In some examples, a method for determining feasible portions of a seam includes receiving a representation of a part including the seam. The method also includes discretizing a representation of the seam into a plurality of waypoints. The method also includes evaluating each waypoint for feasibility of welding. The method further includes modifying at least one constraint on at least a first waypoint of the plurality of waypoints and generating a weld path through the plurality of waypoints.
G06F 119/02 - Reliability analysis or reliability optimisationFailure analysis, e.g. worst case scenario performance, failure mode and effects analysis [FMEA]
2.
TECHNIQUES FOR SEAM LOCALIZATION AND GAP MEASUREMENT
This disclosure provides systems, methods, and apparatuses, including computer programs encoded on computer storage media, which provide for welding techniques for manufacturing robots, such as seam localization, gap measurement, or both. For example, the welding techniques may include, during illumination of one or more objects by a light source, controlling a camera to capture images of the one or more objects along at least a portion of a length of a seam formed by the one or more objects. The techniques further include differentiating, in the images, the seam from the one or more objects. In a first aspect, the techniques also include triangulating the differentiated seam to identify a position of the seam relative to a reference point. In a second aspect, the techniques also include determining, based on the differentiated seam, gap information along a portion of the seam. Other aspects and features are also claimed and described.
This disclosure provides systems, methods, and apparatuses, including computer programs encoded on computer storage media, which provide for welding techniques for manufacturing robots, such as seam localization, gap measurement, or both. For example, the welding techniques may include, during illumination of one or more objects by a light source, controlling a camera to capture images of the one or more objects along at least a portion of a length of a seam formed by the one or more objects. The techniques further include differentiating, in the images, the seam from the one or more objects. In a first aspect, the techniques also include triangulating the differentiated seam to identify a position of the seam relative to a reference point. In a second aspect, the techniques also include determining, based on the differentiated seam, gap information along a portion of the seam. Other aspects and features are also claimed and described.
B23K 31/00 - Processes relevant to this subclass, specially adapted for particular articles or purposes, but not covered by any single one of main groups
A robotic welding system includes at least one first robot arm positioned in a welding cell, a second robot arm coupled to a welding tool and also located within the welding cell. The system includes a pose adjustment station and a welding station inside the cell. A controller is connected to both robot arms and includes a processor and memory storing instructions. When executed by the processor, the instructions cause the system to perform operations including grasping objects with the first robot arm in various initial poses from the highly unstructured storage environment, transferring the objects to the relatively structured pose adjustment station for re-grasping in a common adjusted grasp pose that facilitates downstream pre-welding operations. The system then re-grasps the objects in the adjusted grasp pose(s) and performs pre-welding and welding operations. The introduction of the pose adjustment station significantly reduces overall weld cycle time.
B23K 37/04 - Auxiliary devices or processes, not specially adapted for a procedure covered by only one of the other main groups of this subclass for holding or positioning work
This disclosure provides systems, methods, and apparatuses, including computer programs encoded on computer storage media, that provide for techniques for manufacturing robots, such as path clearance planning techniques for manufacturing robots. For example, the techniques may generating, based on an end effectuator (EE), a joint, or a combination thereof of a robot arm of the robot for the robot arm in a first state, a plurality of candidate states. The techniques also include, based on the plurality of candidate states, determining a set of verified states. Each verified state may be included in the set of verified states satisfies a clearance threshold value with respect to an object. The techniques further include determining, based on a cost function, a trajectory between the first state and a second state, the second state included in the set of verified states. Other aspects and features are also claimed and described.
This disclosure provides systems, methods, and apparatuses, including computer programs encoded on computer storage media, that provide for techniques for manufacturing robots, such as path clearance planning techniques for manufacturing robots. For example, the techniques may generating, based on an end effectuator (EE), a joint, or a combination thereof of a robot arm of the robot for the robot arm in a first state, a plurality of candidate states. The techniques also include, based on the plurality of candidate states, determining a set of verified states. Each verified state may be included in the set of verified states satisfies a clearance threshold value with respect to an object. The techniques further include determining, based on a cost function, a trajectory between the first state and a second state, the second state included in the set of verified states. Other aspects and features are also claimed and described.
Systems and methods for real time feedback and for updating welding instructions for a welding robot in real time is described herein. The data of a workspace that includes a part to be welded can be received via at least one sensor. This data can be transformed into a point cloud data representing a three-dimensional surface of the part. A desired state indicative of a desired position of at least a portion of the welding robot with respect to the part can be identified. An estimated state indicative of an estimated position of at least the portion of the welding robot with respect to the part can be compared to the desired state. The welding instructions can be updated based on the comparison.
