Cognitive robotic tool selector and applicator

Robotic processor embodiments determine via graphical image analysis physical attributes of an engagement area of a work-piece that a specified tool physically engages to execute a specific action. The processors identify a model set plurality of alternate substitute tools that are each available within a physical environment of the engagement area and have a body portion with physical dimensions that conform to physical dimensions of the work-piece engagement area, and thereby select a substitute tool that has a body portion that best conforms to the physical dimensions of the work-piece engagement area and meets constraints for substitute tool selection for executing the specific action.

BACKGROUND

The term “robot” generally refers to a programmable machine capable of carrying out a complex series of manual actions automatically and autonomously (without the direct supervision or control of a human manager). Robots may assist or replace humans in performing a wide variety of tasks and are often deployed to perform repetitive or dangerous tasks which humans prefer not to do, or are unable to do because of size limitations, or which take place in extreme environments such as outer space or the bottom of the sea, or otherwise where the costs involved in deployment are less than the costs identified in using a human to perform a specified task.

SUMMARY

In one aspect of the present invention, a computerized method for cognitive robotic substitute tool selection and application includes executing steps on a computer processor. Thus, a computer processor is configured to, in response to determining that a specified tool is not available for use in executing a specific action on a work-piece, determine via graphical image analysis physical attributes of an engagement area of the work-piece that the specified tool physically engages to execute the specific action. The configured processor identifies a model set plurality of alternate substitute tools that are each available within a physical environment of the engagement area and have a body portion with physical dimensions that conform to physical dimensions of the work-piece engagement area. The configured processor thereby selects a substitute tool that has a body portion that best conforms to the physical dimensions of the work-piece engagement area and meets constraints for substitute tool selection for executing the specific action.

In another aspect, a system has a hardware processor in circuit communication with a computer readable memory and a computer-readable storage medium having program instructions stored thereon. The processor executes the program instructions stored on the computer-readable storage medium via the computer readable memory and is thereby configured to, in response to determining that a specified tool is not available for use in executing a specific action on a work-piece, determine via graphical image analysis physical attributes of an engagement area of the work-piece that the specified tool physically engages to execute the specific action. The configured processor identifies a model set plurality of alternate substitute tools that are each available within a physical environment of the engagement area and have a body portion with physical dimensions that conform to physical dimensions of the work-piece engagement area. The configured processor thereby selects a substitute tool that has a body portion that best conforms to the physical dimensions of the work-piece engagement area and meets constraints for substitute tool selection for executing the specific action.

In another aspect, a computer program product for cognitive robotic substitute tool selection and application has a computer-readable storage medium with computer readable program code embodied therewith. The computer readable hardware medium is not a transitory signal per se. The computer readable program code includes instructions for execution which cause the processor to, in response to determining that a specified tool is not available for use in executing a specific action on a work-piece, determine via graphical image analysis physical attributes of an engagement area of the work-piece that the specified tool physically engages to execute the specific action. The processor is thereby caused to identify a model set plurality of alternate substitute tools that are each available within a physical environment of the engagement area and have a body portion with physical dimensions that conform to physical dimensions of the work-piece engagement area. The processor is thereby caused to select a substitute tool that has a body portion that best conforms to the physical dimensions of the work-piece engagement area and meets constraints for substitute tool selection for executing the specific action.

DETAILED DESCRIPTION

Characteristics are as follows:

Rapid elasticity: capabilities can be rapidly and elastically provisioned, in some cases automatically, to quickly scale out and be rapidly released to quickly scale in. To the consumer, the capabilities available for provisioning often appear to be unlimited and can be purchased in any quantity at any time.

Service Models are as follows:

Deployment Models are as follows:

FIG.3is a schematic of an example of a programmable device implementation10according to an aspect of the present invention, which may function as a cloud computing node within the cloud computing environment ofFIG.2. Programmable device implementation10is only one example of a suitable implementation and is not intended to suggest any limitation as to the scope of use or functionality of embodiments of the invention described herein. Regardless, programmable device implementation10is capable of being implemented and/or performing any of the functionality set forth hereinabove.

FIG.4illustrates cognitive robotic tool application according to embodiments of the present invention. A robotic device processor (for example, a central processing unit (CPU)) executes code (such as code installed on a storage device in communication with the processor) and is thereby configured according to the present invention (a “configured processor”) to receive and understand (process) an input command at102to execute a specific mechanical or physical action upon a work-piece via use of a tool.

