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 control system for parking a vehicle uses a directed graph representing a traffic network within parking space to determine a coarse path subsequently refined to control the vehicle according to refined path. The directed graph includes waypoints connected by edges, a waypoint defines a position and an orientation, while edge defines a collision free path for the vehicle. The coarse path is selected as a shortest route of waypoints connecting an initial waypoint on the directed graph closest to the initial state of the vehicle with a target waypoint on the directed graph closest to the target state of the vehicle. The refined path is a path on a tree constructed to reduce a deviation of a cost of a motion defined by a refined path connecting the initial node with the target node of the tree from a cost of the coarse path defining the route of waypoints.

Abstract: A manipulation controller is provided for reorienting an object by a manipulator of a robotic system. The manipulation controller includes an interface controller configured to acquire measurement data from sensors arranged on the robotic system, at least one processor, and a memory configured to store a computer-implemented method.

Abstract: A computer-implemented method is provided for detecting broken bar faults of an induction motor during operations. The method includes steps of injecting a frequency modulation continuous wave (FMCW) voltage signal to the voltage source to power the motor, acquiring, in a time domain, a signal of a stator current powering the induction motor via an interface, performing Fourier Transform (FT) on the stator current and the injected FMCW signal to get spectra of the stator current and the injected signal, computing cross correlation between the spectrum of injected signal and the spectrum of stator current, extracting a fault signature at frequency f=±2(1?s)f0 in the cross-correlation function, and detecting a broken-bar fault in the induction motor if the fault signature magnitude is greater than a threshold.

Abstract: Disclosed a method and system for fault location and protection of Microgrids which are operated under islanded mode by being disconnected from distribution systems under large disturbance or disaster scenarios. The disclosed method is invented to meet the protection needs for disconnected ungrounded microgrids without appropriate protection systems that are usually installed only at distribution substations. Moreover, the disclosed protection method or scheme is targeted at inverter-dominated microgrids in which fault current limiters are installed to protect inverters introduced by the increasing penetration of inverter-based distributed generators (IBDGs).

Abstract: A probabilistic feedback controller for controlling an operation of a robotic system using a probabilistic filter subject to a structural constraint on an operation of the robotic system is configured to execute a probabilistic filter estimates a distribution of a current state of the robotic system given a previous state of the robotic system based on a motion model of the robotic system perturbed by stochastic process noise and a measurement model of the robotic system perturbed by stochastic measurement noise having an uncertainty modeled as a time-varying Gaussian process represented as a weighted combination of time-varying basis functions with weights defined by corresponding Gaussian distributions. The probabilistic filter recursively updates both the distribution of the current state of the robotic system and the Gaussian distributions of the weights of the basis functions selected to satisfy the structural constraint indicated by measurements of the state of a robotic system.

Abstract: A motor assembly comprising a mover assembly and a stator. The mover assembly comprising a plurality of mover assembly units, each unit comprising: a non-ferromagnetic core with a profile of an outer surface having at least two flat sections lying on intersecting planes; at least two ferromagnetic laminated structures arranged on the at least two flat sections of the non-ferromagnetic core, each ferromagnetic laminated structure includes a stack of ferromagnetic plates, each plate is covered with a non-conductive coating. Each ferromagnetic laminated structure is arranged on a corresponding flat section of the at least two flat sections of the non-ferromagnetic core such that side of each ferromagnetic plate is adjacent to the non-ferromagnetic core thereby making the ferromagnetic plates of the at least two ferromagnetic laminated structures lie on intersecting planes.

Abstract: An audio processing system is provided. The audio processing system comprises an input interface configured to accept an audio signal. Further, the audio processing system comprises a memory configured to store a neural network trained to determine different types of attributes of multiple concurrent audio events of different origins, wherein the types of attributes include time-dependent and time-agnostic attributes of speech and non-speech audio events. Further, the audio processing system comprises a processor configured to process the audio signal with the neural network to produce metadata of the audio signal, the metadata including one or multiple attributes of one or multiple audio events in the audio signal.

Abstract: Disclosed a method and system for fault location and protection of Microgrids which are operated under islanded mode by being disconnected from distribution systems under large disturbance or disaster scenarios. The disclosed method is invented to meet the protection needs for disconnected ungrounded microgrids without appropriate protection systems that are usually installed only at distribution substations. Moreover, the disclosed protection method or scheme is targeted at inverter-dominated microgrids in which fault current limiters are installed to protect inverters introduced by the increasing penetration of inverter-based distributed generators (IBDGs).

Abstract: A control system controls a vehicle using a probabilistic motion planner and an adaptive predictive controller. The probabilistic motion planner produces a sequence of parametric probability distributions over a sequence of target states for the vehicle with parameters defining a first and higher order moments. The adaptive predictive controller optimizes a cost function over a prediction horizon to produce a sequence of control commands to one or multiple actuators of the vehicle. The cost function balances a cost of tracking of different state variables in the sequence of the target states defined by the first moments. The balancing is performed by weighting different state variables using one or multiple of the higher order moments of the probability distribution.

Abstract: A robotic system for manipulating an object with a robotic manipulator is provided. The robotic system is configured to collect a digital representation of a task for manipulating the object; solve a robust control problem to optimize a sequence of control forces to be applied by the robotic manipulator to change a state of the object, where an evolution of the state of the object is governed by a stochastic complementarity system modeling the task with a predefined probability. The robust control problem optimizes a cost function to generate the sequence of control forces performing the task subject to joint chance constraints including a first chance constraint on the state of the object being manipulated and a second chance constraint on stochastic complementarily constraints modeling manipulation of the object. The robotic system is further configured to control the manipulation of the object based on the sequence of control forces.

