One aspect of the present disclosure relates to a generation method for a training dataset, comprising: capturing, by one or more processors, a target object to which a marker unit recognizable under a first illumination condition is provided; and acquiring, by the one or more processors, a first image where the marker unit is recognizable and a second image obtained by capturing the target object under a second illumination condition.

A user can easily create a robot program. A measuring device includes a position determination processing part that determines a holding position, held by a robot hand, of a workpiece placed in a work space and determines coordinates of a fixed via point having any single attribute based on a result of measurement made by a measuring part and holding information, the fixed via point being one of an approach position of the robot hand for holding the holding position, the holding position, and a retreat position after holding, and an output part that outputs, to a robot controller, the coordinates of the fixed via point determined by the position determination processing part and attribute information showing the attribute of the fixed via point.

A computing system and a method for calibration verification is presented. The computing system is configured to perform a first calibration operation, and to control a robot arm to move a verification symbol to a reference location. The robot control system further receives, from a camera, a reference image of the verification symbol, and determines a reference image coordinate for the verification symbol. The robot control system further controls the robot arm to move the verification symbol to the reference location again during an idle period, receives an additional image of the verification symbol, and determines a verification image coordinate. The robot control system determines a deviation parameter value based the reference image coordinate and the verification image coordinate, and whether the deviation parameter value exceeds a defined threshold, and performs a second calibration operation if the threshold is exceeded.

The system can include: a container 110, a set of sensors 120, and a controller 130. The system can optionally include a robot 140. However, the system 100 can additionally or alternatively include any other suitable set of components. The system functions to monitor and/or maintain a fullness level of a container. The system can additionally or alternatively function to enable robotic picking out of the container (e.g., in a pick-and-place setting). The system can additionally function to maintain candidate objects within reach of the robot's end effector to increase robot uptime while minimizing the extent of the robot's required motion (e.g., in the z-axis).

The image processing device according to the invention includes: a first acquisition unit to acquire a captured image; a display control unit to display a setting screen to allow to user to set an image processing area, which is an area where predetermine image processing is performed, in the image acquired by the first acquisition unit on a display device; and a second acquisition unit configured to acquire movable range information indicating a movable range of a working device, operations of which are controlled on the basis of a result of the predetermined image processing. The display control unit controls the display of the setting screen so as to cause the user to identify a range in which the working device is not able to operate in the image, on the basis of the movable range information acquired by the second acquisition unit.

An apparatus for guiding an autonomous vehicle towards a docking station including an autonomous vehicle with a camera-based sensing system, a drive system for driving the autonomous vehicle, and a control system for controlling the drive system. The apparatus includes a docking station including a first fiducial marker and a second fiducial marker, wherein the second fiducial marker is positioned on the docking station to define a predetermined relative spacing with the first fiducial marker, wherein the control system is operable to receive an image provided by the camera-based sensing system, the image including a representation of the first and second fiducial markers, and to control the drive system so as to guide the autonomous vehicle towards the base station based on a difference between the representation of the first and second fiducial markers in the received image and the predetermined relative spacing between the first and second fiducial markers.

A machining system having plural machining devices installed at plural points in a robot arm. the machining system carrying out machining to a processed object made of metal be by using these machining devices, the machining system further having a control device that controls drive of the machining devices so as to offset processing reaction forces by at least one of a thrust force and a torque to be obtained when the machining devices carry out machining to the processed object simultaneously between the machining devices.

A method and a device for operating a robot are provided. According to an example of the method, information of a first gesture is acquired from a group of gestures of an operator, each gesture from the group of gestures corresponding to an operation instruction from a group of operation instructions. A first operation instruction from the group of operation instructions is obtained based on the acquired information of the first gesture, the first operation corresponding to the first gesture. The first operation instruction is executed.

Systems and methods are provided for placing non-destructive marks onto a part via an end effector of a robot. One embodiment is a system comprising an end effector of a robot. The end effector includes an extendable punch that places targets onto a part, and supports that hold a strip of reflective adhesive tape between the punch and the part. Extending the punch cuts out a target from the strip and applies an adhesive side of the target to the part, and retracting the punch leaves a reflective side of the target visible on the part.

One variation of a method for automatically generating a planogram for a store includes: dispatching a robotic system to autonomously navigate within the store during a mapping routine; accessing a floor map of the floor space generated by the robotic system from map data collected during the mapping routine; identifying a shelving structure within the map of the floor space; defining a first set of waypoints along an aisle facing the shelving structure; dispatching the robotic system to navigate to and to capture optical data at the set of waypoints during an imaging routine; receiving a set of images generated from optical data recorded by the robotic system during the imaging routine; identifying products and positions of products in the set of images; and generating a planogram of the shelving segment based on products and positions of products identified in the set of images.