Abstract: A system and method for operating a robotic system to register unrecognized objects is disclosed. The robotic system may use first image data representative of an unrecognized object to derive an initial minimum viable region (MVR). The robotic system may analyze second image data representative of the unrecognized object to detect a condition representative of an accuracy of the initial MVR. The robotic system may register the initial MVR or an adjustment thereof based on the detected condition.

Abstract: A method for operating a robotic system includes determining a discretized object model based on source sensor data; comparing the discretized object model to a packing plan or to master data; determining a discretized platform model based on destination sensor data; determining height measures based on the destination sensor data; comparing the discretized platform model and/or the height measures to an expected platform model and/or expected height measures; and determining one or more errors by (i) determining at least one source matching error by identifying one or more disparities between (a) the discretized object model and (b) the packing plan or the master data or (ii) determining at least one destination matching error by identifying one or more disparities between (a) the discretized platform model or the height measures and (b) the expected platform model or the expected height measures, respectively.

Abstract: A system and method of operation of a robotic system including: receiving a sensor reading associated with a target object; generating a base plan for performing a task on the target object, wherein generating the base plan includes determining a grip point and one or more grip patterns associated with the grip point for gripping the target object based on a location of the grip point relative to a designated area, a task location, and another target object; implementing the base plan for performing the task by operating an actuation unit and one or more suction grippers according to a grip pattern rank, to generate an established grip on the target object, wherein the established grip is at a grip pattern location associated with the grip patterns; measuring the established grip; comparing the established grip to a force threshold; and re-gripping the target object based on the established grip falling below the force threshold.

Abstract: A method of operating a robotic system includes: receiving first image data representative of a package surface; identifying a pair of edges based on the first image data; determining a minimum viable region based on the pair of edges; receiving second image data representative of the package after the lift; and creating registration data based on the first and second image data.

Abstract: The present disclosure provides a control method of a robotic system. The control method includes: deriving an approach location at which the end effector grips an operation object; deriving a scan location for scanning an identifier of the operation object; and based on the approach location and the scan location, creating or deriving a control sequence to instruct the robot to execute the control sequence. The control sequence includes (1) gripping the operation object from a start location; (2) scanning an identifier of the operation object with a scanner located between the start location and a task location; (3) temporarily releasing the operation object from the end effector and regripping the operation object by the end effector to be shifted, at a shift location, when a predetermined condition is satisfied; and (4) moving the operation object to the task location.

Abstract: A computing system and method for object recognition is presented. The method includes the computing system obtaining an image for representing the one or more objects, and generating a target image portion associated with one of the one or more objects. The computing system determines whether to classify the target image portion as textured or textureless, and selects a template storage space from among a first and second template storage space, wherein the first template storage space is cleared more often relative to the second template storage space. The first template storage space is selected in response to a textureless classification, and the second template storage space is selected as the template storage space in response to a textured classification. The computing system performs object recognition based on the target image portion and the selected template storage space.

Abstract: A gripper including: an orientation sensor configured to generate an orientation reading for a target object; a first grasping blade and a second grasping blade configured to secure the target object in conjunction with the first grasping blade and at an opposite end of the target object relative to the first grasping blade; a first position sensor, of the first grasping blade, configured to generate a first position reading of the first grasping blade relative to the target object; a second position sensor, of the second grasping blade, configured to generate a second position reading of the second grasping blade relative to the target object; and a blade actuator configured to secure the target object with the first grasping blade and the second grasping blade based on a valid orientation of the orientation reading and based on the first position reading and the second position reading indicating a stable condition.

Abstract: Systems and methods for processing spatial structure data are provided. The system accesses spatial structure data, which describes object structure, and which has depth information indicative of a plurality of layers for the object structure. The system further extracts, from the spatial structure data, a portion of the spatial structure data representative of one layer of the plurality of layers. The system identifies, from the portion of the spatial structure data, a plurality of vertices that describe a contour of the layer. Additionally, the system identifies convex corners of the layer based on the plurality of vertices and performs object recognition according to the convex corners.

Abstract: A computing system and method are presented. The computing system may store sensor data which includes: (i) a set of movement data, and (ii) a set of actuation data. The computing system may divide the sensor data into training data and test data by: (i) selecting, as the training data, movement training data and corresponding actuation training data, and (ii) selecting, as the test data, movement test data and corresponding actuation test data. The computing system may determine, based on the movement training data and the actuation training data, at least one of: (i) a friction parameter estimate or (ii) a center of mass (CoM) estimate, and may determine actuation prediction data based on the movement test data and based on the at least one of the friction parameter estimate or the CoM estimate. The computing system may further determine residual data, and determine a value for an error parameter.

Abstract: A system and method for motion planning is presented. The system is configured, when an object is or has been in a camera field of view of a camera, to receive first image information that is generated when the camera has a first camera pose. The system is further configured to determine, based on the first image information, a first estimate of the object structure, and to identify, based on the first estimate of the object structure or based on the first image information, an object corner. The system is further configured to cause an end effector apparatus to move the camera to a second camera pose, and to receive second image information for representing the object's structure. The system is configured to determine a second estimate of the object's structure based on the second image information, and to generate a motion plan based on at least the second estimate.

