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 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: 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 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.

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 computing system including a processing circuit in communication with a robot and a camera having a field of view. The processing circuit obtains image information based on the objects in the field of view and a loading environment, the loading environment which includes loading areas, an object queue, and a buffer zone. The computing system is configured to use the obtained image information in motion planning operations for the retrieval and placement of objects from the object queue into the loading environment. Pallets provided within the loading environment (i.e., within the loading areas) are dedicated to receiving objects having corresponding object type identifiers. The computer system further uses the image information to determine the fill status of pallets existing within the loading environment, and whether new pallets need to be brought into the loading environment and/or swapped out with existing pallets to account for future planning and placement operations.

Abstract: Robotic systems with variable gripping mechanisms, and related systems and methods are disclosed herein. In some embodiments, the robotic system includes a robotic arm and an object-gripping assembly coupled to the robotic arm. The object-gripping assembly can include a main body coupled to the robotic arm through an external connector on an upper surface of the main body and a vacuum operated gripping component coupled to a lower surface of the main body. The object-gripping assembly can also include a variable-width gripping component coupled to the main body. The variable-width gripping component is movable between a fully folded state, a plurality of extended states, and a clamping state to grip a variety of target objects of varying shapes, sizes, weights, and orientations.

Abstract: A computing system including a processing circuit in communication with a camera having a field of view. The processing circuit is configured to perform operations related to detecting, identifying, and retrieving objects disposed amongst a plurality of objects. The processing circuit may be configured to perform operations related to object recognition template generation, feature generation, hypothesis generation, hypothesis refinement, and hypothesis validation.

Abstract: A computing system including a processing circuit in communication with a camera having a field of view. The processing circuit is configured to perform operations related to detecting, identifying, and retrieving objects disposed amongst a plurality of objects. The processing circuit may be configured to perform operations related to object recognition template generation, feature generation, hypothesis generation, hypothesis refinement, and hypothesis validation.

Abstract: A computing system including a processing circuit in communication with a camera having a field of view. The processing circuit is configured to perform operations related to detecting, identifying, and retrieving objects disposed amongst a plurality of objects. The processing circuit may be configured to perform operations related to object recognition template generation, feature generation, hypothesis generation, hypothesis refinement, and hypothesis validation.

Abstract: A computing system including a processing circuit in communication with a camera having a field of view. The processing circuit is configured to perform operations related to detecting, identifying, and retrieving objects disposed amongst a plurality of objects. The processing circuit may be configured to perform operations related to object recognition template generation, feature generation, hypothesis generation, hypothesis refinement, and hypothesis validation.

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.

Abstract: A system and method for performing automatic camera calibration is provided. The system receives a calibration image, and determines a plurality of image coordinates for representing respective locations at which a plurality of pattern elements of a calibration pattern appear in a calibration image. The system determines, based on the plurality of image coordinates and defined pattern element coordinates, an estimate for a first lens distortion parameter of a set of lens distortion parameters, wherein the estimate for the first lens distortion parameter is determined while estimating a second lens distortion parameter of the set of lens distortion parameters to be zero, or is determined without estimating the second lens distortion parameter. The system determines, after the estimate of the first lens distortion parameter is determined, an estimate for the second lens distortion parameter based on the estimate for the first lens distortion parameter.

Abstract: A system and method for operating a robotic system to scan and register unrecognized objects is disclosed. The robotic system may use an image data representative of an unrecognized object located at a start location to implement operations for transferring the unrecognized object from the start location. While implementing the operations, the robotic system may obtain additional data, including scanning results of one or more portions of the unrecognized object not included in the image data. The robotic system may use the additional data to register the unrecognized object.

Abstract: A system and method for performing automatic camera calibration is provided. The system receives a calibration image, and determines a plurality of image coordinates for representing respective locations at which a plurality of pattern elements of a calibration pattern appear in a calibration image. The system determines, based on the plurality of image coordinates and defined pattern element coordinates, an estimate for a first lens distortion parameter of a set of lens distortion parameters, wherein the estimate for the first lens distortion parameter is determined while estimating a second lens distortion parameter of the set of lens distortion parameters to be zero, or is determined without estimating the second lens distortion parameter. The system determines, after the estimate of the first lens distortion parameter is determined, an estimate for the second lens distortion parameter based on the estimate for the first lens distortion parameter.

Abstract: A system and method for operating a robotic system to scan and register unrecognized objects is disclosed. The robotic system may use an image data representative of an unrecognized object located at a start location to implement operations for transferring the unrecognized object from the start location. While implementing the operations, the robotic system may obtain additional data, including scanning results of one or more portions of the unrecognized object not included in the image data. The robotic system may use the additional data to register the unrecognized object.

Abstract: A method and computing system for transferring objects between a source repository and a destination repository is provided. The computing system is configured to operate by a combination of pre-planned and image base trajectories to improve speed and reliability of object transfer. The computing system is configured to capture image information of repositories and use the captured information to alter or adjust pre-planned trajectories to improve performance.

Abstract: A system and method of detecting objects are provided. The method includes generating first edge information from first image data representing an object based on a first mode of image capture, generating second edge information from second image data representing the object based on a second mode of image capture, the second mode being different from the first mode, fusing the first edge information with the second edge information to generate fused edge information, generating an object detection hypothesis based on the fused edge information, and validating the object detection hypothesis based on the fused edge information, the first edge information, and/or the second edge information.

Abstract: A robot control system and a method for automatic camera calibration is presented. The robot control system includes a control circuit configured to determine all corner locations of an imaginary cube that fits within a camera field of view, and determine a plurality of locations that are distributed on or throughout the imaginary cube. The control circuit is further configured to control a robot arm to move a calibration pattern to the plurality of locations, and to receive a plurality of calibration images corresponding to the plurality of locations, and to determine respective estimates of intrinsic camera parameters based on the plurality of calibration images, and to determine an estimate of a transformation function that describes a relationship between a camera coordinate system and a world coordinate system. The control circuit is further configured to control placement of the robot arm based on the estimate of the transformation function.