B23K 9/095 - Monitoring or automatic control of welding parameters
B23K 9/127 - Means for tracking lines during arc welding or cutting
B23K 26/03 - Observing, e.g. monitoring, the workpiece
G01B 11/25 - Measuring arrangements characterised by the use of optical techniques for measuring contours or curvatures by projecting a pattern, e.g. moiré fringes, on the object
G05D 3/20 - Control of position or direction using feedback using a digital comparing device
Disclosed are systems, methods, and apparatuses, including computer programs encoded on computer storage media, for operation of a robotic welding system. In one aspect, a method for calibrating a tool center point (TCP) of the robotic welding system includes identifying, based on multiple images, a location of a tip of a protrusion extending from the weldhead. Each image of the multiple images including at least a portion of the protrusion extending from a tip of the weldhead. The tip of the weldhead is associated with a first frame of reference. The method also includes determining, based on the location of the terminal end of the protrusion, a second frame of reference that is offset from the first frame of reference. The method further includes generating one or more TCP calibration values based on the second frame of reference. Other aspects and features are also claimed and described.
In some examples, an autonomous robotic welding system comprises a workspace including a part having a seam, a sensor configured to capture multiple images within the workspace, a robot configured to lay weld along the seam, and a controller. The controller is configured to identify the seam on the part in the workspace based on the multiple images, plan a path for the robot to follow when welding the seam, the path including multiple different configurations of the robot, and instruct the robot to weld the seam according to the planned path.
B23K 37/02 - Carriages for supporting the welding or cutting element
B23K 37/04 - Auxiliary devices or processes, not specially adapted for a procedure covered by only one of the other main groups of this subclass for holding or positioning work
B25J 11/00 - Manipulators not otherwise provided for
B25J 13/08 - Controls for manipulators by means of sensing devices, e.g. viewing or touching devices
G06T 7/70 - Determining position or orientation of objects or cameras
G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
Disclosed are systems, methods, and apparatuses, including computer programs encoded on computer storage media, for operation of an assembly robotic system. In one aspect, the assembly robotic system performs at least one of a first or second scan operation. In the first scan operation, one or more scan poses is selected from among a plurality of generated candidate poses. For each scan pose of the one or more scan poses, the controller initiates a scan operation associated with a region identified to include a seam associated with a feature of the object. As part of the second scan operation, for each candidate scan pose, a scan operation is simulated. Based on the generated simulated scan data, multiple scan poses are selected and a scan trajectory is generated for a scan operation. Other aspects and features are also claimed and described.
Disclosed are systems, methods, and apparatuses, including computer programs encoded on computer storage media, for operation of an assembly robotic system. In one aspect, the assembly robotic system performs at least one of a first or second scan operation. In the first scan operation, one or more scan poses is selected from among a plurality of generated candidate poses. For each scan pose of the one or more scan poses, the controller initiates a scan operation associated with a region identified to include a seam associated with a feature of the object. As part of the second scan operation, for each candidate scan pose, a scan operation is simulated. Based on the generated simulated scan data, multiple scan poses are selected and a scan trajectory is generated for a scan operation. Other aspects and features are also claimed and described.
B23K 37/02 - Carriages for supporting the welding or cutting element
G05B 19/4155 - Numerical control [NC], i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form characterised by programme execution, i.e. part programme or machine function execution, e.g. selection of a programme
13.
SCAN PLANNING AND SCAN OPERATIONS FOR WELDING AN OBJECT
Disclosed are systems, methods, and apparatuses, including computer programs encoded on computer storage media, for operation of an assembly robotic system. In one aspect, the assembly robotic system performs at least one of a first or second scan operation. In the first scan operation, one or more scan poses is selected from among a plurality of generated candidate poses. For each scan pose of the one or more scan poses, the controller initiates a scan operation associated with a region identified to include a seam associated with a feature of the object. As part of the second scan operation, for each candidate scan pose, a scan operation is simulated. Based on the generated simulated scan data, multiple scan poses are selected and a scan trajectory is generated for a scan operation. Other aspects and features are also claimed and described.
Disclosed are systems, methods, and apparatuses, including computer programs encoded on computer storage media, for operation of an assembly robotic system. In one aspect, the assembly robotic system performs at least one of a first or second scan operation. In the first scan operation, one or more scan poses is selected from among a plurality of generated candidate poses. For each scan pose of the one or more scan poses, the controller initiates a scan operation associated with a region identified to include a seam associated with a feature of the object. As part of the second scan operation, for each candidate scan pose, a scan operation is simulated. Based on the generated simulated scan data, multiple scan poses are selected and a scan trajectory is generated for a scan operation. Other aspects and features are also claimed and described.
Some embodiments described herein relate to optical systems and methods for determining the shape and/or size of objects that include projecting a pattern of light onto the object. The pattern of light can be configured such that first-order reflections can be distinguished from second- and/or higher-order reflections, which can be rejected. Thus, even in instances in which the pattern of light is reflected onto the object multiple times, the original, or first-order, reflection can be detected, distinguished, and/or used for laser triangulation. In some embodiments, a pattern of light that does not have reflection and/or rotational symmetry is projected onto the object, such that second-order and/or higher-order reflections can be distinguished from the first-order reflection.