At104the configured processor determines that a tool that is indicated within a tool data repository101(for example, a database of information indexed to a storage memory device, a cloud resource, etc.) as appropriate for executing the action is not available. For example, where the physical action is “unscrew a No. 2 standard-head (single-slot) machine screw,” and a tool indicated by the action command data, or by data within the tool data repository101, as specified or appropriate for the action is a “No. 2 standard-head screwdriver” that fits a rotating tool of the robot, the configured processor determines at104that the specified socket bit is missing from a tool box provided to the robot. The tool data repository101includes historical data and information about previous executions of the specific action on the work-piece by historic tools inclusive of the specific tool and of other, different, substitute tools.

At106, in response to determining that the specified tool is not available for use in executing the specific action on the work-piece, the configured processor determines physical attributes (illustrative but not limiting or exhaustive example include dimensions, material qualities, environmental context, etc.) of the work-piece “engagement area”: the area or areas that the specified tool physically engages to execute the specific action. More particularly, the configured processor measures or otherwise determines physical attributes of regions or areas of engagement of the respective work-piece and of tools that historically engage said engagement areas in executing the specified action in historic data within the tool data repository101(“historic tools”) that include the specified tool. The determined physical dimensions and attributes may include physical shapes, height, width, depth and other dimensions, orientations, and atmospheric and environmental attributes (temperature, pressure, winds, presence or absence of water, lubricants, etc.); ranges of, or constraints on, motion of the historic tools or work-piece in executing the specific action within the physical attributes of the engagement action area; dimensions of other supporting devices used during execution of the action (supporting walls, ledges, lips or other resting or aligning surfaces; strapping, chains, and other constraining or force transferring components, etc.); and still other attributes descriptive of the engagement areas will be apparent to one skilled in the art. The determinations at106may be retrieved from or based upon historic or other data stored in the tool data repository101or available thereto (for example, through a network communication to another, cloud resource), or they may be made by the configured processor via analyzing image data or other data representative of the engagement areas, including as discussed below in other embodiments of the present invention.

At108the configured processor determines, identifies or defines constraints for substitute tool selection for executing the specific action on the work-piece as a function of the determined physical attributes of the engagement; illustrative but not limiting or exhaustive examples include cost and priority constraints; maximum and minimum shape dimensions (for example, tool lip thickness that will fit within a “No. 2 standard-head screw slot”), material composition, material strength or modulus; compatibility of material properties to the engagement area atmospheric and environmental attributes (for example, water or liquid-resistant surfaces or material integrity for operations in the rain or under water, spark-free surface treatments within potential explosive atmospheres; non-conductive properties with respect to electrified engagement areas); maximum or minimum replacement costs or risk of loss amounts associated with damage to the substitute tool or work-piece from improper or deficient performance in executing the action; and still other constraints will be apparent to one skilled in the art.

At110the configured processor selects a substitute tool that has a body portion and/or other attributes that best conform to the physical dimensions of the work-piece engagement area and meets the constraints determined at108from a universe of possible tools, and at112utilizes the selected tool to execute the specific action. More particularly, the robotic system processor performs a feasibility analysis on selected ones of a universe of alternate tool or solution objects to select a best or lowest-cost one based on data obtained from historical data analysis. For example, the configured processor determines from previous iterations or analysis that thin paper strips cannot be used as an adequate substitute for a bandage roll to dress a wound (due to body fluids seeping through, failure to conform to and seal a wound opening from air or contaminants, failure to maintain structural integrity and remain in place for an adequate time, etc.). The configured processor may also identify that a cloth object may function as a substitute for the bandage roll in dressing a wound, and between two different cloth objects select a clean rag over a dress shirt object for use, in recognition that the rag has no replacement cost while replacement of the dress shirt will incur a financial cost. Further, if a context constraint indicates that stopping bleeding immediately is required (due to a severe wound), satisfactory execution of the action may be prioritized over cost, wherein the material cost is weighted lower or disregarded and, so that the best option for dressing the wound is selected regardless of cost of replacement.

