Patent Application
20250135657
This disclosure relates generally to robotic systems, and, more particularly, to robotic systems with tool changers.
Sheet metal parts are used in a multitude of applications and across many different industries (e.g., in aerospace, automotive, biomedical, and consumer electronics industries). Sheet metal part forming is the manufacturing process through which sheet metal parts are made. However, sheet metal part forming is very tool intensive, which makes it costly and time consuming to fabricate sheet metal parts. A method for sheet metal part forming is stamping. In stamping, a series of female and male dies that are specific to each design and material are fabricated (tooling). A sheet metal part is formed in a press machine by sandwiching sheet metal between the two dies with force. Stamping requires a large investment in dies and is not accommodating to changes in design and material, making the sheet metal forming process expensive and time-consuming.
Embodiments of the disclosure have other advantages and features which will be more readily apparent from the following detailed description and the appended claims, when taken in conjunction with the examples in the accompanying drawings, in which:
The Figures (FIGS.) and the following description relate to preferred embodiments by way of illustration only. It should be noted that from the following discussion, alternative embodiments of the structures and methods disclosed herein will be readily recognized as viable alternatives that may be employed without departing from the principles of what is claimed.
Reference will now be made in detail to several embodiments, examples of which are illustrated in the accompanying figures. The figures depict embodiments of the disclosed system (or method) for purposes of illustration only. One skilled in the art will readily recognize from the following description that alternative embodiments of the structures and methods illustrated herein may be employed without departing from the principles described herein.
Some embodiments relate to tool holder assemblies, which are in part described below with respect to
In an embodiment a robotic system includes: a robot arm; a tool; a tool holder; and a tool holder assembly coupled to an end of the robot arm and configured to hold the tool holder during operation of the robotic system to form a machined part, the tool holder assembly including: an internal cavity; a drawbar in the internal cavity and extending through a tunnel at a first cavity end of the internal cavity; a spring positioned in the internal cavity to press or pull the drawbar away from the tunnel and toward a second cavity end opposite the first cavity end; a piston in the internal cavity and positioned between the drawbar and the second cavity end; and a port configured to allow fluid to enter the internal cavity between the piston and the second cavity end.
Robotic sheet part forming is a sheet metal part forming technique where a sheet is formed into a desired geometry by a series of incremental deformations applied by a robot (e.g., a machined part). For example, the robot is outfitted with a stiff stylus that delivers deformations to the sheet. The robot may change tools to apply different operations (e.g., trimming and hemming) to the metal part. Multiple robots may be used in the process to provide more accurate control of the process.
Increasing the speed and decreasing the cost to manufacture sheet metal parts is desirable for enhancing product development in all stages of design and manufacturing. In light of this, some embodiments relate to an intelligent machine learning-based system that automates object process parameter generation for real-time control of novel robotic forming of sheet metal, plastics, polymers, and composite parts. Relative to conventional techniques, the disclosed (e.g., fast forming) techniques may enable faster prototyping and may enable rapid customization of mass-produced products. Agile production or prototyping in turn enables development of better-quality products and streamlining production. It may also increase industrial competitiveness in both mature and emerging markets by reducing the time and capital used for developing new components. The benefits may extend further for “lightweighting” strategies employed in various industries (e.g., aerospace and automotive) that want to move towards lighter and higher strength alloys but are slowed down by testing of these alloys. For simplicity, the below descriptions refer to forming parts from sheet metal. However, as indicated above, embodiments described herein may be applicable to forming parts from other materials, such as plastics, polymers, and composites.
Robotic sheet metal part forming overcomes the restrictions of the traditional methods by reducing or removing fabrication of tooling and dies from the production process. Robotic sheet part forming is a sheet metal part forming technique where a sheet is formed into a desired geometry by a series of (e.g. small) incremental deformations applied by a robot. For example, the robot is outfitted with a stiff stylus that delivers deformations to the sheet. Multiple robots may be used in the process to provide more accurate control of the deformations.