G01B 11/25 - Measuring arrangements characterised by the use of optical techniques for measuring contours or curvatures by projecting a pattern, e.g. moiré fringes, on the object
In some examples, an autonomous robotic welding system comprises a workspace including a part having a seam, a sensor configured to capture multiple images within the workspace, a robot configured to lay weld along the seam, and a controller. The controller is configured to identify the seam on the part in the workspace based on the multiple images, plan a path for the robot to follow when welding the seam, the path including multiple different configurations of the robot, and instruct the robot to weld the seam according to the planned path.
G06K 9/00 - Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
B23K 37/02 - Carriages for supporting the welding or cutting element
B23K 37/04 - Auxiliary devices or processes, not specially adapted for a procedure covered by only one of the other main groups of this subclass for holding or positioning work
G06T 7/70 - Determining position or orientation of objects or cameras
G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
This disclosure provides systems, methods, and apparatuses, including computer programs encoded on computer storage media, that provide for welding techniques for manufacturing robots, such multipass welding techniques for welding robots. For example, the welding techniques may enable generation of weld instructions based on a welding fill plan. The instructions may be generated based on a bead model or a table that indicates a wire feed speed, a travel speed, or a voltage. As another example, the techniques may enable generation of weld instructions based on the one or more dimensions of a seam. As another example, the techniques may enable generation of a joint model of a cross-section of a seam to be welded. The joint model may be generated based on a combination of a plurality of feature components to generate the joint model of the seam. Other aspects and features are also claimed and described.
B25J 11/00 - Manipulators not otherwise provided for
18.
SYSTEM FOR GENERATING INSTRUCTIONS FOR A WELDING ROBOT, COMPUTER IMPLEMENTED METHODS OF GENERATING INSTRUCTIONS FOR A WELDING ROBOT, EACH USING TECHNIQUES FOR MULTIPASS WELDING
B23K 31/00 - Processes relevant to this subclass, specially adapted for particular articles or purposes, but not covered by any single one of main groups
B23K 31/02 - Processes relevant to this subclass, specially adapted for particular articles or purposes, but not covered by any single one of main groups relating to soldering or welding
B23K 31/12 - Processes relevant to this subclass, specially adapted for particular articles or purposes, but not covered by any single one of main groups relating to investigating the properties, e.g. the weldability, of materials
In various examples, a computer-implemented method of generating instructions for a welding robot. The computer-implemented method comprises identifying an expected position of a candidate seam on a part to be welded based on a Computer Aided Design (CAD) model of the part, scanning a workspace containing the part to produce a representation of the part, identifying the candidate seam on the part based on the representation of the part and the expected position of the candidate seam, determining an actual position of the candidate seam, and generating welding instructions for the welding robot based at least in part on the actual position of the candidate seam.
B25J 13/08 - Controls for manipulators by means of sensing devices, e.g. viewing or touching devices
B23K 37/02 - Carriages for supporting the welding or cutting element
B25J 11/00 - Manipulators not otherwise provided for
B23K 37/04 - Auxiliary devices or processes, not specially adapted for a procedure covered by only one of the other main groups of this subclass for holding or positioning work
G06T 7/70 - Determining position or orientation of objects or cameras
G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
SYSTEM FOR GENERATING INSTRUCTIONS FOR A WELDING ROBOT, COMPUTER IMPLEMENTED METHODS OF GENERATING INSTRUCTIONS FOR A WELDING ROBOT, EACH USING TECHNIQUES FOR MULTIPASS WELDING
This disclosure provides a system (200), and computer implemented methods for generating instructions for a welding robot (216) with multipass welding techniques. The welding techniques enable generation of weld instructions based on a welding fill plan. The instructions are generated based on a bead model or a table that indicates a wire feed speed, a travel speed, or a voltage. As another example, the techniques enable generation of weld instructions based on the one or more dimensions of a seam. Or the techniques enable generation of a joint model of a cross-section of a seam to be welded. The joint model is generated based on a combination of a plurality of feature components to generate the joint model of the seam.
B23K 31/00 - Processes relevant to this subclass, specially adapted for particular articles or purposes, but not covered by any single one of main groups
B23K 31/02 - Processes relevant to this subclass, specially adapted for particular articles or purposes, but not covered by any single one of main groups relating to soldering or welding
B23K 31/12 - Processes relevant to this subclass, specially adapted for particular articles or purposes, but not covered by any single one of main groups relating to investigating the properties, e.g. the weldability, of materials
21.
Real time feedback and dynamic adjustment for welding robots
Systems and methods for real time feedback and for updating welding instructions for a welding robot in real time is described herein. The data of a workspace that includes a part to be welded can be received via at least one sensor. This data can be transformed into a point cloud data representing a three-dimensional surface of the part. A desired state indicative of a desired position of at least a portion of the welding robot with respect to the part can be identified. An estimated state indicative of an estimated position of at least the portion of the welding robot with respect to the part can be compared to the desired state. The welding instructions can be updated based on the comparison.
