Abstract: A design engine systematically explores a design space associated with a design problem related to mechanical assemblies. The design engine implements a constraint programming approach to produce mechanical assembly configurations that adhere to a set of design constraints. For each feasible configuration, the design engine then optimizes various parameters to generate design options that meet a set of design objectives. With these techniques, the design space can be explored very quickly to generate significantly more feasible design options for the mechanical assembly than possible with conventional manual approaches. Accordingly, numerous design options can be generated that may otherwise never be produced using those conventional approaches.

Abstract: An apparatus includes: at least one conductive wire spool; a motion platform that includes a first actuator for following a first programmed motion in a first dimension and a second actuator for following a second programmed motion in a second dimension that is perpendicular to the first direction; a deposition head that is mounted to the motion platform, receives a conductive wire from the conductive wire spool, and attaches the conductive wire onto a surface of a substrate; and a controller that causes the motion platform to move along a programmed deposition path on the surface of the substrate, wherein at least a portion of the programmed deposition path varies in the first dimension and in the second dimension.

Abstract: A computer-implemented method for generating a forward-kinematics machine-learning (ML) model for controlling a machine includes: based on a target state for the machine, determining an ideal roto-translation for an end effector associated with the machine; using a first version of the forward-kinematics ML model, determining a predicted roto-translation for the end effector based on the target state; determining a predicted location for at least one calibration point on the end effector based on the predicted roto-translation for the end effector; determining a difference between the predicted location for the at least one calibration point and a measured location for the at least one calibration point; and generating a second version of the forward-kinematics ML model based on the difference.

Abstract: A computer-implemented method for controlling a machine includes: determining a first state for the machine based on a kinematics model of the machine and a target roto-translation for an end effector associated with the machine; determining, using a forward-kinematics machine-learning model, a difference between the target roto-translation of the end effector and a first roto-translation of the end effector when the machine is in the first state; based on the difference between the target roto-translation and the first roto-translation, determining a second state for the machine; and outputting a control input for one or more actuators that causes the machine enter into the second state.

Abstract: Design process that performs geometry synthesis on a 3D model of a product based on a design problem statement and manufacturing constraints associated with a manufacturing machine intended to manufacture the product. The manufacturing constraints may include dimensions for a tool bit, dimensions for a tool head, a set of machining directions of the manufacturing machine, or any combination thereof. For a 5-axis manufacturing machine, the set of machining directions may be determined by a “NormalSearch” algorithm and/or a “HeatSearch” algorithm. The geometry synthesis produces a design solution comprising a final 3D model of the product, whereby each point on the boundary of the final 3D model is determined to be accessible by a tool bit and/or tool head in at least one machining direction of the manufacturing machine. Thus, the design solution for the product is more easily and directly manufacturable by the manufacturing machine.

Abstract: A computer-implemented method for positioning a workpiece for a computer numerical controlled (CNC) process includes: causing a positioner to move an end effector to an initial position; receiving first position information associated with a first optical signal transmitted from a first optical target coupled to the workpiece; receiving second position information associated with a second optical signal transmitted from a second optical target coupled to the end effector; determining an offset between the initial position and a target position for the end effector based on the first position information and the second position information; and causing the positioner to move the end effector to a final position based on the offset.

Abstract: A computer-implemented method for performing laser engraving operations on a target engraving region, the method comprising: causing a positioner to move a laser-engraving head to a first position; while the laser-engraving head is disposed at the first position, determining a location of the target engraving region; while the laser-engraving head is disposed at the first position, determining a location of an actual engraving region; determining an offset based on the location of the target engraving region and the location of actual engraving region; modifying at least one process parameter value for an engraving head to generate a modified parameter value; and while the laser-engraving head is disposed at the first position, causing the laser-engraving head to perform one or more laser engraving operations based on the modified parameter value.

Abstract: A method for fabricating a multi-material structure includes: forming a structural member with at least one open-cell void that is formed on a surface of the structural member; depositing a first portion of a polymeric skin on the surface; and depositing a second portion of the polymeric skin within the at least one open-cell void.

Abstract: A multi-material structure includes: a structural member that includes an isotropic material and at least one open-cell void formed in the isotropic material; and a skin that includes a polymetric material and is disposed on a surface of the structural member and within the at least one open-cell void.

Abstract: A design engine generates a configuration option that includes a specific arrangement of interconnected mechanical elements adhering to one or more design constraints. Each element within a given configuration option is defined by a set of design variables. The design engine implements a parametric optimizer to optimize the set of design variables associated with each configuration option. For a given configuration option, the parametric optimizer discretizes continuous equations governing the physical dynamics of the configuration. The parametric optimizer then determines the gradient of an objective function based on the discretized equations the gradient of objective and constraint functions based on discrete direct differentiation method or discrete adjoint variable method derived directly from the discretized motion equations. Then, the parametric optimizer traverses a design space where the configuration option resides to reduce improve the objective function, thereby optimizing the design variables.