The use of two robots (one on each side of the sheet) may provide several advantages. For example, if only a single robot is used, the sheet may globally deform (instead of locally deform). Thus, using two robots may enable localized deformations. A second robot (also referred to as a support robot) may reduce or prevent tearing of the part by providing supporting pressure on the opposite side of the part. The location of the robots (and their end effectors) with respect to each other may be based on the design of the part and the material and thickness of the sheet. These locations may be determined by a model (described further below). An example of the advantages of two robots is illustrated in
A controller may receive and process sensor data from the sensors to determine the proper parameters (e.g., joint angle values for each joint of the robotic arm) and control the robot arms accordingly. In some embodiments, the robots are controlled to pinch or otherwise apply pressure to the sheet metal with a hard implement (e.g., a stylus) or other tool to form the sheet of metal in accordance with a program applied by the controller to result in a desired geometry. For example, the program controls the robot arms to move in a particular sequence and apply the tool to the sheet metal according to particular programmed parameters at each step (e.g., time step) of the sequence to achieve a programmed geometry. The program (via the robotic arms) may cause the different applied tools to bend, pinch, cut, heat, seam, or otherwise form the metal in accordance with the program.
An example part forming process is illustrated in
The controller determines the process parameters to achieve the desired robotic forming operations. Parameters such as the path of the robotic forming tool during the process, its speed, geometry of the forming tool, amount of force, angle and direction of the forming tool, clamping forces of the sheet, etc. may have direct but nonlinear effects on the final geometry. The part forming process may include a set of time steps, where each step describes parameters values for one or more parameters. The part forming process may be iterative. Thus, by executing the system according to the parameter values at each time step, the controller may form the part described in the input design. The parameters values may be determined by the model.
The disclosed robotic system may achieve real-time adaptive control of a part forming process. The method may start with an input design of a part and a (e.g., statistical) model that is generated using a training data set. The training data set may include data from simulation data, and physical process characterization data (such as an in-process inspection or post-build inspection from previously formed parts or geometries). An in-process inspection may include inspecting a part during the forming process. For example, a scanning sensor records the shape of the part as it is being formed. In another example, an eddy current sensor detects defects like cracks. In another example, a force sensor measures the forces applied to the part. A post-build inspection is intended to gather information on a fully formed part. A post-build inspection may include similar inspection techniques as an in-process inspection (e.g., inspecting a part using a scanning sensor or eddy current sensor). However, a post-build inspection may include inspection techniques not performed while the part is being formed (e.g., due to practicality). For example, a fully formed part may be inspected using an x-ray machine.
A state of the part may be described by a mesh. The mesh may be a graph of coupled nodes, where each node represents a physical point of the part metal. Each node may be described by the following variables: X, Y, Z, F1z, F1x, F1y, F2z, F2x, F2y, thickness, dx, dy, and dz. X, Y, and Z represent the location of the node in space. Thickness indicates the sheet thickness at that node. Each node may be coupled to neighboring nodes (e.g., three neighbors). These coupled nodes represent the part in cartesian space. F1z, F1x, and Fly represent the force that one of the robots (e.g., robot 1) is applying at that node, and F2z, F2x, F2y, represent the force another robot (e.g., robot 2) is applying at that node. dx, dy, and dz represent the size of movements capable at a node if the robots pull back from the part at this time (e.g., they capture the elastic strain of the material).
The model can be used to determine the process parameters (e.g., in real time or offline). This method automates the generation of parameters for the robotic forming process (further described in the next paragraph). Due to the optimization process, the generated parameters may not be conceivable by engineers.
After the model is determined (e.g., by a training process), optimization techniques may be used to determine parameters to apply at each (e.g., time) step of the part forming process to create the intended part geometry. For example, for a given time step, the model is applied to various input parameter values according to an optimization technique to determine which parameter values will result in a desired geometry (or a geometry close to the desired geometry). Multiple optimization techniques may be used. Example optimization techniques include gradient descent, Adam optimization, and Bayesian optimization. An optimization technique may be chosen based on the complexity of the desired geometry. The optimization may be done both in the long and short horizons (e.g., time scales). The long horizon optimization may be done offline (before the part forming process begins) to determine steps of the process (e.g., step by step instructions for the robot to achieve the desired geometry). For example, a long horizon optimization may determine how to form a material sheet into a fully formed part. In some embodiments, long horizon optimizations determine a set of intermediate geometries that occur during a part forming process (e.g., intermediate geometries between the sheet and the fully formed part (e.g., for each time step or layer)). However, errors or inaccuracies may accrue over time (e.g., for processes with lengthy build times or processes with a large number of time steps). For example, the part may deform differently than the model predicted. To remedy this issue, short horizon optimizations may be performed during the forming process (online) to reduce or correct errors that may accrue. For example, the model is queried by a (e.g., online) controller that can modify (e.g., correct) steps determined during the long horizon optimization based on the current state of the sheet. For example, for a given time step, instead of assuming the part has a geometry predicted by the long horizon optimization, sensor data may be used to determine the actual geometry of the part. The model may then be queried to determine a new set of parameter values for the time step (or modify the long horizon parameters associated with the time step). For example, the model may be queried to determine which parameter values will form the actual geometry into the predicted geometry (or another intermediate geometry from the long horizon optimization).