Feasibility analysis at110may include the use of cloud server or other networked resources to gather material properties and determine resultant operative capacities. Embodiments of a robotic system perform contextual analysis at110of the action to be performed, determining amount of force required, direction of applied force, type of applied action, how the action is to be performed, etc., and identify and select alternate solutions or tools based on feasibility and cost-benefit analysis. Cost-benefit analysis generally considers priority and importance of the action and the cost of using each alternate solution or tool. Thus, in response to determining that the risk of loss or other cost of the use any identified substitute tool exceeds a threshold at110, the configured processor refrains from execution of the action, pauses, until the specified or required tool becomes available, or the cost drops below the threshold in another iteration of determination of the cost (for example, in response to dynamic update of the constraints determined at108, or of the tool specification and usage data101).

Some embodiments of the present invention may also dynamically learn and improve substitute tool selection and utilization processes, such as those performed at110or at112. Thus, in response to user feedback, at114the configured processor of the present example determines whether the selected substitute tool adequately executed the specific action upon the work-piece, and updates the historic data accordingly. More particularly, in response to determining at114that the selected substitute tool did not adequately execute the specific action upon the work-piece (“No” condition), at116the configured processor lowers weightings (likelihoods, score values, confidences, etc.) used for selection of the selected tool for executing the specific action on work-piece engagement areas having the same or similar determined physical attributes in subsequent iterations of the process at110, thereby lowering the frequency or possibility that a tool have a poor performance quality is selected again for use in executing the specific action in a similar engagement context.

Otherwise, in response to determining at114that the selected substitute tool adequately executed the specific action upon the work-piece (“Yes” condition), at118the configured processor maintains or increases the weightings, etc., used for selection of the selected tool for executing the specific action on the work-piece engagement areas having the same or similar determined physical attributes in subsequent iterations at110, thereby maintaining or increasing a frequency, likelihood or possibility that a tool determined to have adequate performance is selected again for use in executing the specific action.

FIG.5illustrates one embodiment of the present invention that selects a substitute tool that has attributes that meet determined constraints (at110ofFIG.4) as a function of searching a knowledge base of substitute tool attributes that are most likely to meet the determined constraints. Thus, at202a processor configured according to the present invention (“configured processor”) compares values of the determined constraints (for example, rectangular tool lip with thickness less than but within 75% of width dimension of “No. 2 standard-head screw slot”; formed by material having a strength or modulus value of no less than 105% percent of a torque required to unscrew a work-piece screw; material resistant to dissolution or structural compromise in water, for an under-water execution constraint; and having a maximum replacement cost value below a risk threshold, reflecting risk of damage for use of tool outside scope of designed function) to tool attributes indexed within a tool knowledge base of the tool data repository101, to thereby identify a subset of tools of a universe of possible tools that have tool attributes indexed within the tool knowledge base that match or satisfy the values of the determined constraints.

At204the configured processor selects a lowest cost one of the subset of tools as the tool substitute. For example, where a plastic spoon and a metal spoon each have handle tip attributes indexed within the tool data repository101that meet the constraints as to rectangular tool lip thickness, strength/modulus value of no less than 105% percent of a torque required to unscrew the work-piece screw; material resistant to dissolution or structural compromise in water; and maximum replacement cost value below the risk threshold; the configured processor selects the metal spoon over the plastic spoon at204as a function of determining that the metal spoon has a lower risk of failure cost due to use outside the scope of its designed function (namely, as an eating utensil, not a tool to impart torque forces). The determination of lower cost may also be based on determining a corresponding lower risk or exposure to lost time and/or resource expenditures to replace the failed tool, and repeat with another substitute tool, as the metal material is stronger than the plastic handle material.

FIG.6illustrates another embodiment of the present invention that selects a substitute tool that has attributes that meet determined constraints as a function of a visual analysis of work-piece engagement areas. Thus, at302a robotic device processor configured according to the present invention (“configured processor”) receives and understands (processes) an input command to execute a specific mechanical or physical action upon a work-piece via use of a specific (specified) tool. At304the configured processor determines that the specified tool is not available. For example, wherein the physical action specified for execution as processed or recognized at302is “unscrew a No. 2 standard-head (single-slot) screw,” the work-piece is a No. 2 standard-head (single-slot) screw (such as the screw402illustrated inFIG.7), and the specified tool is a “No. 2 standard-head screwdriver” (such as the screwdriver404illustrated inFIG.7) that fits a rotating tool attachment appendage of the robot (not shown), the configured processor determines at304that no screwdriver meeting the specification is available to the robot (it is missing from a designated supply area, etc.).

