A system comprises a first robotic arm adapted to support and move a tool and a second robotic arm adapted to support and move a camera. The system also comprises an input device, a display, and a processor. The processor is configured to, in a first mode, command the first robotic arm to move the camera in response to a first input received from the input device to capture an image of the tool and present the image as a displayed image on the display. The processor is configured to, in a second mode, display a synthetic image of the first robotic arm in a boundary area around the captured image on the display, and in response to a second input, change a size of the boundary area relative a size of the displayed image.

A robot system for picking randomly shaped and sized object from a continuously moving stream of objects in bulk, e.g. a 3D bulk, and placing the object singulated and aligned on an induction or directly on a sorter. A pick and place robot has a robotic actuator for moving a gripper with a controllable gripping configuration of its gripping members, e.g. four suction cups, to adapt the gripper for various objects. A control system processes a 3D image of objects upstream of a position of the pick and place robot, identifies separate objects in the 3D image, and selects which object to grip, based on parameters of the identified separate objects determined from the 3D image. Based on e.g. size and shape of the selected object to grip, the gripping configuration of the gripper is adjusted to match the surface of the object to grip for optimal gripping. The robotic actuator, e.g. a gantry type robotic actuator, is then controlled to move the gripper to a position for gripping the object, and afterwards move the gripper with the gripped object to a target position and with a target orientation to release grip of the object and thus place the object on an induction or directly on a sorter. An image after placing the object along with properties of the object determined from the 3D image can be used as input to a machine learning for online improving pick and place performance of the robot system, e.g. for online improving the algorithm for selection of which object to pick, and also for selection of the appropriate gripping configuration to match the object.

A vision system and control system for a robotic pack station is disclosed. Robotic pack stations typically include a work cell, which enables the transfer of items from a tote or a bin to a container. The work cell may include one or more of the following: a robotic arm, a vision system, a control system, a conveyor, and a pack platform. The vision system and control system of the present invention identify items and provide instructions to the robotic arm to pick and/or place items in a bin or a tote.

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.

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.

A pick and place system comprises a computer connected to receive images of a field of view of a bin or other location at which objects are placed from disparate viewpoints. The computer is configured to process 2D image data of one or more of the images to determine a coarse pose and search range corresponding to the object. The computer is configured to perform subsequent stereo matching within the search range to obtain an accurate pose of the object. The computer is connected to control a robot to pick and place a selected object. Poses of objects may be determined asynchronously with picking the objects. Poses of plural objects may be determined and saved. the images may be processed to detect changes in the field of view. Saved poses for objects unaffected by changes may be used to pick the corresponding objects.

A control apparatus for a robot including a three-dimensional sensor includes an operation controller that controls the robot to shift a measurement range of the three-dimensional sensor in a scan area, and a map obtainer that updates map information based on a result of measurement performed by the three-dimensional sensor. The map information indicates a scan status at each of a plurality of points in the scan area. The operation controller performs first scanning in which the measurement range of the three-dimensional sensor is shifted to update map information about a local range in the scan area, and performs second scanning in which the measurement range of the three-dimensional sensor is shifted away from the local range to update map information about a range different from the local range for which the first scanning is performed to update map information.

The present invention relates to safety in a dynamic 3D healthcare environment. The invention in particular relates to a medical safety-system for dynamic 3D healthcare environments, a medical examination system with motorized equipment, an image acquisition arrangement, and a method for providing safe movements in dynamic 3D healthcare environments. In order to provide improved safety in dynamic 3D healthcare environments with a facilitated adaptability, a medical safety-system (10) for dynamic 3D healthcare environments is provided, comprising a detection system (12), a processing unit (14), and an interface unit (16). The detection system comprises at least one sensor arrangement (18) adapted to provide depth information of at least a part of an observed scene (22). The processing unit comprises a correlation unit (24) adapted to correlate the depth information. The processing unit comprises a generation unit (26) adapted to generate a 3D free space model (32). The interface unit is adapted to provide the 3D free space model.

An information processor calculates, for a robot hand including a plurality of fingers, a gripping pose at which the robot hand grips a target object. The information processor includes a candidate single-finger placement position detector that detects, based on three-dimensional measurement data obtained through three-dimensional measurement of the target object and hand shape data about a shape of the robot hand, candidate placement positions for each of the plurality of fingers of the robot hand, a multi-finger combination searcher that searches for, among the candidate placement positions for each of the plurality of fingers, a combination of candidate placement positions to allow gripping of the target object, and a gripping pose calculator that calculates, based on the combination of candidate placement positions for each of the plurality of fingers, a gripping pose at which the robot hand grips the target object.

Embodiments provide a system suitable for handling and correcting elastic materials and a method thereof. In the embodiments, a system for handling and correcting elastic materials includes a workbench, and also includes: an image recognition device, a control unit, a motion robot and a correction device. The present disclosure is intended to provide a system for handling and correcting elastic materials and a method thereof, relying on automatic equipment to perform correction operations, with high degree of automation and precise control.