While long horizon optimizations may be used to determine an entire part forming process or significant portions of the process, determinations made by short horizon optimizations may be limited to small portions of the part forming process. For example, a short horizon optimization determines a number of interactions (e.g., less than ten) between the end effector and the part. In another example, a short horizon optimization determines interactions between the end effector and the part that will occur during a time window (e.g., less than ten seconds). In another example, a short horizon optimization determines parameter values for a set of time steps (e.g., less than ten time steps). In another example, a short horizon optimization determines how to form a part in a first geometry into a second geometry, where the first and second geometries are intermediate geometries determined by a long horizon optimization. In another example, a short horizon optimization is used to determine how to form a part so that it is a threshold percent closer to a final geometry (e.g., less than ten percent).
In some embodiments, a long horizon optimization is used without short horizon optimizations (e.g., the model has a threshold accuracy or the part forming process has a short build time or a small number of time steps). In some embodiments, short horizon optimizations are used without a long horizon optimization.
Referring back to the model 200, the model may be trained using the data from a simulation module. Additionally, or alternatively, the model 200 may be trained using data (e.g., sensor data) from a physical process that forms a part.
In some embodiments, multiple models are trained. For example, models may be trained using different machine learning techniques. Additionally, or alternatively, models may be trained for specific materials (e.g., steel vs. aluminum), geometries (simple vs. complex), or sheet thickness (e.g., 1 mm vs. 2 mm). Among other advantages, models trained for specific specifications may be more accurate than a general model.
The model 200 may also be applied by the controller 255 of the robotic system 260 in the online process. More specifically, the model 200 may determine predictions about the resulting change in geometry from each parameter change at each point in time in the part forming process. In the online process, the controller uses sensors installed on the robotic forming system to obtain sensor data 265 to determine a current geometry of the part. The current geometry may then be input to the model 200. The model predicts the outcome (e.g., a resulting change in geometry) of changes in those process parameters. By iterating over different possible parameters and their outcome predicted by the model, the controller identifies and chooses the (e.g., best) parameter 250 that produces the most desirable outcome to control the robotic forming system through a forming process that achieves the desired geometry. The controller uses the best parameters and may repeats this optimization cycle (e.g., in every step of the process) to improve the outcome.
In addition to the model 200 described above with respect to
A more complex model is the one that breaks the forming process into layers and tries to predict the effect of various parameter values at each layer. In this context, “layer” refers to a section of a part. For example, a first layer refers to the section that extends one inch away from the original sheet and a second layer refers to the section that extends from the first inch to the second inch. An example of a layer based model is further described below.
Model 1415 may be developed as a sequence model which means it may be any of the sequence architectures (e.g., RNN, LSTM, Transformers). This model has more advantages than model 1400 since it is agnostic to general changes to the policy for forming robots. For example, model 1415 may be used to model inset adding or doing ADSIF or grouped DSIF. That being said, in some embodiments, model 1415 does not capture physical phenomena that may occur during each layer or group of layers.
Referring back to
Referring back to
By varying different input process parameters such as the forming path, its speed, and the geometry being formed, the simulation module 225 can generate a (e.g., large) data set indicating how a specific metal is deformed with this process (e.g., how metal deforms in response to certain input parameters). The simulation data is used to train a model (e.g., by a training module). The model may be trained using one or more different machine learning techniques and constructs, such as Neural Networks, Random Forests, Decision trees, or regressions. in some embodiments, the training techniques are supervised learning techniques.
In some embodiments, the simulation data is used to train an initial model. The initial model may then be refined or retrained using data from physical part forming processes to increase the accuracy of the model.
In the examples described above, the model is generally described in the context of forming operations. However, the model (or another model) may be trained to predict other part operations, such as trimming or hemming.
The model created using simulation data may be further trained from data derived from an actual physical process that uses a robot arm and an actual sheet. The physical system is equipped with one or more different types of sensors. Example sensors include: (1) encoders in the robot joints that provide positional information as determined by the position of the joints, (2) optical trackers (e.g., a camera) that track the location of robot in (e.g., 3D) space, (3) surface scanners to generate as-built geometry of the part before, during, and after the forming process (surface scanners may have a point accuracy of 0.5 mm), (4) load sensors that determine the force the forming end effectors apply on the sheet, (5) ultrasonic sensors (e.g., electromagnetic acoustic transducer or EMAT) for real-time monitoring of material thickness, and (6) eddy current sensors (e.g., pulsed eddy current) for real-time monitoring of the metallurgical state of metallic sheet. In some embodiments, if the surface scanner is attached to the robot arm, surface scanner data may be stitched together based on the encoder data to determine the geometry of a part (the location of the scanner depends on the position of the arm).