G01B 11/25 - Measuring arrangements characterised by the use of optical techniques for measuring contours or curvatures by projecting a pattern, e.g. moiré fringes, on the object
G05D 3/20 - Control of position or direction using feedback using a digital comparing device
G06V 20/20 - ScenesScene-specific elements in augmented reality scenes
A manufacturing cell for welding a workpiece includes a robotic arm extending between a base and a terminal end, a weld head coupled to the terminal end of the robotic arm such that the weld head is permitted to travel relative to the base of the robotic arm, wherein the weld head is configured to weld the workpiece, a sensor pod coupled to the weld head and including an outer pod housing defining an internal chamber extending between a front end and a rear end of the pod housing, and wherein the front end of the pod housing defines a receptacle, a sensor positioned in the internal chamber of the pod housing, the sensor configured to provide sensor feedback associated with the workpiece, and a consumable window including a transparent material is insertable into the receptacle such that a longitudinal axis of the sensor intersects the consumable window when the consumable window is inserted into the receptacle, and a controller coupled to the sensor pod and configured to operate at least one of the robotic arm and the weld head based on the sensor feedback provided by the sensor of the sensor pod.
B25J 11/00 - Manipulators not otherwise provided for
B25J 19/00 - Accessories fitted to manipulators, e.g. for monitoring, for viewingSafety devices combined with or specially adapted for use in connection with manipulators
This disclosure provides systems, methods, and apparatuses, including computer programs encoded on computer storage media, that provide for optical techniques for manufacturing robots, such as for filtering certain reflections when scanning an object. For example, the techniques may include receiving, from a detector, sensor data based on detected light, the detected light including reflections of light projected by one or more emitters and reflected off of an object. The techniques may further include determining, based on the sensor data, a first-order reflection and a second-order reflection. The techniques may also include determining, based on the first-order reflection and a second-order reflection, a difference, the difference includes a polarity difference, an intensity difference, or a combination thereof. The techniques may include filtering the second-order reflection based on the difference Other aspects and features are also claimed and described.
G01B 11/25 - Measuring arrangements characterised by the use of optical techniques for measuring contours or curvatures by projecting a pattern, e.g. moiré fringes, on the object
This disclosure provides systems, methods, and apparatuses, including computer programs encoded on computer storage media, that provide for optical techniques for manufacturing robots, such as for filtering certain reflections when scanning an object. For example, the techniques may include receiving, from a detector, sensor data based on detected light, the detected light including reflections of light projected by one or more emitters and reflected off of an object. The techniques may further include determining, based on the sensor data, a first-order reflection and a second-order reflection. The techniques may also include determining, based on the first-order reflection and a second-order reflection, a difference, the difference includes a polarity difference, an intensity difference, or a combination thereof. The techniques may include filtering the second-order reflection based on the difference Other aspects and features are also claimed and described.
An adjustable workpiece cradle for a welding system includes a support frame, an elongate flexible member coupled to the support frame and extending along a pathway that forms a concave receptacle configured to laterally receive an elongate workpiece for the welding system, and an adjustment module coupled to the flexible member, wherein the adjustment module includes a powertrain configured to selectably adjust the size of the concave receptacle formed by the pathway of the flexible member.
B23K 37/053 - Auxiliary devices or processes, not specially adapted for a procedure covered by only one of the other main groups of this subclass for holding or positioning work aligning cylindrical workClamping devices therefor
This disclosure provides systems, methods, and apparatuses, including computer programs encoded on computer storage media, for operation of an assembly robotic system. In one aspect of the disclosure, the assembly robotic system includes a tool coupled to a robot device and configured to be selectively coupled to a first object. The assembly robotic system also includes a welding tool, one or more sensors configured to generate sensor data, and a controller. The controller is configured to control the tool to couple the tool to the first object based on the sensor data, control the robot device to bring the first object into a spatial relationship with a second object, and generate a weld instruction to cause the weld tool to weld a seam formed between the first and second objects. Other aspects and features are also claimed and described.
B23K 37/04 - Auxiliary devices or processes, not specially adapted for a procedure covered by only one of the other main groups of this subclass for holding or positioning work
This disclosure provides systems, methods, and apparatuses, including computer programs encoded on computer storage media, for operation of an assembly robotic system. In one aspect of the disclosure, the assembly robotic system includes a tool coupled to a robot device and configured to be selectively coupled to a first object. The assembly robotic system also includes a welding tool, one or more sensors configured to generate sensor data, and a controller. The controller is configured to control the tool to couple the tool to the first object based on the sensor data, control the robot device to bring the first object into a spatial relationship with a second object, and generate a weld instruction to cause the weld tool to weld a seam formed between the first and second objects. Other aspects and features are also claimed and described.