Abstract: A computing system and method for estimating friction and/or center of mass (CoM) are presented. The system may perform the method by selecting at least one of: (i) a first joint from among a plurality of joints, or (ii) a first arm segment from among a plurality of arm segments. The computing system further outputs a set of one or more movement commands for causing robot arm movement that includes relative movement between the first arm segment and a second arm segment via the first joint, and receiving a set of actuation data and a set of movement data associated with the first joint or the first arm segment. The computing system further determines, based on the set of actuation data and the set of movement data, at least one of: (i) a friction parameter estimate or (ii) a CoM estimate.

Abstract: A method and system for processing camera images is presented. The system receives a first depth map generated based on information sensed by a first type of depth-sensing camera, and receives a second depth map generated based on information sensed by a second type of depth-sensing camera. The first depth map includes a first set of pixels that indicate a first set of respective depth values. The second depth map includes a second set of pixels that indicate a second set of respective depth values. The system identifies a third set of pixels of the first depth map that correspond to the second set of pixels of the second depth map, identifies one or more empty pixels from the third set of pixels, and updates the first depth map by assigning to each empty pixel a respective depth value based on the second depth map.

Abstract: An trajectory information generating unit for generating trajectory information defining a trajectory for which a picking hand picks a work at a first position and arranges the work at a second position, an execution control unit for operating a picking apparatus based on trajectory information generated by the trajectory information generating unit, and an execution time estimating unit for estimating a period of time from when the picking apparatus receives an instruction for starting an operation on a work to a time when the operation of the picking apparatus on the work is ended are included. The trajectory information generating unit may adjust an amount of calculation based on an estimation result of the execution time estimating unit.

Abstract: A method for operating a robotic system that includes calculating a base motion plan, wherein the base motion plan includes a sequence of commands or settings, or a combination thereof, that operates a robotic arm and a gripper to transfer a target object from a start location to a task location; receiving a contact measure while executing the base motion plan, wherein the contact measure represents an amount of grip of the gripper on the target object; and generating one or more actuator commands/settings that deviate from the base motion plan when the contact measure fails to satisfy a threshold, wherein the one or more actuator commands/settings thereof are configured to operate the robotic arm, the gripper, or a combination thereof to execute one or more response actions not included in the base motion plan.

Abstract: The present disclosure relates to operation of a robotic system to transfer an object from a source to a destination. The robotic system may implement one or more motion plans or portions thereof to operate a picking robot to grip and lift the object and place a transfer tray under the lifted object. The robotic system may further implement the one or more motion plans or portions thereof to place the object on the transfer tray and laterally displace the transfer tray and the object thereon toward the destination. The robotic system may operate a placement mechanism to transfer the object from the transfer tray to the destination.

Abstract: A method for operating a robotic system including determining an initial pose of a target object based on imaging data; calculating a confidence measure associated with an accuracy of the initial pose; and determining that the confidence measure fails to satisfy a sufficiency condition; and deriving a motion plan accordingly for scanning an object identifier while transferring the target object from a start location to a task location.

Abstract: The present disclosure relates to methods and systems for generating a verified minimum viable range (MVR) of an object. An exposed outer corner and exposed edges of an object may be identified by processing one or more image data. An initial MVR may be generated by identifying opposing parallel edges opposing the exposed edges. The initial MVR may be adjusted, and the adjusted result may be tested to generate a verified MVR.

Abstract: A computing system and a method for calibration verification is presented. The computing system is configured to perform a first calibration operation, and to control a robot arm to move a verification symbol to a reference location. The robot control system further receives, from a camera, a reference image of the verification symbol, and determines a reference image coordinate for the verification symbol. The robot control system further controls the robot arm to move the verification symbol to the reference location again during an idle period, receives an additional image of the verification symbol, and determines a verification image coordinate. The robot control system determines a deviation parameter value based the reference image coordinate and the verification image coordinate, and whether the deviation parameter value exceeds a defined threshold, and performs a second calibration operation if the threshold is exceeded.

Abstract: A robotic system for arranging packages at a destination according to a stacking sequence. The robotic system uses a storage area for temporarily storing packages that arrive out-of-sequence until they are next-in-sequence for placement at the destination. The robotic system processes an incoming package, determines if it is next-in-sequence for placement at the destination, and if it is, places the package at the destination. On the other hand, if it is not next-in-sequence for placement at the destination, it stores the package in the storage area. A package in the storage area is transferred to the destination when it is next-in-sequence for placement at the destination. By using the temporary storage for storing out of sequence packages, the robotic system eliminates the need for receiving the packages in a stacking sequence, which also eliminates the need for sequencing machines.

Abstract: A robot control system and a method for updating camera calibration is presented. The method comprises the robot control system performing a first camera calibration to determine camera calibration information, and outputting a first movement command based on the camera calibration information for a robot operation. The method further comprises outputting, after the first camera calibration, a second movement command to move a calibration pattern within a camera field of view, receiving one or more calibration images, and adding the one or more calibration images to a captured image set. The method further comprises performing a second camera calibration based on calibration images in the captured image set to determine updated camera calibration information, determining whether a deviation between the camera calibration information and the updated camera calibration information exceeds a defined threshold, and outputting a notification signal if the deviation exceeds the defined threshold.