In response to determining that the specified tool is unavailable, at306the configured processor determines, via image data analysis, physical dimensions of a “tool engagement area” of the work-piece that is engaged by the missing, specified tool to execute the specified job or action. Thus, the configured processor acquires image data of the work-piece engagement area from a camera device or other source and analyzes the image data to determine physical dimensions that include length, depth and width of the work-piece area engaged by the specified tool: for example, length, depth and width dimensions of the slot403of the screw head402illustrated inFIG.7.

At308the configured processor determines contextual constraints for executing the specified action as a function of image analysis of the work-piece engagement area and the physical environment of the engagement area. The contextual constraints may include a force estimated to be required to be imparted by a substitute tool on the work-piece: in the example ofFIG.7, an insertion force required to engage the screw head slot403, and a rotation toque required to unscrew the work-piece screw402, determined (via image data analysis) from identification of the work-piece materials and size conditions in view of the physical attributes, wherein different identified values of work-piece materials (plastic, wood, metal, aluminum, brass, etc.) shaft diameters (as estimated from size of screw head determined from image data), and environmental conditions (lubrication visible or not, rust visible or not, under water, indoors or exterior, weathered conditions, etc.) result in corresponding different determinations of the minimum insertion force and torque requirements for substitute tool selections by the configured processor.

Determining contextual constraints at308may also include determining length, depth and width dimensions of an “operating area” that encompasses the engagement area in an orientation affording access to a tool to physically engage the engagement area and execute the specific action in directions of motion required to generate forces determined for the executed action. Thus, the configured processor may process image data of the work-piece engagement area and operating area that is acquired by a camera or other image data sensor to determine respective measurements of the work-piece engagement and operating areas, to thereby estimate maximum tool displacement diameters defined by motion of the tool.

With reference to an example illustrated inFIG.7, the configured processor at306determines length, depth and width dimensions of an engagement area slot403of a work-piece screw head402; and at308, length, depth and width dimensions of an operating area constraint encompassing the screw head slot403and projecting outward from the screwhead402on a clearance radius from a central axis of the screw about the which the screw rotates to tighten or loosen upon a thread engagement with another work-piece (not shown), wherein the clearance radius is a length from the axis of the screw that defines minimum dimensions of a volume of space that is free of visible obstructions from surrounding structures, and so that a substitute tool will fit within the operating area and engage the work-piece engagement area (screw head slot403) and freely rotate the engaged screw head slot403without obstruction from surrounding elements (for example, sidewalls, solid edges, gearing pieces, etc.)

Determining contextual constraints at308may also include environmental constraints. For example, the configured processor may set atmospheric pressure data obtained from barometric sensors as a minimum operative atmospheric pressure for the substitute tool; determine that the substitute tool must meet a moisture constraint, to function under water or in rain or other damp conditions, as determined by image or water sensor data or weather data sensor inputs or weather prediction data; and still other operating environment condition constraints will be apparent to one skilled in the art.

At310the configured processor creates (defines, etc.) a model set of alternate, substitute devices, tools or solutions that each have body portions with dimensions that fit the physical dimensions of the work-piece engagement area and are identified as available within an environment of the robot. The model set tools may be identified as objects visible (via image data analysis) within camera data feeds of an environment of the robot; or as indexed to or flagged in association with the specific missing tool, the executed action and/or the physical dimensions of the work-piece engagement area in a tool knowledge base, such as within an object data repository301and indexed to respective storage locations accessible to the robot. For example, the configured processor may process image data at310that is acquired from surroundings of the robot, including images of counters, work benches, contents of drawers opened by the robot, etc., in a physical search routine via robotic motors and appendages, to find objects having body portions of dimensions that appear to fit the engagement areas of the work-piece. The configured processor may also search drawer contents databases within the data repository301to find associated or indexed objects and their indicated locations (which drawer or utensil bin, etc.).

Thus,FIG.7illustrates one model set of substitute tools405generated by the configured processor at310in response to analyzing image data to identify objects within a kitchen-area domain of the configured processor robot, wherein the configured processor determines that each has a body portion defined by dimensions that meet thresholds of (fit) the work-piece screw402slot403length, width, and depth dimensions: a ladle406having a curved handle end shape portion408; a slotted spoon410having a flat handle end shape portion412; a table spoon414having a flat handle end shape portion418; a soup spoon420having a pointed handle end shape portion422; a plastic spoon422having a flat, planar handle end shape portion424; and a knife426having a pointed blade tip portion428.

