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 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: Systems and methods for classifying at least a portion of an image as being textured or textureless are presented. The system receives an image generated by an image capture device, wherein the image represents one or more objects in a field of view of the image capture device. The system generates one or more bitmaps based on at least one image portion of the image. The one or more bitmaps describe whether one or more features for feature detection are present in the at least one image portion, or describe whether one or more visual features for feature detection are present in the at least one image portion, or describe whether there is variation in intensity across the at least one image portion. The system determines whether to classify the at least one image portion as textured or textureless based on the one or more bitmaps.

Abstract: A computing system including a processing circuit in communication with a camera having a field of view, The processing circuit obtains image information based on the objects in the field of view and defines a minimum viable region for a target open corner. Potential minimum viable regions are defined by identifying candidate edges of an object and determining potential intersection points based on the candidate edges. The minimum viable region may then be identified and validated from the potential minimum viable regions.

Abstract: Systems and methods for object detection and robotic control or pickup of the detected objects are provided. Systems and methods described herein provide for the determination and adjustment of minimum viable regions on a surface of an object for robotic pickup. Determination of a minimum viable region may increase the accuracy and efficiency of robotic object handling. The minimum viable region may be used to select grasping areas for a movement operation configured to provide supplemental image information for estimating dimensions of a target object.

Abstract: A computing system including a communication interface and a processing circuit. The communication interface communicates with a robot and a camera having a field of view. The processing circuit performs obtaining image information based on objects within the field of view and determines a first template matching score which indicates a degree of match between the image information and an model template. The processing circuit further determines image edge information based on the image information and determines a second template matching score which indicates a degree of match between the image edge information and a template. The processing circuit additional determines an overall template matching score based on the first template matching score and the second template matching score.

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 processing candidate edges are presented. The method may be performed when spatial structure information and 2D image information are stored. The method may include identifying, based on the spatial structure information, a 3D location that represents a corner of an object structure; identifying, based on the spatial structure information, a 3D vector that extends from the 3D location and is parallel with an edge; determining a 2D location within the 2D image information that corresponds to the 3D location; determining a 2D vector within the 2D image information that corresponds to the 3D vector; determining an edge detection region; identifying a cluster of candidate edges within the edge detection region that does not represent any object edge; identifying, as a 2D object edge, a candidate edge that is not part of the identified cluster; and performing segmentation based on the 2D object edge.

Abstract: A system and method for operating a transfer robot and a multi-surface gripper to grasp and transfer objects is disclosed.

Abstract: The present disclosure relates to verifying an initial object estimation of an object. A two-dimensional (2D) image representative of an environment including one or more objects may be obtained. The 2D image may be inspected to detect edges of an object. The edges may be processed to verify or update an initial object estimation to increase the accuracy of an object detection result.

Abstract: A method performed by a computing system is presented. The method may include the computing system receiving image information that represents an object surface associated with a flexible object, and identifying, as a grip region, a surface region of the object surface that satisfies a defined smoothness condition and has a region size that is larger than or equal to a defined region size threshold, wherein the grip region is identified based on the image information. The method may further include identifying, as a safety region, a three-dimensional (3D) region which surrounds the grip region in one or more horizontal dimensions, and which extends from the grip region along a vertical dimension that is perpendicular to the one or more horizontal dimensions. The method may further include performing robot motion planning based on the grip region and the safety region.

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 method and computing system for performing the method are presented. The method may include receiving image information representing an object; identifying a set of one or more matching object recognition templates associated with a set of one or more detection hypotheses. The method may further include selecting a primary detection hypothesis associated with a matching object recognition template; generating a primary candidate region based on the matching object recognition template; determining at least one of: (i) whether the set of one or more matching object recognition templates has a subset of one or more remaining matching templates, or (ii) whether the image information has a portion representing an unmatched region; and generating a safety volume list based on at least one of: (i) the unmatched region, or (ii) one or more additional candidate regions that are generated based on the subset of one or more remaining matching templates.

Abstract: A system and method for processing candidate edges are presented. The method may be performed when spatial structure information and 2D image information are stored. The method may include identifying, based on the spatial structure information, a 3D location that represents a corner of an object structure; identifying, based on the spatial structure information, a 3D vector that extends from the 3D location and is parallel with an edge; determining a 2D location within the 2D image information that corresponds to the 3D location; determining a 2D vector within the 2D image information that corresponds to the 3D vector; determining an edge detection region; identifying a cluster of candidate edges within the edge detection region that does not represent any object edge; identifying, as a 2D object edge, a candidate edge that is not part of the identified cluster; and performing segmentation based on the 2D object edge.

Abstract: The present disclosure relates to verifying an initial object estimation of an object. A two-dimensional (2D) image representative of an environment including one or more objects may be obtained. The 2D image may be inspected to detect edges of an object. The edges may be processed to verify or update an initial object estimation to increase the accuracy of an object detection result.

Abstract: A method for operating a robotic system includes obtaining and processing first data representative of an object at a start location. An event may be detected while implementing an operation based on the image data. A gripper height that corresponds to the event may be determined. Accordingly, the method may include calculating an object height that represents a height estimate of the object.

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: 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 method and computing system for facilitating edge detection are presented. The computing system may include at least one processing circuit configured to receive image information representing a group of objects in a camera field of view, and to identify, from the image information, a plurality of candidate edges associated with the group of objects. The at least one processing circuit may further determine, when the plurality of candidate edges include a first candidate edge which is formed based on a border between a first image region and a second image region, whether the image information satisfies a defined darkness condition at the first candidate edge. The at least one processing circuit may further select a subset of the plurality of candidate edges to form a selected subset of candidate edges for representing the physical edges of the group of objects.

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 at a start location. 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.