The encoders may be attached to each joint on the robot to track its actual movement, the optical trackers may be mounted around the manufacturing cell. This allows the optical trackers to capture images that include tracking targets installed on the robotic arms and the frame holding the sheet in place. The load sensor and scanner may be attached to the end-of-arm tooling to track forming forces and deformation of the sheet during the process.
Example optical trackers are illustrated in
In some embodiments, the robot arm is outfitted with a scanner and a load sensor (e.g., force/torque sensor) as illustrated in
With the sensors described above, accurate data can be captured to characterize steps of a part forming process.
Referring back to
Once a process model 200 is generated using the above-described training process, the model may be applied in the control process of the robotic forming in two ways. The model may as an input takes a specification for a sheet, such as its material properties (e.g., stress-strain curve) and failure criteria. It may also receive a specification for forming paths (which may initially be determined offline) and the type and size of the tool. The model can be either queried online for optimized process parameters for each time step of the process in real-time, or it can be used in the design of experiments offline to determine optimal policy for forming the part. The policy here refers to general pathing strategies in forming a part.
Two categories of systems discussed below may increase the speed of sheet metal part fabrication using robots. The first system and design (“Forming With Rollers”) increases the speed of the forming process itself, while the second (“Integration of Downstream Processes”) addresses downstream processes from part forming to decrease total fabrication time.
To increase the speed of the part forming process, an end-effector tool may be configured to interact with the sheet metal with reduced (e.g., low) friction forces. Reducing friction allows for reduction in vibrations in the sheet and hence allows increased speed of forming without negative impact on the geometrical accuracy of the formed part. It may also result in better surface quality (e.g., reduced tearing and galling) compared to tools not configured to reduce friction (e.g., static forming tools).
An example tool configured to reduce friction is a stylus made of a material (or coated with a material) configured to reduce friction. Thus, if the stylus is dragged across the surface of a part, the reduced friction may reduce or eliminate surface degradations and increase the path speed.
Other tools configured to reduce friction may include roller tools. Roller tools may result in lower friction forces than a stylus. Different rollers with different radii and shape can be used to accommodate for different features in the part design.
In some embodiments, the roller can only roller about a single rotational axis (e.g., as in
In some embodiments, a roller tool includes a roller that can rotate about multiple rotational axes. An example, of this is illustrated in
The disclosed roller design installed on a robotic setup allows for robotic part forming with reduceds friction, hence reduced forces which then allows for better surface quality of the formed part and increased speed of the forming process.
Sheet metal part forming may be one of many manufacturing steps performed to produce a final sheet metal part. For example, a sheet metal part also goes through trimming, hole making, hemming, or other processing steps after the part forming process. Traditional methods involve transferring a sheet metal part from one specialized manufacturing station to another, performing each manufacturing step in each corresponding station to produce the delivering the final part. This results in increased manufacturing time due to the time for physically moving the part from one station to another.
Each of the downstream processes generally has its own specific tooling. For example, for trimming a part, it is desirable to use a geometry specific frame that can hold the geometry of the part while a trimming operation is performed.
In some embodiments, the robotic system allows for performing two or more (e.g., all) downstream manufacturing steps in the same station using the same robotic setup, thus avoiding moving of the part and decreasing the total fabrication time. Each downstream process may use a different tool. For example, when performing trimming (e.g., hole making), the robot arm may attach different tools such as a spindle, laser, or a plasma torch. The robotic arm can be controlled to automatically change the tool through software instructions of the program executed by the controller (e.g., controller 255). For example, the controller can control the robot arm at varying times throughout the process to perform a programmed operation on the sheet metal with a particular tool, to control an actuator to release a tool from the tool holder (e.g., into a tool rack), and to cause the robot arm to attach a new tool from the tool holder (e.g., from the tool rack) for performing a subsequent operation.
