Abstract: A method for assembling parts in an assembly line, such as an automotive final assembly line, is disclosed. The method includes advancing a part along the assembly line with an Automated Guided Vehicle (AGV), arranging a first real time vision system to monitor the position of the AGV in at least two directions, and providing the readings of the first real time vision system to a controller arranged to control an assembly unit of the assembly line to perform an automated operation on the part that is advanced or supported by the AGV. An assembly line is also disclosed.

Abstract: A system and method for collecting data regarding operation of a robot using, at least in part, responses from a first operation model to an input of sensed data from a plurality of sensors. The collected data can be used to optimize the first operation model to generate a second operation model. While the first operation model is being optimized, a train data-driven model that utilizes an end-to-end learning approach can be generated that is based, at least in part, on the collected data. Both the second operation model and the train data-driven model can be evaluated, and, based on such evaluation, a determination can be made as to whether the train data-driven model is reliable. Moreover, based on a comparison of the models, one of the second operation model and the train data-driven model can be selected for validation, and if validated, used in the operation of the robot.

Abstract: A system and method that automatically resolves conflicts among sensor information in a sensor fusion robot system. Such methods can accommodate converging ambiguous and divergent sensor information in a manner that can allow continued, and relatively accurate, robotic operations. The processes can include handling sensor conflict via sensor prioritization, including, but not limited, prioritization based on the particular stage or segment of the assembly operation when the conflict occurs, overriding sensor data that exceeds a threshold value, and/or prioritization based on evaluations of recent sensor performance, predictions, system configuration, and/or historical information. The processes can include responding to sensor conflicts through comparisons of the accuracy of workpiece location predictions from different sensors during different assembly stages in connection with arriving at a determination of which sensor(s) is providing accurate and reliable predictions.

Abstract: A system and method for use of artificial and nature racking features to calibrate sensors and tune a robotic control system of a sensor fusion guided robotic assembly. The artificial tracking features can have a configuration, or be at a location, that may be less susceptible to noise and error. Thus, the sensors can at least initially be calibrated, and the control system initially tuned, using the first tracking features until the sensors and control system satisfy operation performance criteria. Second tracking features, which may correspond to features on a workpiece that will be utilized in an assembly operation performed by the robot. By pre-calibrating the sensors, and pre-tuning the control system prior to calibration using the second tracking features, sensor calibration and system tuning based on the second tracking features can be attained faster and with less complexity.

Abstract: A system and method for determining performance of a robot. In one form the robot is constructed as you assembling automotive workpieces onto an automobile assembly. In one form the robot accomplishes the task of assembling an automotive workpiece onto the automotive assembly by using vision feedback and force feedback. The vision feedback can use any number of features perform its function. Such features can include an artificial feature such as but not limited to a QR code, as well as a natural feature such as a portion of the workpiece or automotive assembly. In one embodiment the robot is capable of detecting a collision event and assessing the severity of the collision event. In another embodiment the robot is capable of evaluating its performance by attracting a performance metric against a performance threshold, and comparing a sensor fusion output with a sensor fusion output reference.

Abstract: A robotic system is provided for assembling parts together. In the assembly process, both parts are moving separately with one part moving on an assembly base and another part moving on a moveable arm of a robot base. Motion data is measured by an inertial measurement unit (IMU) sensor. Movement of the robot base or moveable arm is then compensated based on the measured motion to align the first and second parts with each other and assemble the parts together.

Abstract: A system and method for predicting the location at which a feature that is being tracked during a robotic assembly operation will be located within one or more images captured by a vision device. A vision device can be mounted to a robot such that the location of the vision device as the robot moves can be known or determined. In the event of an interruption of the tracking of the feature by the vision device as the corresponding workpiece is moving, the location of the feature relative to a vision device can be predicted, such as, via use of current or past historical movement information for the feature and/or the associated workpiece. Using the predicted location of the feature and the known location of the vision device, the location at which the feature will be located in an image(s) captured by the vision device can be predicted.

Abstract: A method is disclosed, including: providing a part having a target at which an assembly operation is to be performed by an industrial robot; determining the target position, by controlling the end effector of the robot to approach the target, detecting a contact between a location utensil attached to the end effector and the target and controlling the end effector of the robot at least by force control until the location utensil reaches a predetermined position relative to the target, and determining the target position as indicated by the absolute position of the location utensil when the location utensil is in said predetermined position relative to the target; registering the target position; and controlling the end effector of the robot to perform the assembly operation at the registered target position. An assembly unit or system is also disclosed.

Abstract: A robotic system is provided for assembling parts together. In the assembly process, both parts are moving separately with one part moving on an assembly base and another part moving on a moveable arm of a robot base. Motion data is measured by an inertial measurement (IMU) sensor. Movement of the robot base or moveable arm is then compensated based on the measured motion to align the first and second parts with each other and assemble the parts together.

Abstract: A robotic assembly operation is provided for assembling a second part to a first part. During setup of the assembly operation, control parameters and a control scheme are set and changed by simulating the operation and testing whether performance requirements are met. A dry run may be performed thereafter, and test data may be collected after running the simulation to determine if the performance requirements are satisfied during the dry run. During production, production data may also be collected and control parameters may be tuned when changes occur during production in order to maintain stable assembly.

Abstract: A system and method for predicting the location at which a feature that is being tracked during a robotic assembly operation will be located within one or more images captured by a vision device. A vision device can be mounted to a robot such that the location of the vision device as the robot moves can be known or determined. In the event of an interruption of the tracking of the feature by the vision device as the corresponding workpiece is moving, the location of the feature relative to a vision device can be predicted, such as, via use of current or past historical movement information for the feature and/or the associated workpiece. Using the predicted location of the feature and the known location of the vision device, the location at which the feature will be located in an image(s) captured by the vision device can be predicted.

Abstract: A system and method for automatic recovery from a failure in a robotic assembly operation using multiple sensor input. Moreover, following detection of an error in an assembly operation from data provided by a first sensor, a recovery plan can be executed, and, if successful, a reattempt at the failed assembly operation can commence. The assembly stage during which the error occurred can be detected by a second sensor that is different from the first sensor. Identification of the assembly stage can assist with determining the recovery plan, as well as identifying the assembly operation that is to be reattempted. The failure can be detected by comparing information obtained from a sensor, such as, for example, a force signature, with corresponding historical information, including historical information obtained at the identified assembly stage for prior workpieces.

Abstract: A system and method that automatically resolves conflicts among sensor information in a sensor fusion robot system. Such methods can accommodate converging ambiguous and divergent sensor information in a manner that can allow continued, and relatively accurate, robotic operations. The processes can include handling sensor conflict via sensor prioritization, including, but not limited, prioritization based on the particular stage or segment of the assembly operation when the conflict occurs, overriding sensor data that exceeds a threshold value, and/or prioritization based on evaluations of recent sensor performance, predictions, system configuration, and/or historical information. The processes can include responding to sensor conflicts through comparisons of the accuracy of workpiece location predictions from different sensors during different assembly stages in connection with arriving at a determination of which sensor(s) is providing accurate and reliable predictions.

Abstract: A method for assembling parts in an assembly line, such as an automotive final assembly line, is disclosed. The method includes advancing a part along the assembly line with an Automated Guided Vehicle (AGV), arranging a first real time vision system to monitor the position of the AGV in at least two directions, and providing the readings of the first real time vision system to a controller arranged to control an assembly unit of the assembly line to perform an automated operation on the part that is advanced or supported by the AGV. An assembly line is also disclosed.