Abstract: System and method are disclosed for multi-phase process of automated data capture for photogrammetry and 3D model building of an unknown object (311) in an unknown environment. Planner module (152) generates a flight plan (413) for a camera drone (110) to fly autonomously on a flight path along a virtual polygon grid (302) defined above the target object (311) during a survey phase. Model builder computer (153) receives a point cloud dataset (321) captured by LiDAR sensor on camera drone (301) during survey flight and constructs low resolution 3D mesh (331) of the target object (311). Planner module (152) generates a flight path (413) for camera drone inspection phase with virtual waypoints surrounding the target object (311) at a marginal distance from the surface defined by the low resolution 3D mesh (331).

Abstract: Current approaches to controlling robots from multiple vendors typically requires multiple software systems that define vendor-exclusive fleet manager or dispatch systems. Autonomous devices (e.g., robots, drones, vehicles) can be controlled from multiple vendors that use multiple locally sourced map. For example, maps from individual robots can be translated to a base map that can be used to command and control hybrid fleets of robots.

Abstract: A system determines a location and a size of a new power generation or power regulating unit within a current system architecture of a power system including a plurality of power generation units. The system comprises a controller including a processor and a memory, computer-readable logic code stored in the memory which, when executed by the processor, causes the controller to execute a hybrid algorithm as a combination of a data-driven algorithm and a model-based algorithm to determine an optimal location and size of the new power generation or power regulating unit. The data-driven algorithm encodes a location and a size information. The controller to enable the model-based algorithm to optimize performance of a selected location and size of the new power generation or power regulating unit, which is based on a linearized system or a nonlinear system to provide guidance for the data-driven algorithm to incorporate physical rules and verify a new system architecture.

Abstract: A computer-implemented method for building an object detection module uses mesh representations of objects belonging to specified object classes of interest to render images by a physics-based simulator. Each rendered image captures a simulated environment containing objects belonging to multiple object classes of interest placed in a bin or on a table. The rendered images are generated by randomizing a set of parameters by the simulator to render a range of simulated environments. The randomized parameters include environmental and sensor-based parameters. A label is generated for each rendered image, which includes a two-dimensional representation indicative of location and object classes of objects in that rendered image frame. Each rendered image and the respective label constitute a data sample of a synthetic training dataset. A deep learning model is trained using the synthetic training dataset to output object classes from an input image of a real-world physical environment.

Abstract: A computer-implemented method for online calibration of power system model against a power system includes iteratively approximating the power system model, at sequential optimization steps, around a moving design point defined by parameter values of a set of calibration parameters of the power system model. At each optimization step, an approximated system model is used to transform a dynamic input signal into a model output signal, which is compared with measurement signals obtained from measurement devices installed in the power system that define an actual power system output signal generated in response to the dynamic input signal. Parameter values of the calibration parameters adjusted in a direction to minimize an error between the model output signal and the actual power system output signal. The power system model is calibrated against the power system based on resulting optimal values of the calibration parameters.

Abstract: A system (100) for enabling trusted on-demand distributed manufacturing includes a first interface (120) configured to receive product data from a product data source (110-A, 110-B, 110-N), a second interface (130) configured to exchange manufacturing data from a manufacturing data source (140-A, 140-B, 140-N), a trust anchor module (170) configured via computer executable instructions to add a physically unclonable function (PUF) to a product, generate a non-fungible token (NFT) to represent the product on an NFT platform (172), a matching module (174) configured via computer executable instructions to match the product characteristics with requirements of a buyer and manufacturing capabilities of a producer, and a traceability module (176) to verify success of a manufacturing process.

Abstract: A method for adding assets to a distribution network includes using a placement generation engine to generate discrete placements of assets to be added to the distribution network subject to asset-installation constraint(s). Each placement is defined by a mapping of an asset, from multiple assets of different sizes, to a placement location defined by a node or branch of the distribution network. Each placement is used to update an operational circuit model of the distribution network for tuning control parameters of one or more controllers of the distribution network for robust operation over a range of load and/or generation scenarios. A cost function is evaluated for each placement based on a simulated operation. Parameters of the placement generation engine are iteratively adjusted based on the evaluated cost functions to arrive at an optimal placement and sizing of assets to be added to the distribution network.

Abstract: In described embodiments of method for executing autonomous bin picking, a physical environment comprising a bin containing a plurality of objects is perceived by one or more sensors. Multiple artificial intelligence (AI) modules feed from the sensors to compute grasping alternatives, and in some embodiments, detected objects of interest. Grasping alternatives and their attributes are computed based on the outputs of the AI modules in a high-level sensor fusion (HLSF) module. A multi-criteria decision making (MCDM) module is used to rank the grasping alternatives and select the one that maximizes the application utility while satisfying specified constraints.

Abstract: According to aspects of embodiments described herein, an optical computing device (100) comprises a plurality of input waveguides (101), a photonic meta-surface (103) in contact with the plurality of input waveguides, and a plurality of output waveguides (105) in contact with the transformational meta-surface. The optical computing device may be configured to perform a mathematical operation may be a matrix multiplication. A computer-implemented method (300) of designing an optical computing device includes a plurality of input waveguides, a photonic meta-surface, and a plurality of output waveguides, the method includes exciting each input waveguide one-by-one (303) and measuring the energy at the input region and the output region (305) to determine a contribution of the current input waveguide. The sum of contributions (307) of all input waveguides are compared to a target transformation (315) to determine a loss value used to update a set of design parameters (317).

