A method and system for adapting a CNC machine tool path from a nominal workpiece shape to an actual workpiece shape. The method includes defining a grid of feature points on a nominal workpiece shape, where the feature points encompass an area around the machine tool path but do not necessarily include points on the machine tool path. A probe is used to detect locations of the feature points on an actual workpiece. A space mapping function is computed as a transformation from the nominal feature points to the actual feature points, and the function is applied to the nominal tool path to compute a new tool path. The new tool path is used by the CNC machine to operate on the actual workpiece. The feature points are used to characterize the three dimensional shape of the working surface of the actual workpiece, not just a curve or outline.

This invention provides a novel tool path planning method for five-axis flank milling by imposing the constraints of curve interpolation on the tool path. The tool motion is described in the form of spline curves during its optimization-driven calculation process, instead of discrete cutter locations in CNC linear interpolation. The coefficients of the curve equations are generated by minimizing accumulated geometrical errors on the machined surface using optimization algorithms. The continuity imposed by the spline motion reduces uneven modifications of cutter locations during the optimization process. The resultant tool path yields superior.

Methods, systems, and apparatus, including medium-encoded computer program products, for computer aided design and manufacture of physical structures using toolpaths generated by reinforcement learning for use with subtractive manufacturing systems and techniques, include: obtaining, in a computer aided design or manufacturing program, a three dimensional model of a manufacturable object; generating toolpaths that are usable by a computer-controlled manufacturing system to manufacture at least a portion of the manufacturable object by providing at least a portion of the three dimensional model to a machine learning algorithm that employs reinforcement learning, wherein the machine learning algorithm includes one or more scoring functions that include rewards that correlate with desired toolpath characteristics comprising toolpath smoothness, toolpath length, and avoiding collision with the three dimensional model; and providing the toolpaths to the computer-controlled manufacturing system to manufacture at least the portion of the manufacturable object.

This method for generating a tool path for processing a workpiece is provided with: a step for setting a first reference plane with respect to the workpiece; a step for setting, with respect to the workpiece, a second reference plant which is not parallel to the first reference plane; a step for interpolating, on the basis of the first reference plane and the second reference plane, a plurality of third reference planes, which are not parallel to each other, between the first reference plane and the second reference plane; a step in which partial tool paths for processing the workpiece are generated for each of the plurality of third reference planes on the basis of the corresponding third reference plane; and a step for generating a tool path by sequentially connecting the partial tool paths of the plurality of third reference planes.

Methods, systems, and apparatus, including medium-encoded computer program products, for computer aided design and manufacture of physical structures using toolpaths generated by reinforcement learning for use with subtractive manufacturing systems and techniques, include: obtaining, in a computer aided design or manufacturing program, a three dimensional model of a manufacturable object; generating toolpaths that are usable by a computer-controlled manufacturing system to manufacture at least a portion of the manufacturable object by providing at least a portion of the three dimensional model to a machine learning algorithm that employs reinforcement learning, wherein the machine learning algorithm includes one or more scoring functions that include rewards that correlate with desired toolpath characteristics comprising toolpath smoothness, toolpath length, and avoiding collision with the three dimensional model; and providing the toolpaths to the computer-controlled manufacturing system to manufacture at least the portion of the manufacturable object.

Methods and system for computing integrals over geometric domains using moment-base representations for interoperability are disclosed. A first computing device may receive data for geometric and field representations of an object, the geometric representation specifying a geometric domain of the object, and the field representation specifying a spatially varying physical quantity. The first computing device may integrate a predetermined set of basis functions over the geometric domain multiplied by a field to derive a moment-vector for the object, the moment-vector encapsulating an analytic formulation of the geometric domain that is independent of the geometric and field representations. The first computing device may computationally generate quadrature rules for integrating an arbitrary function by applying moment-fitting to the moment-vector. The quadrature rules may be provided to a second computing device, which may integrate the arbitrary function over the geometric domain by applying the quadrature rules, independently of the geometric and field representations.

A method and system for adapting a CNC machine tool path from a nominal workpiece shape to an actual workpiece shape. The method includes defining a grid of feature points on a nominal workpiece shape, where the feature points encompass an area around the machine tool path but do not necessarily include points on the machine tool path. A probe is used to detect locations of the feature points on an actual workpiece. A space mapping function is computed as a transformation from the nominal feature points to the actual feature points, and the function is applied to the nominal tool path to compute a new tool path. The new tool path is used by the CNC machine to operate on the actual workpiece. The feature points are used to characterize the three dimensional shape of the working surface of the actual workpiece, not just a curve or outline.

Provided is a tool path generating method for processing wood as a processing object by a multi-axis processing machine, including a plane extracting step of extracting at least one plane included in a processing objective region being a region at which the processing object is processable, a plane processing determining step of determining whether or not the plane extracted in the plane extracting step is processable by a disk blade attached to the multi-axis processing machine, a disk blade processing path generating step of generating a processing path for the disk blade on the plane determined as being processable in the plane processing determining step, and a tool path generating step of generating a tool path including the processing path for the disk blade.

This method for generating a tool path for processing a workpiece is provided with: a step for setting a first reference plane with respect to the workpiece; a step for setting, with respect to the workpiece, a second reference plant which is not parallel to the first reference plane; a step for interpolating, on the basis of the first reference plane and the second reference plane, a plurality of third reference planes, which are not parallel to each other, between the first reference plane and the second reference plane; a step in which partial tool paths for processing the workpiece are generated for each of the plurality of third reference planes on the basis of the corresponding third reference plane; and a step for generating a tool path by sequentially connecting the partial tool paths of the plurality of third reference planes.

Methods, systems, and apparatus, including medium-encoded computer program products, for computer aided design and manufacture of physical structures using toolpaths generated by reinforcement learning for use with subtractive manufacturing systems and techniques, include: obtaining, in a computer aided design or manufacturing program, a three dimensional model of a manufacturable object; generating toolpaths that are usable by a computer-controlled manufacturing system to manufacture at least a portion of the manufacturable object by providing at least a portion of the three dimensional model to a machine learning algorithm that employs reinforcement learning, wherein the machine learning algorithm includes one or more scoring functions that include rewards that correlate with desired toolpath characteristics comprising toolpath smoothness, toolpath length, and avoiding collision with the three dimensional model; and providing the toolpaths to the computer-controlled manufacturing system to manufacture at least the portion of the manufacturable object.