Abstract: A design application receives an exemplary design from an end-user having one or more functional attributes relevant to solving a design problem. The design application then generates a set of labels that describes the functional attributes of the exemplary design. Based on the set of labels, the design application explores a functional space to retrieve one or more system classes having functionally descriptive labels that are similar to the set of labels generated for the exemplary design. The one or more system classes include different approaches to solving the design problem, and represent systems having at least some functional attributes in common with the exemplary design.

Abstract: A design application is configured to perform a system-level optimization of a collection of system components. The design application iteratively executes a multi-objective solver to optimize structural and functional relationships between the system components in order to meet global design criteria and generate a system design. The design application initializes the design process by extracting from a knowledge base system templates having taxonomic, structural, or functional attributes relevant to the system design. The design application generates the knowledge base by mining taxonomic, structural, and functional relationships from a corpus of engineering texts.

Abstract: A computer-implemented method for positioning a workpiece within a processing system includes: extracting at least one feature of a workpiece from a three-dimensional model of the workpiece; determining a location of the at least one feature relative to a work surface of the processing system based on geometric information included in the three-dimensional model; and projecting a laser trace onto the location via a laser projector.

Abstract: In one embodiment, a model generator generates a new model for a behavior of a system based on an existing, authoritative model. First, a mapping generator generates a mapping model that maps authoritative values obtained via the authoritative model to measured values that represent the behavior of the system. Subsequently, the model generator creates the new model based on the authoritative model and the mapping model. In this fashion, the mapping model indirectly transforms the authoritative model to the new model based on the measured values. Advantageously, the authoritative model enables the model generator to increase a rate of accuracy improvement experienced while developing the new model compared to a rate of accuracy improvement that would be experienced were the new model to be generated based on conventional modeling techniques. In particular, for a given sampling budget, the model generator improves the accuracy of the new model.

Abstract: Embodiments of the invention disclosed herein provide techniques for generating an alternative design recommendation. The techniques include determining, via a processor, a first function associated with one or more first components included in a first design. The techniques further include analyzing, via the processor, a plurality of components included in a database to select one or more second components associated with a second function that corresponds to the first function. The techniques further include causing an alternative design recommendation that includes the one or more second components to be output for display.

Abstract: An optical device includes: a first connector for a first optical fiber that transmits a first laser beam from a first laser source; a second connector for a second optical fiber that transmits a second laser beam from a second laser source; and one or more optical elements that direct the first laser beam from the first connector to a first beam collimator and direct the second laser beam from the second connector to the first beam collimator, wherein, the first beam collimator: produces a first collimated beam based on the first laser beam, directs the first collimated beam to a laser-scanning device, produces a second collimated beam based on the second laser beam, and directs the second collimated beam to the laser-scanning device.

Abstract: A design engine consolidates portions of a mechanical assembly design to reduce the number of components included in the design. The design engine analyzes the design to determine various criteria associated with the assembly. Then, the design engine identifies a group of components within the design to be consolidated. The design engine determines a volumetric region where the group of components resides and then subdivides the volumetric region. The design engine then initiates a generative design process based on the determined criteria to create geometry within each subdivision of the volumetric region. The newly generated geometry includes fewer components than the initial group of components. The design engine then replaces the group of components with the newly generated geometry, thereby consolidating the group and reducing the total number of components included in the design.

Abstract: A computer-implemented method for generating laser engraving instructions for performing a patterning process on a workpiece surface includes receiving a first input value indicating a first laser-pulse pattern and a second input value for a laser parameter associated with a laser-engraving system; and generating a machine-command sequence for the laser-engraving system based on the first input value and the second input value.

Abstract: Embodiments of the invention disclosed herein provide techniques for generating a design autocomplete recommendation. The techniques include determining one or more first components included in a first design. The techniques further include analyzing, via the processor, a plurality of designs included in a database to select a second design that includes one or more second components that correspond to the one or more first components. The techniques further include selecting, via a processor, one or more third components included in the second design that are not included in the first design. The techniques further include causing an autocomplete recommendation that includes the one or more third components to be output.

Abstract: A method for laser engraving a three-dimensional pattern into a surface of a workpiece, the method comprising: positioning a laser-engraving head to engrave a first engraving region of the workpiece; and applying a first plurality of laser pulses to a set of first predetermined locations within the first engraving region, wherein the first set of predetermined locations within the first engraving region is based on a probability distribution function that corresponds to a portion of the three-dimensional pattern that is associated with the first engraving region.