Abstract: System and method enable development of an industrial metaverse used in engineering by computer aided design. A metaverse pipeline includes a plurality of metaverse entities including at least one design application and one simulation application configured to develop a virtual environment metaverse representation of an industrial facility. A metaverse knowledge graph describes semantics and relationships between the metaverse pipeline entities and is configured to exchange information across the software applications of the metaverse pipeline entities of various platforms while developing the virtual environment metaverse. The metaverse knowledge graph enables synchronization across metaverse development platforms, such that updates to one platform are transferrable, whereby the virtual entities and environment can be assimilated according to new edits.

Abstract: A computer-implemented method for failure classification of a surface treatment process includes receiving one or more process parameters that influence one or more failure modes of the surface treatment process and receiving sensor data pertaining to measurement of one or more process states pertaining to the surface treatment process. The method includes processing the received one or more process parameters and the sensor data by a machine learning model deployed on an edge computing device controlling the surface treatment process to generate an output indicating, in real-time, a probability of process failure via the one or more failure modes. The machine learning model is trained on a supervised learning regime based on process data and failure classification labels obtained from physics simulations of the surface treatment process in combination with historical data pertaining to the surface treatment process.

Abstract: System and method optimize recyclability of an electronic device during manufacturing design A manufacturing design software produces engineering bill of materials, manufacturing bill of materials, and bill of process for the manufacturing design. Recycling process plan engine constructs a recycling process plan for the electronic device according to the manufacturing design. A virtual model of recycling processes is constructed by mapping needed skills to corresponding recycling equipment using a library of recycling equipment information. Recycling process plan engine uses the virtual model to simulate the recycling plan and optimizes each recycling process, and the overall sequence of recycling processes, according to an objective function. Evaluator module receives key performance indicator values from a virtual model simulation and calculates the value of the objective function based on key performance indicators.

Abstract: An edge device can be configured to perform industrial control operations within a production environment that defines a physical location. The edge device can include a plurality of neural network layers that define a deep neural network. The edge device be configured to obtain data from one or more sensors at the physical location defined by the production environment. The edge device can be further configured to perform one or more matrix operations on the data using the plurality of neural network layers so as to generate a large scale matrix computation at the physical location defined by the production environment. In some examples, the edge device can send the large scale matrix computation to a digital twin simulation model associated with the production environment, so as to update the digital twin simulation model in real time.

Abstract: System and method simulate power distribution system reconfigurations for multiple contingencies. Decision tree model is instantiated as a graph with nodes and edges corresponding to simulated outage states of one or more buses in the power distribution system and simulated states of reconfigurable switches in the power distribution system, Edges related to each outage are disconnected. A reconfiguration path is determined with a plurality of switches reconfigured to a closed state by an iteration of tree search algorithms. A simulation estimates feeder cable and transformer loading and bus voltages on the reconfigured path for comparing against constraints including system capacity ratings and minimum voltage.

Abstract: In an example aspect, a first object (e.g., an electronic component) is inserted by a robot into a second object (e.g., a PCB). An autonomous system can capture a first image of the first object within a physical environment. The first object can define a mounting interface configured to insert into the second object. Based on the first image, a robot can grasp the first object within the physical environment. While the robot grasps the first object, the system can capture a second image of the first object. The second image can include the mounting interface of the first object. Based on the second image of the first object, the system can determine a grasp offset associated with the first object. The grasp offset can indicate movement associated with the robot grasping the first object within the physical environment. The system can also capture an image of the second object. Based on the grasp offset and the image of the second object, the robot can insert the first object into the second object.

Abstract: A method of managing change in a complex system begins with identifying an unsatisfied need to be met by the system. To satisfy the need a proposed change to the system to satisfy the need is represented a high-level representation of the proposed change. The high-level representation is mapped to a low-level executable semantic model, which is used to validate the proposed change and ensure the proposed change meets the identified and does not require additional changes to the system. On a condition that the validating steps determines that additional changes are required the additional changes are represented in the high-level representation of the system; the high-level change is mapped to the low-level executable semantic model and the additional changes are re-validated.

Abstract: Systems and methods are provided for generating a flow control plan for a plurality of components in a flow control system. A decentralized multi-agent control framework is used to plan and schedule for each agent independently without a central processor. Each agent of the multi-agent control framework separately optimizes a local portion of the system as a function of values for one or more parameters. Agents communicate with other connected agents, sharing values for parameters. The communication provides a negotiation and consensus for values of the shared parameters that are used by the agent to recalculate optimized parameters values for the local portion of the system.

Abstract: A computer-implemented method for constructing structures using beams bounded by quadric surfaces of revolution includes generating a quador beam within a computer-aided design (CAD) tool. The quador beam comprises two spheres at opposing endpoints, and the beam is bounded by a quadric surface of revolution around an axis of symmetry joining the center of the two spheres. The quadric surface of revolution abuts with tangent continuity with the surface of each of the spheres. Once generated, the quador beam can be visualized in the CAD tool or another display medium.

Abstract: A method for estimating an admittance matrix for a transmission network comprises estimating in an upper layer time-series data for hidden nodes in the transmission network, computing in a lower layer an estimated admittance matrix for the transmission network and iteratively exchanging information between the upper layer and the second lower layer to produce a final admittance matrix for the transmission matrix. In some embodiments, the method may further comprise spatially dividing the transmission network into a plurality of subnets in the upper layer and estimating the time-series data for the hidden nodes for each subnet. Estimating the times series data for the hidden nodes for each subnet in parallel.

Abstract: A computer-implemented method for constructing structures using beams bounded by quadric surfaces of revolution includes generating a quador beam within a computer-aided design (CAD) tool. The quador beam comprises two spheres at opposing endpoints, and the beam is bounded by a quadric surface of revolution around an axis of symmetry joining the center of the two spheres. The quadric surface of revolution abuts with tangent continuity with the surface of each of the spheres. Once generated, the quador beam can be visualized in the CAD tool or another display medium.