system performing a task is disclosed. The device submits a sequence of control inputs to the system thereby changing states of the system according to the task and receives a feedback signal. The device determines a current control input for controlling the system based on the feedback signal including a current measurement of a current state of the system by solving a polynomial optimization of a polynomial function with a reformulation derived by introducing additional variables reducing a degree of the polynomial function till a target degree subject to constraints on a structure of the additional variables. The device solves a mixed-integer optimization problem to find an optimal solution among all possible encodings of factorizations of the polynomial function that reduces the degree of the polynomial function till the target degree with a minimum number of additional variables.

Abstract: A system for controlling an operation of a machine for performing a task is disclosed. The system submits a sequence of control inputs to the machine and receives a feedback signal. The system further determines, at each control step, a current control input for controlling the machine based on the feedback signal including a current measurement of a current state of the system by applying a control policy transforming the current measurement into the current control input based on current values of control parameters in a set of control parameters of a feedback controller. Furthermore, the system may iteratively update a state of the feedback controller defined by the control parameters using a prediction model predicting values of the control parameters and a measurement model updating the predicted values to produce the current values of the control parameters that explain the sequence of measurements according to a performance objective.

Abstract: A controller for controlling a vapor compression system is provided. The controller is configured to control an operation of the VCS with different combinations of setpoints for different actuators of the VCS to estimate a cost of operation of the VCS for each of the different combinations of setpoints, and compute, using a Bayesian optimization of the combinations of setpoints and their corresponding estimated costs of operation, a probabilistic surrogate model, wherein the probabilistic surrogate model defines at least first two order moments of the cost of operation in the probabilistic mapping. The controller is further configured to select an optimal combination of setpoints having the largest likelihood of being a global minimum at the surrogate model according to an acquisition function of the first two order moments of the cost of operation.

Abstract: Data communications and storage systems require error control techniques and digital modulation schemes to be transferred efficiently and successfully. Constellation shaping based on probabilistic amplitude shaping (PAS) offers an energy-efficient transmission in particular for long shaping blocks. However, longer shaping blocks can cause burst errors and enhancement of bit error rates besides longer latency to complete distribution matcher and dematcher operations. Methods and systems are disclosed that provide a way to resolve the issues by introducing a dual concatenation of pre-shaping and post-shaping error correction codes to mitigate burst errors of shaping. This enables low-complexity, high-performance and parallel architecture with a balanced overhead of dual-concatenation codes for shaping systems.

Abstract: A gripper system having tentacles including a control system configured to receive operator data and sensor data. Compare stored object configurations associated with grips to identify a corresponding set of object configurations using a target object shape and a pose via sensor data and select an object configuration. Compare stored commands to identify sets of commands corresponding to the object configuration and select sets of commands. If a set of pickup actions are received, compare to the corresponding object configuration to identify a set of pickup actions using the received set of pickup actions, and select a set of pickup actions. Compare the sets of commands to identify a corresponding first set of commands corresponding to a set of pickup actions using the set of pickup actions and select the first set of commands. If the received set of pickup actions are absent, then select a second set of commands.

Abstract: A multiple input multiple output (MIMO) radar system for detecting a moving object is based on an explicit signal model. The explicit signal model accounts for waveform separation residuals by relating measurements of the virtual array to an auto-term including a Kronecker product of object-receiver signatures and transmitter-object signatures; and a cross-term including a Kronecker product of object-receiver signatures and transmitter-object residual signatures. The radar system uses a spatial MIMO object detector that is based on the explicit signal model to detect the moving object.

Abstract: Stochastic nonlinear model predictive control (SNMPC) allows to directly take uncertainty of the dynamics and/or of the system's environment into account, e.g., by including probabilistic chance constraints. However, SNMPC requires the approximate computation of the probability distributions for the state variables that are propagated through the nonlinear system dynamics. This invention proposes the use of Gaussian-assumed density filters (ADF) to perform high-accuracy propagation of mean and covariance information of the state variables through the nonlinear system dynamics, resulting in a tractable SNMPC approach with improved control performance. In addition, the use of a matrix factorization for the covariance matrix variables in the constrained optimal control problem (OCP) formulation guarantees positive definiteness of the full trajectory of covariance matrices in each iteration of any optimization algorithm.

Abstract: The present disclosure provides an artificial intelligence (AI) system for sequence-to-sequence modeling with attention adapted for streaming applications. The AI system comprises at least one processor; and memory having instructions stored thereon that, when executed by the processor, cause the AI system to process each input frame in a sequence of input frames through layers of a deep neural network (DNN) to produce a sequence of outputs. At least some of the layers of the DNN include a dual self-attention module having a dual non-causal and causal architecture attending to non-causal frames and causal frames. Further, the AI system renders the sequence of outputs.

Abstract: Embodiments disclose a method and system for a scene-aware audio-video representation of a scene. The scene-aware audio video representation corresponds to a graph of nodes connected by edges. A node in the graph is indicative of the video features of an object in the scene. An edge in the graph connecting two nodes indicates an interaction of the corresponding two objects in the scene. In the graph, at least one or more edges are associated with audio features of a sound generated by the interaction of the corresponding two objects. The graph of the audio-video representation of the scene may be used to perform a variety of different tasks. Examples of the tasks include one or a combination of an action recognition, an anomaly detection, a sound localization and enhancement, a noisy-background sound removal, and a system control.

Abstract: A method and a system for processing an image and transform it into a high resolution and high-definition image using a computationally efficient image transformation procedure is provided. The transformation of the image comprises receiving an intensity image and generating an application programming interface (API) call for transforming the received intensity image. The API call is then transmitted to an image processing server for transforming the intensity image into a layered distance field (DF) image. Further, a response is received from the image processing server, wherein the response comprises one or more functions for obtaining the layered DF image.