B23K 37/04 - Auxiliary devices or processes, not specially adapted for a procedure covered by only one of the other main groups of this subclass for holding or positioning work
This disclosure provides systems, methods, and apparatuses, including computer programs encoded on computer storage media, for operation of an assembly robotic system. In one aspect of the disclosure, the assembly robotic system includes a tool coupled to a robot device and configured to be selectively coupled to a first object. The assembly robotic system also includes a welding tool, one or more sensors configured to generate sensor data, and a controller. The controller is configured to control the tool to couple the tool to the first object based on the sensor data, control the robot device to bring the first object into a spatial relationship with a second object, and generate a weld instruction to cause the weld tool to weld a seam formed between the first and second objects. Other aspects and features are also claimed and described.
A transportable manufacturing cell including a robotic arm extending between a base and a terminal end, a tool attached to the terminal end of the robotic arm, a positioner unit including a positioner extending between a base and a connector, the connector configured to secure a workpiece to the positioner, a sensor unit including one or more sensors, a controller configured to control the operation of the robotic arm and the tool attached to the robotic arm, and a support platform assembly including a free-standing first platform and a separate and distinct free-standing second platform, wherein the robotic arm and the sensor unit are each mounted to the first platform and the positioner unit is mounted to the second platform.
B23P 21/00 - Machines for assembling a multiplicity of different parts to compose units, with or without preceding or subsequent working of such parts, e.g. with programme control
30.
MANUFACTURING CELLS HAVING MODULAR SUPPORT PLATFORMS
A transportable manufacturing cell including a robotic arm extending between a base and a terminal end, a tool attached to the terminal end of the robotic arm, a positioner unit including a positioner extending between a base and a connector, the connector configured to secure a workpiece to the positioner, a sensor unit including one or more sensors, a controller configured to control the operation of the robotic arm and the tool attached to the robotic arm, and a support platform assembly including a free-standing first platform and a separate and distinct free-standing second platform, wherein the robotic arm and the sensor unit are each mounted to the first platform and the positioner unit is mounted to the second platform.
B25J 21/00 - Chambers provided with manipulation devices
B23K 37/04 - Auxiliary devices or processes, not specially adapted for a procedure covered by only one of the other main groups of this subclass for holding or positioning work
B23P 21/00 - Machines for assembling a multiplicity of different parts to compose units, with or without preceding or subsequent working of such parts, e.g. with programme control
A method for calibrating a tool center point (TCP) of a robotic welding system. The method includes receiving a plurality of images captured from a plurality of image sensors of the robotic welding system, the plurality of images containing at least a portion of a protrusion extending from a tip of a weldhead of the robotic welding system, and identifying by a controller of the robotic welding system the protrusion extending from the weldhead in the plurality of images. The method additionally includes defining by the controller a longitudinal axis of the protrusion based on the protrusion identified in the plurality of images, and identifying by the controller a location in three-dimensional (3D) space of the weldhead based on the protrusion identified in the plurality of images and the defined longitudinal axis of the protrusion.
This disclosure provides systems, methods, and apparatuses, including computer programs encoded on computer storage media, that provide for training, implementing, or updated machine learning logic, such as an artificial neural network, to model a manufacturing process performed in a manufacturing robot environment. For example, the machine learning logic may be trained and implemented to learn from or make adjustments based on one or more operational characteristics associated with the manufacturing robot environment. As another example, the machine learning logic, such as a trained neural network, may be implemented in a semi-autonomous or autonomous manufacturing robot environment to model a manufacturing process and to generate a manufacturing result. As another example, the machine learning logic, such as the trained neural network, may be updated based on data that is captured and associated with a manufacturing result. Other aspects and features are also claimed and described.
This disclosure provides systems, methods, and apparatuses, including computer programs encoded on computer storage media, that provide for training, implementing, or updated machine learning logic, such as an artificial neural network, to model a manufacturing process performed in a manufacturing robot environment. For example, the machine learning logic may be trained and implemented to learn from or make adjustments based on one or more operational characteristics associated with the manufacturing robot environment. As another example, the machine learning logic, such as a trained neural network, may be implemented in a semi-autonomous or autonomous manufacturing robot environment to model a manufacturing process and to generate a manufacturing result. As another example, the machine learning logic, such as the trained neural network, may be updated based on data that is captured and associated with a manufacturing result. Other aspects and features are also claimed and described.
This disclosure provides systems, methods, and apparatuses, including computer programs encoded on computer storage media, that provide for training, implementing, or updated machine learning logic, such as an artificial neural network, to model a manufacturing process performed in a manufacturing robot environment. For example, the machine learning logic may be trained and implemented to learn from or make adjustments based on one or more operational characteristics associated with the manufacturing robot environment. As another example, the machine learning logic, such as a trained neural network, may be implemented in a semi-autonomous or autonomous manufacturing robot environment to model a manufacturing process and to generate a manufacturing result. As another example, the machine learning logic, such as the trained neural network, may be updated based on data that is captured and associated with a manufacturing result. Other aspects and features are also claimed and described.