Abstract: Embodiments of the present disclosure disclose a system and method for localization of a target sound event. The system collects a first digital representation of an acoustic mixture of sounds of a plurality of sound events, by using an acoustic sensor. The system receives a second digital representation of a sound corresponding to the target sound event. Further, the first digital representation and the second digital representation are processed by a neural network to produce a localization information indicative of a location of an origin of the target sound event with respect to a location of the acoustic sensor.

Abstract: Embodiments of the present invention disclose a method and system for performing video anomaly detection by training neural networks. The method includes collecting a video of one or more digital images from a source domain. The method includes obtaining a set of images of foreground objects present in the video. In addition, the method includes training of a first neural network to predict frames for the one or more digital images in the video. The first neural network is trained using a future frame prediction module that predicts frames for the one or more digital image. The method includes training of a second neural network to classify the predicted frame as normal and to classify the synthesized pseudo anomaly frame as abnormal. The method includes performing video anomaly detection based on training of the first neural network and the second neural network.

Abstract: A Bluetooth-enabled device is provided, the Bluetooth-enabled device being configured to control a radio frequency (RF) chain during a first period to receive at a single antenna selected from a plurality of antennas, a constant tone extension (CTE) signal of multiple frames transmitted by the Bluetooth-enabled transmitter over multiple frequencies. Further the RF chain is controlled during a second period to switch among the plurality of antennas to receive the CTE signal at each of the plurality of antennas. An initial time-of-flight (ToF) data of the CTE signal is determined from first samples of the CTE signal received during the first period. Further, the Bluetooth-enabled transmitter is localized with respect to a location of the Bluetooth-enabled device using a signal model connecting samples of the CTE signal with an unknown angle-of-arrival of the CTE signal received at specific times, an unknown ToF conditioned on the initial ToF data.

Abstract: A system for controlling or optimizing the performance of a vapor compression system by modifying the actuator commands via an output interface, that realizes thermofluid property functions and their derivatives as spline functions which are represented in a coordinate system that is aligned with a fluid saturation curve. The system includes an interface configured to receive measurement data from sensors, a memory configured to store thermofluid property data and computer-executable programs including a B-spline method, and a processor for performing the computer-implemented method. The processor is configured to take as input two thermofluid property variables, and compute a coordinate transformation in which one axis of the coordinates is aligned with the liquid and vapor saturation curves. In the saturation-curve aligned coordinates, a spline function represents the thermofluid property function, with coefficients and knots stored in memory.

Abstract: A computer-implemented method is provided for generating device parameters of circuits using a pretrained reinforcement learning (RL) agent composed of a graph neural network (GNN) and a fully connected neural network (FCNN). The method is performed by steps including acquiring inputs with respect to a set of desired specifications or one desired specification of a circuit, device parameters, a fixed topology of the circuit and providing the inputs to the RL agent. The desired circuit description includes a graph modeling the topology of the circuit and device parameters of the circuit, and the desired specifications include gain, bandwidth, phase margin, power consumption, output power and power efficiency.

Abstract: A vehicle includes an advanced driver-assistance system (ADAS) configured to intervene in an operation of the control system by complementing or overriding the driving input in response to detecting a driving condition dependent on a calibration parameter indicative of a preference of execution of the driving maneuver. The ADAS is calibrated based on a crowd-local distribution function of the calibration parameter indicative of a distribution of the preference of execution of the driving maneuver by other drivers of other vehicles at a specific location or a specific environment in response to detecting that the vehicle approaches the specific location or the specific environment.

Abstract: An imaging controller is provided for segmenting instances from depth images including objects to be manipulated by a robot. The imaging controller includes an input interface configured to receive a depth image that includes objects, a memory configured to store instructions and a neural network trained to segment instances from the objects in the depth image, and a processor, coupled with the memory, configured to perform the instructions to segment a pickable instance using the trained neural network.

Abstract: A computer-implemented method is provided for training a global machine learning model using a learning server and a set of vehicle agents connected to roadside units (RSUs). The method includes steps of selecting vehicle agents from a pool of the vehicle agents connected to the RSUs, associating the selected vehicle agents and the RSUs respectively based on distances from the selected vehicle agents to the RSUs configured to provide measurements of the distances to the learning server, and transmitting a global model, a selected agent set and deadline thresholds in each global training round to the RSUs configured to transmit the global model and training deadlines to the selected vehicle agents. The associated RSUs compute the training deadlines of the corresponding selected vehicle agents and the selected vehicle agents locally train the global model independently using the local datasets collected by the on-board sensors of the selected vehicle agents to generate locally trained models.

Abstract: A controller and a method for controlling motion of a vehicle is provided. The method comprises acquiring motion information including a current state of the vehicle and a desired state of the vehicle, determining a combination of a steering angle of the wheels and motor forces for moving the vehicle from the current state into the desired state by using a first model of the motion of the vehicle and a second model of the motion of the chassis of the vehicle, determining a cost function of the motion of the vehicle, optimizing the cost function of the motion of the vehicle to compute a command signal for controlling the steering wheel and the plurality of electric motors, and controlling the steering angle of the wheels and the motor forces based on the command signal.