In one embodiment, a system for inspecting an object comprises a first camera for inspecting a first surface of the object, and a second camera for inspecting a second surface of the object. The object may be placed upon a support structure during simultaneous inspection by the first camera and the second camera. At least one roller is arranged to selectively engage the object when the object is placed upon the support structure, wherein the at least one roller is adapted for circumferential rotation relative to the support structure. Rotation of the at least one roller causes a corresponding circumferential rotation of the object relative to the first and second cameras.

According to an embodiment, there is provided a handling system capable of handling a plurality of objects, the handling system including: a movable arm, a holder, a sensor, and a controller. The holder is attached to the movable arm and is capable of holding the object. The sensor is capable of detecting the object. The controller controls the movable arm and the holder. The controller determines whether or not to change an arrangement of the object before the object is held, on the basis of information acquired from the sensor. In a case where it is determined to change the arrangement of the object, the controller evaluates effectiveness of an arrangement change operation for each object, and decides on an arrangement change operation on the basis of an evaluation result.

A system and method identifying an object, such as a transparent object, to be picked up by a robot from a bin of objects. The method includes obtaining a 2D red-green-blue (RGB) color image and a 2D depth map image of the objects using a 3D camera, where pixels in the depth map image are assigned a value identifying the distance from the camera to the objects. The method generates a segmentation image of the objects using a deep learning mask R-CNN (convolutional neural network) that performs an image segmentation process that extracts features from the RGB image and assigns a label to the pixels so that objects in the segmentation image have the same label. The method then identifies a location for picking up the object using the segmentation image and the depth map image.

An example computer-implemented method includes receiving, from one or more vision components in an environment, vision data that captures features of the environment, including object features of an object that is located in the environment, and prior to a robot manipulating the object: (i) determining based on the vision data, at least one first adjustment to a programmed trajectory of movement of the robot operating in the environment to perform a task of transporting the object, and (ii) determining based on the object features of the object, at least one second adjustment to the programmed trajectory of movement of the robot operating in the environment to perform the task, and causing the robot to perform the task, in accordance with the at least one first adjustment and the at least one second adjustment to the programmed trajectory of movement of the robot.

A robot arm control device according to the present disclosure comprises a workpiece selecting section that selects a target workpiece, which is a workpiece to be picked up and placed, among a plurality of workpieces conveyed by a conveyor system in a predetermined flow direction; and a motion control section that controls a motion of the robot arm to pick up the target workpiece at a predetermined pick up position and place the target workpiece at the target placement position selected among a plurality of predetermined placement positions, wherein the workpiece selecting section selects, among the workpieces that are candidates for selection, the workpiece that has a shortest distance from the distal end position at a task-start timing to the workpiece position at the task-start timing as the target workpiece.

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.

According to one embodiment, an object handling device causes a hand to grasp, convey, and place an object in a container. The object handling device includes one or more processors configured to calculate an expanded interference region by combining an interference region of the hand interfering with another object and an interference region of the grasped object interfering with the another object; calculate at least a placement position between the placement position and a placement posture of the object in the container in accordance with information on an obstacle in the container and the expanded interference region; and calculate a release position at which the hand releases the object, on the basis of the placement position of the object.

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.

A robotic system is disclosed that include an articulated arm and a first perception system for inspecting an object, as well as a plurality of additional perception systems, each of which is arranged to be directed toward a common area in which an object may be positioned by the robotic arm such that a plurality of views within the common area may be obtained by the plurality of additional perception systems.

The present application discloses a robotic control system, and a method and a computer system for controlling a robot. The robotic control system includes a memory and one or more processors coupled to the memory. The memory is configured to store configured to store a model of a robot having a plurality of axes of control including at least a linear axis and one or more rotational axes. The one or more processors are configured to use the model to control the robot to perform a task, including by sending to the robot a set of control signals to cause the robot to move with respect to two or more of said axes of control including at least the linear axis.