A computer-implemented method executed by data processing hardware of a robot causes the data processing hardware to receive sensor data associated with a door. The data processing hardware determines, using the sensor data, door properties of the door. The door properties can include a door width, a grasp search ray, a grasp type, a swing direction, or a door handedness. The data processing hardware generates a door movement operation based on the door properties. The data processing hardware can execute the door movement operation to move the door. The door movement operation can include pushing the door, pulling the door, hooking a frame of the door, or blocking the door. The data processing hardware can utilize the door movement operation to enable a robot to traverse a door without human intervention.

A picking facility is realized that can shorten the time required to transfer an article from a first support body to a second support body. Of a plurality of articles 50 supported by the first support body 51, the article 50 located at the highest position and the article 50 whose upper face T1 is present in a range of a set distance D downward from the upper face T1 of the article 50 located at the highest position are set as transfer-target articles 50A, and the control device performs a selection control to preferentially select, from the transfer-target articles 50A, a transfer-target article 50A in the normal orientation SC, and a transfer control to control the transfer device so as to transfer the transfer-target article 50A selected through the selection control from the first support body 51 to the second support body.

Systems and methods for performing a task in an operation environment of an aerial device with an autonomous or semi-autonomous robot are described. In some embodiments, a robot is disposed at an end of a boom of an aerial device. The robot may comprise cameras, actuators, sensors, processors, and manipulators that work together to perform tasks fully autonomously or semi-autonomously. Furthermore, the robot may comprise tools for performing the tasks and computer-executable instructions for performing the tasks may be based on the various sensory inputs, the tools, and the tasks to be performed.

Autonomous operations, such as robotic grasping and manipulation, in unknown or dynamic environments present various technical challenges. For example, three-dimensional (3D) reconstruction of a given object often focuses on the geometry of the object without considering how the 3D model of the object is used in solving or performing a robot operation task. As described herein, in accordance with various embodiments, models are generated of objects and/or physical environments based on tasks that autonomous machines perform with the objects or within the physical environments. Thus, in some cases, a given object or environment may be modeled differently depending on the task that is performed using the model. Further, portions of an object or environment may be modeled with varying resolutions depending on the task associated with the model.

Devices, systems, and methods for autonomously packing folded laundry articles into a container are described. A packing system includes a refillable cartridge, a queue conveyor having one or more folded laundry articles and stacks of folded laundry articles disposed thereon, at least one retractable conveyor loading end between the refillable cartridge and the queue conveyor for loading the folded laundry articles into the refillable cartridge, a driven lifter for selectively raising and lowering the into and out of the container, and a controller in operative configuration with processors and drives of all of the foregoing and one or more sensors detecting a fill height of the refillable cartridge. The refillable cartridge includes a removable receiving surface that moves from a closed position to an open position during loading of the folded laundry by the retractable conveyor and unloading of the folded laundry into the container.

The invention relates to a method for handling products (17) using an automation system and to an automation system (10), the products being captured by means of an imaging sensor (18) of a control device (12) of the automation system and being handled by means of a handling mechanism (13) of a handling device (11) of the automation system, the control device processing sensor image data from the imaging sensor and controlling the handling device as specified by training data sets contained in a data memory (21) of the control device, the training data sets comprising training image data and/or geometric data and control instructions associated therewith, the training data sets being generated, as a statistical model, exclusively from geometric data contained in the training image data of products, by means of a computer using a computer program product executed thereon, the training data sets being transmitted to the control device.

A robot system includes a robot, an image capture apparatus, an image processing portion, and a control portion. The image processing portion is configured to specify in an image of a plurality of objects captured by the image capture apparatus, at least one area in which a predetermined object having a predetermined posture exists, and obtain information on position and/or posture of the predetermined object in the area. The control portion is configured to control the robot, based on the information on position and/or posture of the predetermined object, for the robot to hold the predetermined object.

A method and system for programming picking and placing of a workpiece is provided. Embodiments may include associating a workpiece with an end effector that is attached to a robot and scanning the workpiece while the workpiece is associated with the end effector. Embodiments may also include determining a pose of the workpiece relative to the robot, based upon, at least in part, the scanning.

According to various embodiments of the present invention, an electronic device comprises: a memory including instructions and a training database, which includes data, on at least one object, acquired on the basis of an artificial intelligence algorithm; at least one sensor; and a processor connected to the at least one sensor and the memory, wherein the processor can be configured to execute the instructions in order to acquire data on a designated area including the at least one object by using the at least one sensor, identify location information and positioning information on the at least one object on the basis of the training database, and transmit a control signal for picking the at least one object to a picking tool related to the electronic device on the basis of the identified location information and positioning information.

A robot hand controller includes an air supply unit configured to supply air into fingers of a robot hand and configured to discharge air in the fingers, and a controller configured to control the air supply unit, where the air supply unit includes two or more air passages respectively connected to the different fingers, the air passages capable of supplying the air into the fingers and discharging the air in the fingers independently from each other, and the controller controls supply and discharge of the air through each of the two or more air passages in response to a shape of the workpiece and an object in a vicinity of a transport destination of the workpiece.