In some examples, a method for determining weldable and unweldable portions of a seam comprises receiving a representation of a part including the seam. The method also includes discretizing a representation of the seam into a plurality of waypoints. The method also includes evaluating each waypoint from the plurality of waypoints for feasibility of welding. The method further includes generating a weld path through at least a subset of the plurality of waypoints in accordance with the feasibility of welding.
G06F 119/02 - Reliability analysis or reliability optimisationFailure analysis, e.g. worst case scenario performance, failure mode and effects analysis [FMEA]
In various examples, a computer-implemented method of generating instructions for a welding robot. The computer-implemented method comprises identifying an expected position of a candidate seam on a part to be welded based on a Computer Aided Design (CAD) model of the part, scanning a workspace containing the part to produce a representation of the part, identifying the candidate seam on the part based on the representation of the part and the expected position of the candidate seam, determining an actual position of the candidate seam, and generating welding instructions for the welding robot based at least in part on the actual position of the candidate seam.
B23K 37/02 - Carriages for supporting the welding or cutting element
B23K 37/04 - Auxiliary devices or processes, not specially adapted for a procedure covered by only one of the other main groups of this subclass for holding or positioning work
B25J 11/00 - Manipulators not otherwise provided for
B25J 13/08 - Controls for manipulators by means of sensing devices, e.g. viewing or touching devices
G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
G06T 7/70 - Determining position or orientation of objects or cameras
In some examples, an autonomous robotic welding system comprises a workspace including a part having a seam, a sensor configured to capture multiple images within the workspace, a robot configured to lay weld along the seam, and a controller. The controller is configured to identify the seam on the part in the workspace based on the multiple images, plan a path for the robot to follow when welding the seam, the path including multiple different configurations of the robot, and instruct the robot to weld the seam according to the planned path.
B25J 13/08 - Controls for manipulators by means of sensing devices, e.g. viewing or touching devices
B23K 37/02 - Carriages for supporting the welding or cutting element
B25J 11/00 - Manipulators not otherwise provided for
B23K 37/04 - Auxiliary devices or processes, not specially adapted for a procedure covered by only one of the other main groups of this subclass for holding or positioning work
G06T 7/70 - Determining position or orientation of objects or cameras
G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
Systems and methods for real time feedback and for updating welding instructions for a welding robot in real time is described herein. The data of a workspace that includes a part to be welded can be received via at least one sensor. This data can be transformed into a point cloud data representing a three-dimensional surface of the part. A desired state indicative of a desired position of at least a portion of the welding robot with respect to the part can be identified. An estimated state indicative of an estimated position of at least the portion of the welding robot with respect to the part can be compared to the desired state. The welding instructions can be updated based on the comparison.
G06T 7/70 - Determining position or orientation of objects or cameras
G06V 20/20 - ScenesScene-specific elements in augmented reality scenes
B23K 9/095 - Monitoring or automatic control of welding parameters
B23K 9/127 - Means for tracking lines during arc welding or cutting
B23K 26/03 - Observing, e.g. monitoring, the workpiece
G01B 11/25 - Measuring arrangements characterised by the use of optical techniques for measuring contours or curvatures by projecting a pattern, e.g. moiré fringes, on the object
G05D 3/20 - Control of position or direction using feedback using a digital comparing device
In various examples, a computer-implemented method of generating instructions for a welding robot. The computer-implemented method comprises identifying an expected position of a candidate seam on a part to be welded based on a Computer Aided Design (CAD) model of the part, scanning a workspace containing the part to produce a representation of the part, identifying the candidate seam on the part based on the representation of the part and the expected position of the candidate seam, determining an actual position of the candidate seam, and generating welding instructions for the welding robot based at least in part on the actual position of the candidate seam.
B25J 11/00 - Manipulators not otherwise provided for
B25J 13/08 - Controls for manipulators by means of sensing devices, e.g. viewing or touching devices
B23K 37/04 - Auxiliary devices or processes, not specially adapted for a procedure covered by only one of the other main groups of this subclass for holding or positioning work
G06T 7/70 - Determining position or orientation of objects or cameras
G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
In various examples, a computer-implemented method of generating instructions for a welding robot. The computer-implemented method comprises identifying an expected position of a candidate seam on a part to be welded based on a Computer Aided Design (CAD) model of the part, scanning a workspace containing the part to produce a representation of the part, identifying the candidate seam on the part based on the representation of the part and the expected position of the candidate seam, determining an actual position of the candidate seam, and generating welding instructions for the welding robot based at least in part on the actual position of the candidate seam.
In some examples, an autonomous robotic welding system comprises a workspace including a part having a seam, a sensor configured to capture multiple images within the workspace, a robot configured to lay weld along the seam, and a controller. The controller is configured to identify the seam on the part in the workspace based on the multiple images, plan a path for the robot to follow when welding the seam, the path including multiple different configurations of the robot, and instruct the robot to weld the seam according to the planned path.
