A work coordinate generation device includes a shape register section configured to register shape information about a shape of a work region optically defined on a target which is a work target of a work robot; a first recognition section configured to acquire first image data; a first coordinate generation section configured to generate a first work coordinate which represents the work region of the first target based on a result of recognition of the first recognition section; a second recognition section configured to acquire second image data; and a second coordinate generation section configured to generate a second work coordinate which represents the work region of the second target based on the first work coordinate and a result of recognition of the second recognition section.

A processing apparatus 1 includes: a workpiece-set-position recognition unit 114 that moves an arm distal-end portion to a specified position measurement point to measure a shape of a workpiece in a workpiece set state in which the workpiece is positioned by a workpiece positioning unit, and thereby recognizes a set position of the workpiece; a processing-point-information generation unit 115 that, based on the set position of the workpiece and processing-target-portion information 124 indicating a position of a target portion of the workpiece for specified processing, generates processing-point information 125 indicating a processing point which is a movement point of the arm distal-end portion to perform the specified processing on the workpiece using a processing tool in the workpiece set state; and a workpiece-processing control unit 116 that moves the arm distal-end portion to the processing point based on the processing-point information 125 to perform the specified processing on the workpiece using the processing tool.

Systems, computer program products, and methods for constructing models and simulations of real-world environments are described. A robot employs various sensors to collect data from its environment and provides this data to a tele-operation system. Any number of tele-artists may access the tele-operation system and use the robot sensor data to collaboratively construct a simulated scene representative of the robot's environment. The tele-artists may continue to update the simulation in real-time as the robot explores its environment and provides more sensor data. The robot may use the simulation in support of fundamental operations through its cognitive architecture, such as action planning and hypothesis generation.

An artificial intelligence controller of the robot may monitor the adaptations made to the simulation by the tele-artists in response to the sensor data in order to learn (e.g., via reinforcement learning) how to autonomously generate and update its own simulation based on its own sensor data.

A machine vision-based method and system for measuring 3D pose of a part or subassembly of parts having an unknown pose are disclosed. A number of different applications of the method and system are disclosed including applications which utilize a reprogrammable industrial automation machine such as a robot. The method includes providing a reference cloud of 3D voxels which represent a reference surface of a reference part or subassembly having a known reference pose. Using at least one 2D/3D hybrid sensor, a sample cloud of 3D voxels which represent a corresponding surface of a sample part or subassembly of the same type as the reference part or subassembly is acquired. The sample part or subassembly has an actual pose different from the reference pose. The voxels of the sample and reference clouds are processed utilizing a matching algorithm to determine the pose of the sample part or subassembly.

A method performed by a robotic system, for identifying single objects from a random assortment of objects. The robotic system picks, among a random assortment of objects on a presentation surface, an object from the presentation surface at a determined picking point. The robotic system removes any remaining objects from the presentation surface. The robotic system places the picked object on the presentation surface. The robotic system further analyzes the picked object on the presentation surface, in order to identify a single object.

The easy and quick detection of a contour shape of an object from three dimensional point group data, and control a robotic arm and a tool using it. An information processing method comprising: a step of acquiring three-dimensional point group data by a sensor from an object, a step of specifying a contour point group data that constitutes a contour of the object from the three-dimensional point group data, a step of acquiring tool control information including tool position information and tool posture information for specifying a tool trajectory of the tool connected to the arm of the working robot from the contour point group data, and a step of controlling the tool based on the tool control information.

A method for grasping texture-less metal parts based on BOLD image matching comprises: obtaining a real image and CAD template images by photographing, extracting a foreground part of the input part image, calculating a covariance matrix of a foreground image, establishing the direction of a temporary coordinate system, and setting directions of line segments to point to a first or second quadrant of the temporary coordinate system; constructing a descriptor of each line segment according to an angle relation between the line segment and k nearest line segments, and matching the descriptors of different line segments in the real image and the CAD template images to obtain line segment pairs; and recognizing a processed pose through a PNL algorithm to obtain a pose of a real texture-less metal part, and then inputting the pose of the real texture-less metal part to a mechanical arm to grasp the part. The present invention can correctly match line segments, obtain an accurate pose of the part by calculation, successfully grasp the part, and satisfy actual application requirements.

A work robot sequentially holds multiple workpieces supplied to a supply area and moves the held workpieces to a work area. The work robot includes an image-capturing device configured to capture images of the multiple workpieces supplied to the supply area in random orientations and positions, an image processing device configured to recognize multiple workpiece regions from the images captured by the image-capturing device, obtain an area and a position of each of the recognized multiple workpiece regions, and obtain a distance between each workpiece region and the work area or the work robot, and a control device configured to determine a holding order of the workpiece based on the areas of the multiple workpiece regions and the distance between each workpiece region and the work area or the work robot as obtained by the image processing device.

In one embodiment, a method includes generating a trajectory plan to complete a task to be executed by a robotic system, identifying objects in the environment required for completing the task, determining attributes for each of the identified objects, determining trajectory-parameters for the trajectory plan based on the determined attributes for each identified object and operational conditions in an environment associated with the robotic system, and executing the task based on the determined trajectory-parameters for the trajectory plan.

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.