Abstract: A system and method for performing automatic camera calibration is presented. The system communicates with a first camera and a second camera, wherein a transparent platform is disposed between the two cameras. When a 3D calibration pattern is disposed on the platform, the system receives a first set of calibration images from the first camera, and a second set of calibration images from the second camera. The system determines, based on the first set of calibration images, a first set of coordinates for corners of the polyhedron. The system further determines, based on the second set of calibration images, a second set of coordinates for the corners. The system determines, based on the coordinates, a spatial relationship between the first camera and the second camera. The system further uses a description of the spatial relationship to generate a 3D model of an object other than the 3D calibration pattern.

Abstract: The present disclosure relates to detecting and registering unrecognized or unregistered objects. A minimum viable range (MVR) may be derived based on inspecting image data that represents objects. The MVR may be determined to be a certain MVR or an uncertain MVR according to one or more features represented in the image data. The MVR may be used to register corresponding objects according to the certain or uncertain determination.

Abstract: A system and method for performing object detection are presented. The system receives spatial structure information associated with an object which is or has been in a camera field of view of a spatial structure sensing camera. The spatial structure information is generated by the spatial structure sensing camera, and includes depth information for an environment in the camera field of view. The system determines a container pose based on the spatial structure information, wherein the container pose is for describing at least one of an orientation for the container or a depth value for at least a portion of the container. The system further determines an object pose based on the container pose, wherein the object pose is for describing at least one of an orientation for the object or a depth value for at least a portion of the object.

Abstract: A control apparatus includes a first information acquiring section that acquires three-dimensional information of a first region of surfaces of a plurality of objects, the information being obtained by imaging or scanning the plurality of objects from a first location; a second information acquiring section that acquires three-dimensional information of a second region of surfaces of the plurality of objects, the information being obtained by imaging or scanning the plurality of objects from a second location; and a combining section that generates information indicating three-dimensional shapes of at least a portion of the surfaces of the plurality of objects, based on the three-dimensional information of the first region acquired by the first information acquiring section and the three-dimensional information of the second region acquired by the second information acquiring section.

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 system and method for determining occlusion are presented. The system receives camera data generated by at least one camera, which includes a first camera having a first camera field of view. The camera data is generated when a stack having a plurality of objects is in the first camera field of view, and describes a stack structure formed from at least an object structure for a first object of the plurality of objects. The system identifies a target feature of or disposed on the object structure, and determines a 2D region that is co-planar with and surrounds the target feature. The system determines a 3D region defined by connecting a location of the first camera and the 2D region. The system determines, based on the camera data and the 3D region, a size of an occluding region, and determines a value of an object recognition confidence parameter.

Abstract: A method and computing system for performing object detection are presented. The computing system may be configured to: receive first image information that represents at least a first portion of an object structure of an object in a camera's field of view, wherein the first image information is associate with a first camera pose; generate or update, based on the first image information, sensed structure information representing the object structure; identify an object corner associated with the object structure; cause the robot arm to move the camera to a second camera pose in which the camera is pointed at the object corner; receive second image information associated with the second camera pose; update the sensed structure information based on the second image information; determine, based on the updated sensed structure information, an object type associated with the object; determine one or more robot interaction locations based on the object type.

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: 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 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 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: 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 control apparatus includes a first information acquiring section that acquires three-dimensional information of a first region of surfaces of a plurality of objects, the information being obtained by imaging or scanning the plurality of objects from a first location; a second information acquiring section that acquires three-dimensional information of a second region of surfaces of the plurality of objects, the information being obtained by imaging or scanning the plurality of objects from a second location; and a combining section that generates information indicating three-dimensional shapes of at least a portion of the surfaces of the plurality of objects, based on the three-dimensional information of the first region acquired by the first information acquiring section and the three-dimensional information of the second region acquired by the second information acquiring section.

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: Robotic systems with griping mechanisms, and related systems and methods are disclosed herein. In some embodiments, the robotic system includes a robotic arm and an end-of-arm tool coupled to the robotic arm. The end-of-arm tool can include a frame and an actuator system coupled to the frame. The end-of-arm tool can also include a first clamping component, a second clamping component, and a third clamping component each coupled to the frame. The third clamping component is positioned peripheral to the second clamping component with respect to the first clamping component and includes one or more extension portions extending toward the first clamping component. The actuator system can be coupled to the first, second, and/or third clamping components to move the first, second, and/or third clamping components along a transverse axis of the end-of-arm tool.

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: 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 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.