In various examples, a computer-implemented method of generating instructions for a welding robot. The computer-implemented method comprises identifying an expected position of a candidate seam on a part to be welded based on a Computer Aided Design (CAD) model of the part, scanning a workspace containing the part to produce a representation of the part, identifying the candidate seam on the part based on the representation of the part and the expected position of the candidate seam, determining an actual position of the candidate seam, and generating welding instructions for the welding robot based at least in part on the actual position of the candidate seam.
In some examples, an autonomous robotic welding system comprises a workspace including a part having a seam, a sensor configured to capture multiple images within the workspace, a robot configured to lay weld along the seam, and a controller. The controller is configured to identify the seam on the part in the workspace based on the multiple images, plan a path for the robot to follow when welding the seam, the path including multiple different configurations of the robot, and instruct the robot to weld the seam according to the planned path.
In some examples, an autonomous robotic welding system comprises a workspace including a part having a seam, a sensor configured to capture multiple images within the workspace, a robot configured to lay weld along the seam, and a controller. The controller is configured to identify the seam on the part in the workspace based on the multiple images, plan a path for the robot to follow when welding the seam, the path including multiple different configurations of the robot, and instruct the robot to weld the seam according to the planned path.
B25J 13/08 - Controls for manipulators by means of sensing devices, e.g. viewing or touching devices
B23K 37/02 - Carriages for supporting the welding or cutting element
B25J 11/00 - Manipulators not otherwise provided for
B23K 37/04 - Auxiliary devices or processes, not specially adapted for a procedure covered by only one of the other main groups of this subclass for holding or positioning work
G06T 7/70 - Determining position or orientation of objects or cameras
G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
Some embodiments described herein relate to optical systems and methods for determining the shape and/or size of objects that include projecting a pattern of light onto the object. The pattern of light can be configured such that first-order reflections can be distinguished from second- and/or higher-order reflections, which can be rejected. Thus, even in instances in which the pattern of light is reflected onto the object multiple times, the original, or first-order, reflection can be detected, distinguished, and/or used for laser triangulation. In some embodiments, a pattern of light that does not have reflection and/or rotational symmetry is projected onto the object, such that second-order and/or higher-order reflections can be distinguished from the first-order reflection.
G01B 11/25 - Measuring arrangements characterised by the use of optical techniques for measuring contours or curvatures by projecting a pattern, e.g. moiré fringes, on the object
46.
Real time feedback and dynamic adjustment for welding robots
Systems and methods for real time feedback and for updating welding instructions for a welding robot in real time is described herein. The data of a workspace that includes a part to be welded can be received via at least one sensor. This data can be transformed into a point cloud data representing a three-dimensional surface of the part. A desired state indicative of a desired position of at least a portion of the welding robot with respect to the part can be identified. An estimated state indicative of an estimated position of at least the portion of the welding robot with respect to the part can be compared to the desired state. The welding instructions can be updated based on the comparison.
G06T 7/70 - Determining position or orientation of objects or cameras
G06V 20/20 - ScenesScene-specific elements in augmented reality scenes
B23K 9/095 - Monitoring or automatic control of welding parameters
B23K 9/127 - Means for tracking lines during arc welding or cutting
B23K 26/03 - Observing, e.g. monitoring, the workpiece
G01B 11/25 - Measuring arrangements characterised by the use of optical techniques for measuring contours or curvatures by projecting a pattern, e.g. moiré fringes, on the object
G05D 3/20 - Control of position or direction using feedback using a digital comparing device
G06K 9/62 - Methods or arrangements for recognition using electronic means
47.
REAL TIME FEEDBACK AND DYNAMIC ADJUSTMENT FOR WELDING ROBOTS
Systems and methods for real time feedback and for updating welding instructions for a welding robot in real time is described herein. The data of a workspace that includes a part to be welded can be received via at least one sensor. This data can be transformed into a point cloud data representing a three-dimensional surface of the part. A desired state indicative of a desired position of at least a portion of the welding robot with respect to the part can be identified. An estimated state indicative of an estimated position of at least the portion of the welding robot with respect to the part can be compared to the desired state. The welding instructions can be updated based on the comparison.
B23K 26/08 - Devices involving relative movement between laser beam and workpiece
B23K 31/00 - Processes relevant to this subclass, specially adapted for particular articles or purposes, but not covered by any single one of main groups
G05B 19/18 - Numerical control [NC], i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form
09 - Scientific and electric apparatus and instruments
37 - Construction and mining; installation and repair services
40 - Treatment of materials; recycling, air and water treatment,
42 - Scientific, technological and industrial services, research and design
Goods & Services
Autonomous welding machines welding; autonomous
pick-and-place machines; autonomous machines for additive
manufacturing. Recorded and downloadable computer software for operating
and programming autonomous welding machines welding,
autonomous pick-and-place machines, and autonomous machines
for additive manufacturing. Rental, installation, and repair of autonomous welding
machines welding, autonomous pick-and-place machines, and
autonomous machines for additive manufacturing. Custom manufacture of autonomous machines for autonomous
welding machines welding, autonomous pick-and-place
machines, and autonomous machines for additive
manufacturing; welding services. Industrial research relating to autonomous welding machines
welding, autonomous pick-and-place machines, and autonomous
machines for additive manufacturing; computer monitoring
services relating to performance of autonomous welding
machines welding, autonomous pick-and-place machines, and
autonomous machines for additive manufacturing; software as
a service services featuring non-downloadable computer
software for operating and programming autonomous welding
machines welding, autonomous pick-and-place machines, and
autonomous machines for additive manufacturing.