In some embodiments, the steps that enable automatic integration of downstream processes in the same station may include the following. (1) the robot goes to a tool rack and picks up a forming tool (e.g., a stylus) using predefined software instructions sent to the robot. (2) the robot forms a part from a flat sheet of metal through software defined path and parameters. (3) After the part is formed, the robot moves back to the tool rack, disengages (e.g., drops) the forming tool, and picks up a trimming tool. This step may also be automated with software instructions. (4) The robot performs a trimming operation on the part with the trimming tool. If further downstream processes, such as hemming (e.g., bending), are used to finish the part, the system may continue from step 3 until no more processes are left to perform. If a station includes multiple robots, the robots may work in conjunction using the same or different tools to achieve a desired process (e.g., a forming or trimming process).
If a manufacturing area includes multiple cells (e.g., each including two robot arms), instead of each cell changing tools to perform different operations, each cell may be assigned to a specific operation. In these embodiments, a part may be moved from one cell to another after each operation on the part is complete.
Thus, the stand design and software-controlled tool changer for controlling the robotic arms allows for automated downstream operations from forming of the sheet metal parts such as trimming, bending, and hemming without removing the part from the fixture and requiring geometry specific fixture.
Tool 1610 is configured to interface with an object (e.g., a piece of sheet metal) to perform part forming operations. Tool holder 1620 is a mechanical device designed to securely hold and support tool 1610. Tool holder 1620 includes an interface configured to interlock with tool holder assembly 1650. In some embodiments, tool holder 1620 has a CAT40 interface or a BT40 interface.
Tool holder assembly 1650 is a mechanical device configured to hold tool holder 1620 during operation of the robotic system. Tool holder assembly 1650 is coupled to an end of robot arm 1670. Tool holder assembly 1650 includes internal cavity 1651 with first cavity end 1671 and second cavity end 1673. A part of drawbar 1652, the spring 1654, and the piston 1655 are located in cavity 1651. Cavity 1651 is cylindrical in the example of
Tool holder assembly 1650 also includes internal tunnel 1653. Tunnel 1653 includes rounded sides although other shaped sides are possible. Tunnel 1653 extends from an end of tool holder 1620 to an end of internal cavity 1651. Tunnel 1653 includes first tunnel portion 1679 at the left side of tool holder assembly 1650 (in the perspective of
Drawbar 1652 is a mechanical component that may interlock with an end of tool holder 1620 (e.g., to securely hold the tool holder 1620). Drawbar 1652 includes a first end that rests in tunnel 1653 and a second end in cavity 1651. Drawbar 1652 is designed to move along tunnel 1653 and within internal cavity 1651 (e.g., horizontally in
Spring 1654 is positioned in the internal cavity 1651 to press or pull the drawbar 1652 away from the tunnel 1653 and toward a second cavity end 1673 (which is opposite first cavity end 1671). In the example of
Piston 1655 is positioned in internal cavity 1651 between the drawbar 1652 and the second cavity end 1673. Due to spring 1654 applying a force to move drawbar 1652 toward second cavity end 1673, spring 1654 may press drawbar 1652 against piston 1655. In some embodiments, piston 1655 and drawbar 1652 are a singular component. Piston 1655 can move within internal cavity 1651 between first cavity end 1671 and second cavity end 1673. Piston 1655 is sized to form a seal within internal cavity 1651 that divides internal cavity 1651 into two sub-cavities (i.e., first sub-cavity 1677 between first cavity end 1671 and piston 1655 and second sub-cavity 1675 between second cavity end 1673 and piston 1655). More specifically, side edges of piston 1655 may form a seal with one or more side walls of 1651 cavity (depending on the shape of internal cavity 1651). Thus, if pressure in one of the sub-cavities increases, the increased pressure may move piston 1655 in internal cavity 1651 such that the volume of one sub-cavity increases and the other sub-cavity decreases. Note that the seal does not need to be a perfect fluid-tight seal. The seal may simply be strong enough to move piston 1655 when pressure in one of the sub-cavities changes (e.g., subject to the force from 1654).
Tool holder assembly 1650 includes a port (not illustrated) to internal cavity 1651. Port can allow fluid (e.g., a liquid or gas (e.g., air)) or to enter or exit internal cavity 1651. Port is positioned to allow fluid to enter or exit the internal cavity between piston 1655 and the second cavity end 1673 (i.e., second sub-cavity 1675).
As previously mentioned, tool holder assembly 1650 enables tool holder 1620 to be locked into or released from tool holder assembly 1650 based on the position of drawbar 1652. If drawbar 1652 translates into tunnel 1653 past a threshold (referred to as drawbar 1652 being at an “unlocked position”), interlocking mechanisms between drawbar 1652 and tool holder 1620 enable tool holder 1620 to be released from tool holder assembly 1650. However, if drawbar 1652 translates toward second cavity end 1673 past a threshold (referred to as drawbar 1652 being at a “locked position”), interlocking mechanisms between drawbar 1652 and tool holder 1620 may prevent tool holder 1620 from being released from tool holder assembly 1650 (assuming drawbar 1652 remains in the locked position).