At312the configured processor selects a lowest-cost, best (highest ranked, weighted, rated or scored) tool of the visual model set for use as a substitute tool to execute the specified action upon the work-piece as a function of comparing respective dimension, material, replacement cost and risk of damage values associated with executing the specified action. More particularly, the configured processor compares their respective dimensions, materials, shapes, and body orientations, replacement costs and risk of damage associated with the executed action as a function of knowledge base data associated or indexed to each potential tool of the visual model set within the object data repository301.

Thus, referring to again to the example ofFIG.7, the configured processor determines at312that the ladle406is ranked lowest relative to the other possible tools, due to a low (below threshold) likelihood that its curved handle end shape408will both fit within the tolerances of the dimensions of the screw slot403, and remain engaged therein during a rotation specified by the executed action. The configured processor further ranks the slotted spoon410next-lowest relative to the remainder, other possible tools414,420,422and426as a function of determining a low relative likelihood that its thick flat handle end shape412will fully fit within the screw slot403and remain engaged during said rotation, and due to identifying a material mismatch between its metal body411and plastic handle413material (as determined from image analysis that distinguishes the different portions411and413and matches each to different material image data within the object data repository301) that increases a high risk that the slotted spoon410will break under torque operational forces likely required to execute the specified un-screwing action.

At312the configured processor ranks the knife426and the soup spoon420higher for selection than the ladle406and slotted spoon410in response to determining that the pointed shapes of their respective blade tip428and handle end422conform more closely to the physical dimensions of the work-piece engagement area are therefore more likely to fully fit within the screw slot403and remain engaged during rotation, and thereby that each has a higher likelihood of success in execution. The configured processor further ranks the soup spoon420higher for selection over the knife426in response to determining a higher likelihood or risk that that the blade tip428may be damaged by the operative torque forces relative to the pointed handle end422, and that the knife426has a higher replacement cost for damage relative to the spoon420.

At312the configured processor ranks the flat handle end shape418of the table spoon414and the flat, planar handle end shape424of the plastic spoon422with higher fit score values relative to scores assigned to the other tools406,410,420and426within the visual model set405. The configured processor gives the plastic spoon422a highest fit score at312, in response to determining via image analysis that dimensions of the flat planar handle end shape424conform most closely to the dimensions determined for the slot403. However, the configured processor assigns a lower material strength score to the plastic spoon422, relative to a material strength score that it assigns to the table spoon414, as functioning or comparing their respective material strengths indicated in the object data repository301.

At312the configured processor weights the fit scores and the material strength scores as a function of the torque forces determined for the specified action, and/or the condition of the screw403indicated by the contextual constraints determined at308(for example, level or amount of rust or lubrication determined in the visual data). In the example ofFIG.7, a weighting of a risk-of-loss cost or factor is increased in proportion to the torque forces anticipated or estimated for executing the action, so that the knife426cannot be chosen (ranked highest) to open a tight screw402, even though it may have the best dimension, shape and orientation attributes, due to the higher risk of loss cost. Similarly, the configured processor determines that the torque forces are substantial and likely to result in failure of the plastic material used to form the plastic spoon422, and accordingly weights the material strength score to have a more determinative effect than the fit score in generating the tool selection rankings, resulting in an overall ranking of the table spoon414over the plastic spoon422, and the other tools, for selection for use as a substitute tool. Thus, even though the plastic spoon422handle end424provides the best fit to the slot403, the next-best-fit tool with a better material strength score, the configured processor ranks the table spoon414highest for selection at312.

The terminology used herein is for describing aspects only and is not intended to be limiting of the invention. As used herein, the singular forms “a”, “an” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms “include” and “including” when used in this specification specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof. Certain examples and elements described in the present specification, including in the claims, and as illustrated in the figures, may be distinguished, or otherwise identified from others by unique adjectives (e.g. a “first” element distinguished from another “second” or “third” of a plurality of elements, a “primary” distinguished from a “secondary” one or “another” item, etc.) Such identifying adjectives are generally used to reduce confusion or uncertainty, and are not to be construed to limit the claims to any specific illustrated element or embodiment, or to imply any precedence, ordering or ranking of any claim elements, limitations, or process steps.