09 - Scientific and electric apparatus and instruments
37 - Construction and mining; installation and repair services
40 - Treatment of materials; recycling, air and water treatment,
42 - Scientific, technological and industrial services, research and design
Goods & Services
(1) Autonomous welding machines; autonomous pick-and-place machines for metal working; autonomous welding machines for additive manufacturing
(2) Recorded and downloadable computer software for operating and programming autonomous welding machines, autonomous pick-and-place machines for metal working, and autonomous welding machines for additive manufacturing (1) Rental, installation, and repair of autonomous welding machines, autonomous pick-and-place machines for metal working, and autonomous welding machines for additive manufacturing
(2) Custom manufacture of autonomous machines for autonomous welding machines, autonomous pick-and-place machines for metal working, and autonomous welding machines for additive manufacturing; welding services
(3) Industrial research relating to autonomous welding machines, autonomous pick-and-place machines for metal working, and autonomous welding machines for additive manufacturing; computer monitoring services relating to performance of autonomous welding machines, autonomous pick-and-place machines for metal working, and autonomous welding machines for additive manufacturing; software as a service services featuring non-downloadable computer software for operating and programming autonomous welding machines, autonomous pick-and-place machines for metal working, and autonomous welding machines for additive manufacturing
09 - Scientific and electric apparatus and instruments
Goods & Services
Recorded and downloadable computer software for operating and programming autonomous welding machines welding, autonomous pick-and-place machines, and autonomous machines for additive manufacturing
37 - Construction and mining; installation and repair services
Goods & Services
Rental, installation, and repair of autonomous welding machines welding, autonomous pick-and-place machines, and autonomous machines for additive manufacturing
42 - Scientific, technological and industrial services, research and design
Goods & Services
Industrial research relating to autonomous welding machines welding, autonomous pick-and-place machines, and autonomous machines for additive manufacturing; Computer monitoring services relating to performance of autonomous welding machines welding, autonomous pick-and-place machines, and autonomous machines for additive manufacturing; Software as a service services featuring non-downloadable computer software for operating and programming autonomous welding machines welding, autonomous pick-and-place machines, and autonomous machines for additive manufacturing
Some embodiments described herein relate to optical systems and methods for determining the shape and/or size of objects that include projecting a pattern of light onto the object. The pattern of light can be configured such that first-order reflections can be distinguished from second- and/or higher-order reflections, which can be rejected. Thus, even in instances in which the pattern of light is reflected onto the object multiple times, the original, or first-order, reflection can be detected, distinguished, and/or used for laser triangulation. In some embodiments, a pattern of light that does not have reflection and/or rotational symmetry is projected onto the object, such that second-order and/or higher-order reflections can be distinguished from the first-order reflection.
G06K 9/00 - Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
G01B 11/25 - Measuring arrangements characterised by the use of optical techniques for measuring contours or curvatures by projecting a pattern, e.g. moiré fringes, on the object
Some embodiments described herein relate to optical systems and methods for determining the shape and/or size of objects that include projecting a pattern of light onto the object. The pattern of light can be configured such that first-order reflections can be distinguished from second- and/or higher-order reflections, which can be rejected. Thus, even in instances in which the pattern of light is reflected onto the object multiple times, the original, or first-order, reflection can be detected, distinguished, and/or used for laser triangulation. In some embodiments, a pattern of light that does not have reflection and/or rotational symmetry is projected onto the object, such that second-order and/or higher-order reflections can be distinguished from the first-order reflection.
G01B 11/25 - Measuring arrangements characterised by the use of optical techniques for measuring contours or curvatures by projecting a pattern, e.g. moiré fringes, on the object
G06T 7/521 - Depth or shape recovery from laser ranging, e.g. using interferometryDepth or shape recovery from the projection of structured light
Some embodiments described herein relate to optical systems and methods for determining the shape and/or size of objects that include projecting a pattern of light onto the object. The pattern of light can be configured such that first-order reflections can be distinguished from second- and/or higher-order reflections, which can be rejected. Thus, even in instances in which the pattern of light is reflected onto the object multiple times, the original, or first-order, reflection can be detected, distinguished, and/or used for laser triangulation. In some embodiments, a pattern of light that does not have reflection and/or rotational symmetry is projected onto the object, such that second-order and/or higher-order reflections can be distinguished from the first-order reflection.
G06K 9/00 - Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
G01B 11/25 - Measuring arrangements characterised by the use of optical techniques for measuring contours or curvatures by projecting a pattern, e.g. moiré fringes, on the object