To enable this, in the example of
When pressure in second sub-cavity 1675 is low (e.g., below a first threshold based on the stiffness of spring 1654), spring 1654 moves drawbar 1652 into the locked position (if drawbar 1652 was in the unlocked position) and applies a force that keeps drawbar 1652 in the locked position (e.g., during part forming operations). However, when pressure in second sub-cavity 1675 is increased (e.g., by fluid being pumped into second sub-cavity 1675 via the port), the increased pressure applies an increasing force against spring 1654. If the pressure becomes high enough to overcome spring 1654 (e.g., above a second threshold based on the stiffness of spring 1654), the pressure moves piston 1655 along internal cavity 1651 toward first cavity end 1671 (and thus pushes drawbar 1652 further into tunnel 1653), which may result in drawbar 1652 moving to the unlocked position. Note that fluid through the port may be controlled by a fluid power system (e.g., a hydraulic or pneumatic system) of robotic system 1600.
Many alternative tool holder assemblies are possible. In a first example, tool holder assembly 1650 may include a second port that allows fluid (e.g., liquid or gas) to enter or exit first sub-cavity 1677. Thus, the position of drawbar 1652 and piston 1655 may be controlled by controlling the fluid pressures in first sub-cavity 1677 and second sub-cavity 1675 (e.g., drawbar 1652 and 1655 may be coupled together). In some of these embodiments, spring 1654 may be removed. In a second example alternative tool holder assembly, spring 1654 may be moved to second sub-cavity 1675 and arranged to push piston 1655 toward first cavity end 1671 and the port may be moved to allow fluid to enter or exit first sub-cavity 1677 (e.g., drawbar 1652 and 1655 may be coupled together). In a third example, second sub-cavity 1675 may include an actuator configured to push piston 1655 toward first cavity end 1671 (and thus push drawbar 1652 further into tunnel 1653). The actuator may be in addition to or alternative to controlling fluid pressure in second sub-cavity 1675.
In some embodiments, tool holder 1620 and tool holder assembly 1650 include channels (e.g., 1665 and 1669). Channels may be used to carry fluid to or from tool 1610 (e.g., during part forming). For example, channel 1665 may be a vacuum passage that helps retain the ball at the end of tool 1610. In another example, channel 1669 may carry coolant to reduce or prevent tool 1610 from overheating during part forming operations.
In some embodiments, tool holder assembly 1650 includes tool holder reader 1658, such as an RFID (radio-frequency identification) sensor. Thus, a control system of robotic system 1600 may use signals from tool holder assembly 1650 to confirm whether a tool holder is installed in tool holder assembly 1650 and/or confirm which tool holder is installed in tool holder assembly 1650 (since many different tools many be used and performing operations with a wrong tool holder can be problematic).
Additional examples of tools, tool holders, and tool holder assemblies are described below. Although references are made to
Some embodiments relate to a robotic system (e.g., 1600), for example configured to form a (e.g., machined) part, the robotic system including: a robot arm (e.g., 120, 1000, 1670); a tool (e.g., 125, 505, 705, 805, 1010, 11001610); a tool holder (e.g., part of 130, 1620); and a tool holder assembly (e.g., part of 130, 1650). The tool holder assembly is coupled to an end of the robot arm and configured to hold the tool holder during operation of the robotic system to form the part, the tool holder assembly including: an internal cavity (e.g., 1651); a drawbar (e.g., 1652) in the internal cavity and extending through a tunnel (e.g., 1653) at a first cavity end (e.g., 1671) of the internal cavity; a spring (e.g., 1654) positioned in the internal cavity to press or pull the drawbar away from the tunnel and toward a second cavity end (e.g., 1673) opposite the first cavity end; a piston (e.g., 1655) in the internal cavity and positioned between the drawbar and the second cavity end; and a port configured to allow fluid to enter the internal cavity between the piston and the second cavity end (e.g., in 1675).
