Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.