Abstract: An artificial intelligence (AI) system is disclosed. The AI system includes a processor that processes a sequence of input frames with a neural network including a dilated self-attention module trained to compute a sequence of outputs by transforming each input frame into a corresponding query frame, a corresponding key frame, and a corresponding value frame leading to a sequence of key frames, a sequence of value frames, and a sequence of query frames of same ordering and by performing attention calculations for each query frame with respect to a combination of a portion of the sequences of key and value frames restricted based on a location of the query frame and a dilation sequence of the key frames and a dilation sequence of value frames extracted by processing different frames of the sequences of key and value frames with a predetermined extraction function. Further, the processor renders the sequence of outputs.

Abstract: A tactile sensor including a camera positioned to capture images of marks. An elastically deformable skin including an outer surface having attributes and an undersurface having pins, ridges, or both. Each undersurface pin or ridge includes a mark. A processor detects displacement of the marks in captured images and compares the displaced positions of the marks in the captured images to stored sets of prelearned positions of marks, based on a distance function, to determine a quality of match value for each set of the prelearned positions of marks. A best quality matched prelearned pattern of forces is determined using a user selected function, to calculate a best matching set of the prelearned positions of marks. Identify a pattern of forces acting on the elastically deformable skin based on the determined best matched prelearned pattern of forces.

Abstract: A system for controlling an autonomous vehicle includes a memory configured to store parameters of a g-g plot defining admissible space of values of longitudinal and lateral accelerations. The g-g plot parameters define a mapping between user driving preferences and constrained control of the autonomous vehicle. The g-g plot parameters include a maximum forward acceleration, a maximum backward acceleration, a maximum lateral acceleration and a shape parameter defining profile of curves connecting maximum values of forward, backward, and lateral accelerations. The system accepts a comfort level as a feedback from a passenger of the vehicle, determines a dominant parameter corresponding to the feedback, updates the dominant parameter of the g-g plot based on the comfort level indicated in the feedback, and controls the vehicle to maintain dynamics of the vehicle within the admissible space defined by the parameters of the updated g-g plot.

Abstract: An apparatus and a method for planning contact-interaction trajectories are provided. The apparatus is a robot that accepts contact interactions between the robot and the environment. The robot stores a dynamic model representing geometric, dynamic, and frictional properties of the robot and the environment, and a relaxed contact model to representing dynamic interactions between the robot and the object via virtual forces. The robot further determines, iteratively until a termination condition is met, a trajectory, associated control commands for controlling the robot, and virtual stiffness values by performing optimization reducing stiffness of the virtual force and minimizing a difference between the target pose of the object and a final pose of the object moved from the initial pose. Further, an actuator moves a robot arm of the robot according to the trajectory and the associated control commands.

Abstract: A method and a system for processing an image and transform it into a high resolution and high-definition image using a computationally efficient image transformation procedure is provided. The transformation of the image comprises receiving, at a first input interface, a layered distance field (DF) image including an ordered sequence of multiple layers. Each layer of the layered DF image includes a DF procedure defining DF values at all locations of the received intensity image and rules for mapping these DF values into intensity values of the layer. The transformation of the image further comprises, receiving, at a second input interface, a transformation instruction and transforming the layered DF image based on the transformation instruction.

Abstract: A distributed machine learning based traffic prediction method is provided for predicting traffic of roads. In this case, the distributed machine learning based traffic prediction method includes distributing global multi-task traffic models by a learning server to learning agents to locally train the traffic models, uploading locally trained traffic models by learning agents to the learning server, updating global multi-task traffic models by the learning server using locally trained traffic model parameters acquired from learning agents, generating a time-dependent global traffic map by the learning server using the well trained global multi-task traffic models, distributing the time-dependent global traffic map to vehicles traveling on the roads, and computing an optimal travel route with the least travel time by a vehicle using the time-dependent global traffic map based on a driving plan.

Abstract: An electrical machine that is an outer runner motor having a rotor mounted rotatably about a machine axis, with the rotor rotatively attached to a shaft. A stator assembly having a stator core with a non-ferromagnetic material. An axial-flux yoke with an inner wall rigidly attached on an outer surface of a first edge wall of the stator core, or a radial-flux yoke with a continuous inner wall rigidly attached on a continuous outer wall of the stator core. Wherein the axial-flux yoke or the radial-flux yoke, include laminated sheets and slots. Windings can be positioned in the slots of either the axial-flux stator yoke or the radial-flux stator yoke. Wherein the stator core and the shaft include a spline coupling feature adapted to selectively couple and mate the stator core to the shaft.

Abstract: A control system for controlling an operation of an elevator arranged to service different floors of a building, is disclosed. The control system comprises an input interface configured to receive a measurement of a distance metric to an object located at a service floor in a line-of-sight of a sensor; an output interface configured to cause a display device to display a floor value indicating a destination floor; and a processor configured to compare the received distance metric with a referenced distance metric to estimate a sign of the comparison and a value of the comparison; repeatedly update, until a termination condition is met, the floor value displayed on the display device in a direction of the elevator service indicated by the sign and with a frequency of the update indicated by the value; and cause the elevator to perform the service operation from the service floor to the destination floor.

Abstract: A controller controls a motion of an object performing a task for changing a state of the object from a start state to an end state while avoiding collision of the object with an obstacle according to an optimal trajectory determined by solving an optimization problem of the dynamics of the object producing an optimal trajectory for performing the task subject to constraints on a solution of first-order stationary conditions modeling a minimum distance between the convex hull of the object and the convex hull of the obstacle using complementarity constraints.