A method and system for picking articles from a collection of articles and arranging articles into placement locations, includes capturing an image with a first vision system from a collection of articles at a first pick location and determining coordinate data for at least some of the articles in the collection of articles. The coordinate data for an article in the collection of articles is provided to a first robotic manipulator. That article is picked from the collection of articles with the first robotic manipulator according to the coordinate data for that article and that article placed at a first place location. The position and orientation data of that article are obtained at a second pick location and provided along with a desired position and orientation of that article at a second place location to a second robotic manipulator. That article is picked with the second robotic manipulator using the position and orientation data of that article at the second pick location and that article is placed at the second place location at the desired position and orientation.

A remote controlled, tele-operated welder includes a multi-axis robot arm, video cameras, sensors a specialized control station that allows an operator to perform flood-fill welding operations at a remote location to avoid the heat, smoke and other environmental effects produced through typical flood-welding operations. The operator accesses the control unit (OCU) using a GUI and mouse, keyboard, joystick, or other custom controls, and observe the piece via the cameras (visual, thermal, or other) placed in the welding station via a feed displayed on the OCU display(s). Audio, video, and/or tactile feedback may be provided to indicate arm, welder, or other system status, for collision warning and arm motion singularity avoidance. Augmented reality informational graphic/textual overlays may provide guidance to an operator, and the apparatus may further include the ability to repeat series of steps needed to handle flood-weld on a given piece, repeatedly across many pieces.

A method for operating an automated food making apparatus having a motor, actuator arm, and an apparatus. The apparatus may be a paddle with flexible fins. The method rotates the paddle with a pin-shaft mechanism to dispense an ingredient placed in a canister, controls the motor automatically based on weight sensor readings, and locates a position of the actuator arm with position sensors. The same motor dispenses ingredients from a plurality of canisters. The method may have a plurality of paddle rotation and weight measurement steps until a target weight is reached. The plurality of paddle rotation steps may be unidirectional or bidirectional paddle rotation. The paddle may be rotated according to one or more paddle rotation algorithms, an error recovery algorithm, or different algorithms based on the amounts of ingredients remaining in the canister. The paddle may be rocked until the target weight is achieved.

An automated food making apparatus is described. An automated food making apparatus can include: a carousel; a dispensing apparatus shared among a plurality of canisters on the carousel, wherein at least one canister includes a paddle; and wherein the dispensing apparatus is configured to rotate the canister's paddle to dispense ingredients stored in the canister. A dispensing mechanism for an automated food making apparatus can include: an actuator arm; a motor that is adapted to rotate the actuator arm; one or more magnets embedded in the actuator arm; and one or more sensors configured to detect position of the actuator arm; wherein the actuator arm dispenses ingredients by rotating a pin located on a canister.

A machine which repetitively performs an operation, or operations, on mass-produced parts which are subject to part-to-part variations compensates for such variations by self-adjustment of its operation, or operations, at a location, or locations, where an operation, or operations, is, or are, performed.

A machine which repetitively performs an operation, or operations, on mass-produced parts which are subject to part-to-part variations compensates for such variations by self-adjustment of its operation, or operations, at a location, or locations, where an operation, or operations, is, or are, performed.

A method for operating an automated food making apparatus having a motor, actuator arm, and an apparatus. The apparatus may be a paddle with flexible fins. The method rotates the paddle with a pin-shaft mechanism to dispense an ingredient placed in a canister, controls the motor automatically based on weight sensor readings, and locates a position of the actuator arm with position sensors. The same motor dispenses ingredients from a plurality of canisters. The method may have a plurality of paddle rotation and weight measurement steps until a target weight is reached. The plurality of paddle rotation steps may be unidirectional or bidirectional paddle rotation. The paddle may be rotated according to one or more paddle rotation algorithms, an error recovery algorithm, or different algorithms based on the amounts of ingredients remaining in the canister. The paddle may be rocked until the target weight is achieved.

Provided is a robot center-of-gravity display device including: a specification setting unit that sets specifications including the weights, center-of-gravity positions, and dimensions of components of respective shafts; a posture setting unit that sets position information of the respective shafts; a robot-image generating unit that generates a three-dimensional model image of the robot in a state where the respective shafts are located at the positions indicated by the position information, based on the set position information of the respective shafts and the specifications of the components; a center-of-gravity-position calculation unit that calculates the center-of-gravity position of the overall robot, based on the set position information of the respective shafts and the specifications of the components; an image combining unit that superimposes an indication showing the center of gravity of the overall robot on the three-dimensional model image at the calculated center-of-gravity position; and a display unit that displays the generated image.

An adaptive learning interface system for end-users for controlling one or more machines or robots to perform a given task, combining identification of gaze patterns, EEG channel's signal patterns, voice commands and/or touch commands. The output streams of these sensors are analysed by the processing unit in order to detect one or more patterns that are translated into one or more commands to the robot, to the processing unit or to other devices. A pattern learning mechanism is implemented by keeping immediate history of outputs collected from those sensors, analysing their individual behaviour and analysing time correlation between patterns recognized from each of the sensors. Prediction of patterns or combination of patterns is enabled by analysing partial history of sensors' outputs. A method for defining a common coordinate system between robots and sensors in a given environment, and therefore dynamically calibrating these sensors and devices, is used to share characteristics and positions of each object detected on the scene.

A method for controlling a manipulator, with the method being particularly suitable for the respecting of predetermined monitoring limits. The method operates by initiating a halting movement or a speed capping based on an identified actual override trend, and is thus suitable, in particular, for path movements by means of spline interpolation.