In some aspects, fluid pressure in the internal cavity between the piston and the second cavity end higher than a threshold pressure causes the piston to move toward the first cavity end (e.g., see the movement of the piston and drawbar in the transition from
In some aspects, fluid pressure in the internal cavity between the piston and the second cavity end higher than a threshold pressure causes the piston to press the drawbar into the tunnel at the first cavity end. In some aspects, translation of the drawbar into the tunnel past a threshold releases the tool holder from the tool holder assembly (e.g., translation such that coupling bearings 1657 are in middle tunnel portion 1681). In some aspects, the robotic system further includes a fluid power system (e.g., a hydraulic system and/or pneumatic system) configured to pump fluid through the port and into the internal cavity (e.g., a hose in
In some aspects, a first end of the drawbar is in the tunnel and a second end is in the internal cavity; and at least a portion of the spring is positioned between the first cavity end and the second end of the drawbar (e.g., see
In some aspects, an end of tunnel is configured to receive the tool holder (e.g., first tunnel portion 1679). In some aspects, the tool holder is configured to be held in the tunnel by the drawbar during operation of the robotic system. In some aspects, the tool holder includes a retention knob (e.g., 1660) configured to interlock with an end of the drawbar in the tunnel.
In some aspects, the robotic system (e.g., the robot arm) further includes: an actuator system configured to control motion of the robot arm through space during operation of the robotic system to form the part. In some aspects, the tool is configured to press into material of the part to form the part.
In some aspects, the tool holder assembly and/or tool holder include a set of channels (e.g., 1665, 1669) configured to carry fluid to or away from the tool. In some aspects, the tool holder further includes a tool holder reader configured to scan the tool holder (e.g., 1658). In some aspects, the tool holder has a CAT40 interface (e.g., including 1660). In some aspects, the tool holder assembly is configured to receive a tool holder with a CAT40 interface (e.g., first tunnel portion 1679 includes a taper (e.g., 1659) that is a CAT40 taper configured to interface with a CAT40 interface.
In some aspects, the tool, the tool holder, and the tool holder fit within a cone shaped design envelop, with the tool being near or at the tip of the cone envelope. Among other advantages, the cone shaped design envelop increases the available angles (in other words, a part forming operation can be performed at a larger angle relative to the surface without the tool holder or tool holder assembly contacting the surface of the object or otherwise hindering the part forming operation). Generally, the smaller the radius of the cone and the larger the height of the cone, the larger the part forming angle can be.
Other aspects include components, devices, systems, improvements, methods, processes, applications, computer readable mediums, and other technologies related to any of the above.
In some embodiments, the controller (e.g., controller 255 or controller 1120) is a machine able to read instructions from a machine-readable medium and execute them in a set of one or more processors.
The machine may be a server computer, a client computer, a personal computer (PC), a tablet PC, a smartphone, an internet of things (IoT) appliance, a network router, or any machine capable of executing instructions 1524 (sequential or otherwise) that specify actions to be taken by that machine. Further, while only a single machine is illustrated, the term “machine” shall also be taken to include any collection of machines that individually or jointly execute instructions 1524 to perform any one or more of the methodologies discussed herein.
The example computer system 1500 includes a processing system comprising a set of one or more processing units 1502 (“processor set 1502”). The processor set 1502 is, for example, one or more central processing units (CPUs), one or more graphics processing units (GPUs), one or more tensor processing units, one or more neural network processing units, one or more digital signal processors (DSPs), one or more state machines, one or more application specific integrated circuits (ASICs), one or more radio-frequency integrated circuits (RFICs), or any combination of these. If the processor set 1502 include multiple processors, the processors may operate individually or collectively. The processor set 1502 also may be a controller. The controller may include a non-transitory computer readable storage medium that may store program code to operate (or control) the robots, e.g.,400A, 400B, and/or other automated components described herein.
For convenience, the processor 1502 is referred to as a single entity but it should be understood that the corresponding functionality may be distributed among multiple processors using various ways, including using multi-core processors, assigning certain operations to specialized processors (e.g., graphics processing units), and dividing operations across a distributed computing environment. Any reference to a processor 1502 should be construed to include such architectures.
The computer system 1500 also includes a main memory 1504. The computer system may include a storage unit 1516. The processor 1502, memory 1504 and the storage unit 1516 communicate via a bus 1508.
In addition, the computer system 1500 can include a static memory 1506, a display driver 1510 (e.g., to drive a plasma display panel (PDP), a liquid crystal display (LCD), or a projector). The computer system 1500 may also include alphanumeric input device 1512 (e.g., a keyboard), a cursor control device 1514 (e.g., a mouse, a trackball, a joystick, a motion sensor, or other pointing instrument), a signal generation device 1518 (e.g., a speaker), and a network interface device 1520, which also are configured to communicate via the bus 1508.
The storage unit 1516 includes a machine-readable medium 1522 on which is stored instructions 1524 (e.g., software) embodying any one or more of the methodologies or functions described herein. The instructions 1524 may also reside, completely or at least partially, within the main memory 1504 or within the processor 1502 (e.g., within a processor's cache memory) during execution thereof by the computer system 1500, the main memory 1504 and the processor 1502 also constituting machine-readable media. The instructions 1524 may be transmitted or received over a network 1526 via the network interface device 1520.
While machine-readable medium 1522 is shown in an example embodiment to be a single medium, the term “machine-readable medium” should be taken to include a single medium or multiple media (e.g., a centralized or distributed database, or associated caches and servers) able to store the instructions 1524. The term “machine-readable medium” shall also be taken to include any medium that is capable of storing instructions 1524 for execution by the machine and that cause the machine to perform any one or more of the methodologies disclosed herein. The term “machine-readable medium” includes, but not be limited to, data repositories in the form of solid-state memories, optical media, and magnetic media.
While machine-readable medium 722 (also referred to as a computer-readable storage medium) is shown in an embodiment to be a single medium, the term “machine-readable medium” should be taken to include a single medium or multiple media (e.g., a centralized or distributed database, or associated caches and servers) able to store the instructions 724. The term “machine-readable medium” shall also be taken to include any medium that is capable of storing instructions 724 for execution by the machine and that cause the machine to perform any one or more of the methodologies disclosed herein. The term “machine-readable medium” shall also be taken to be a non-transitory machine-readable medium. The term “machine-readable medium” includes, but not be limited to, data repositories in the form of solid-state memories, optical media, and magnetic media.
Embodiments of the system and/or method can include every combination and permutation of the various system components and the various method processes.
Some portions of above description describe the embodiments in terms of algorithmic processes or operations. These algorithmic descriptions and representations are commonly used by those skilled in the data processing arts to convey the substance of their work effectively to others skilled in the art. These operations, while described functionally, computationally, or logically, are understood to be implemented by computer programs comprising instructions for execution by a processor or equivalent electrical circuits, microcode, or the like. Furthermore, it has also proven convenient at times, to refer to these arrangements of functional operations as modules, without loss of generality. In some cases, a module can be implemented in hardware, firmware, or software.
As used herein, any reference to “one embodiment” or “an embodiment” means that a particular element, feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment. The appearances of the phrase “in one embodiment” in various places in the specification are not necessarily all referring to the same embodiment.
Some embodiments may be described using the expression “coupled” and “connected” along with their derivatives. It should be understood that these terms are not intended as synonyms for each other. For example, some embodiments may be described using the term “connected” to indicate that two or more elements are in direct physical or electrical contact with each other. In another example, some embodiments may be described using the term “coupled” to indicate that two or more elements are in direct physical or electrical contact. The term “coupled,” however, may also mean that two or more elements are not in direct contact with each other, but yet still co-operate or interact with each other. The embodiments are not limited in this context.
As used herein, the terms “comprises,” “comprising,” “includes,” “including,” “has,” “having” or any other variation thereof, are intended to cover a non-exclusive inclusion. For example, a process, method, article, or apparatus that comprises a list of elements is not necessarily limited to only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Further, unless expressly stated to the contrary, “or” refers to an inclusive or and not to an exclusive or. For example, a condition A or B is satisfied by any one of the following: A is true (or present) and B is false (or not present), A is false (or not present) and B is true (or present), and both A and B are true (or present).
In addition, use of the “a” or “an” are employed to describe elements and components of the embodiments. This is done merely for convenience and to give a general sense of the disclosure. This description should be read to include one or at least one and the singular also includes the plural unless it is obvious that it is meant otherwise. Where values are described as “approximate” or “substantially” (or their derivatives), such values should be construed as accurate +/−10% unless another meaning is apparent from the context. From example, “approximately ten” should be understood to mean “in a range from nine to eleven.”
Upon reading this disclosure, those of skill in the art will appreciate still additional alternative structural and functional designs. Thus, while particular embodiments and applications have been illustrated and described, it is to be understood that the described subject matter is not limited to the precise construction and components disclosed herein and that various modifications, changes and variations which will be apparent to those skilled in the art may be made in the arrangement, operation and details of the method and apparatus disclosed. The scope of protection should be limited only by any claims that issue.
This application claims the benefit of, and priority to, U.S. Provisional Patent Application Ser. No. 63/594,922, “Sheet Part Forming Components and Methods,” filed Oct. 31, 2023, which is incorporated herein by reference in its entirety.
| Number | Date | Country | |
|---|---|---|---|
| 63594922 | Oct 2023 | US |
