A system for controlled distribution of components, the system including a vibrating bowl provided with an enclosure having a wall extending right around an axis of revolution of the bowl and in which the components are placed in bulk, and an articulated gripping arm provided to distribute the components to the automatic assembly installation, the vibrating bowl including an ascending helical ramp extending along an internal face of the wall between a base and an upper edge of the vibrating bowl constituting an exit of the ramp, the components being able to travel along this ramp towards a supply platform, particularly a slide, on which at least one component is arranged in advance of its seizure by the articulated gripping arm, the supply platform being connected to the exit and extending above or in the enclosure of the vibrating bowl.

Various embodiments of the present technology generally relate to robotic devices and artificial intelligence. More specifically, some embodiments relate to a robotic device for picking items from a bin and perturbing items in a bin. In some implementations, the device may include one or more computer-vision systems. A computer-vision system, in accordance with the present technology, may use at least two two-dimensional images to generate three-dimensional (3D) information about the bin and items in the bin. Based on the 3D information, a strategy for picking up items from the bin is determined. When no strategies with high probability of success exist, the robotic device may perturb the contents of the bin to create new available pick-up points and re-attempt to pick up an item.

Various embodiments of the present technology generally relate to robotic devices and artificial intelligence. More specifically, some embodiments relate to a robotic device for picking items from a bin and perturbing items in a bin. The robotic device may include one or more picking elements and one or more perturbation elements for disturbing a present arrangement of items in the bin. In an exemplary embodiment, a perturbation element comprises a compressed air valve. In some implementations, the robotic device may also include one or more computer-vision systems. Based on image data from the one or more computer-vision systems, a strategy for picking up items from the bin is determined. When no strategies with high probability of success exist, the robotic device may perturb the contents of the bin to create new available pick-up points.

A robotic device includes an end effector device, a first sensor, and a controller. The end effector device includes two fingers for gripping a workpiece. The first sensor detects a pressure distribution on a gripping position on the workpiece by the two fingers. The controller performs, based on a temporal variation in the pressure distribution when the workpiece is lifted, posture control including rotation of the end effector device.

Various embodiments of the present technology generally relate to robotic devices and artificial intelligence. More specifically, some embodiments relate to a robotic device for picking items from a bin and perturbing items in a bin. The robotic device may include one or more picking elements and one or more perturbation elements for disturbing a present arrangement of items in the bin. In an exemplary embodiment, a perturbation element comprises a compressed air valve. In some implementations, the robotic device may also include one or more computer-vision systems. Based on image data from the one or more computer-vision systems, a strategy for picking up items from the bin is determined. When no strategies with high probability of success exist, the robotic device may perturb the contents of the bin to create new available pick-up points.

The present disclosure relates to a material handling system for manipulating items. The material handling system includes a repositioning system comprising a robotic tool which includes a robotic arm portion and an end effector. The robotic tool is configured to manipulate an item in a first orientation and reorient the item to a second orientation. The material handling system further includes a vision system having one or more sensors positioned within the material handling system. The vision system is configured to generate inputs corresponding to the characteristics of the items. The material handling system may further include a controller executing instructions to cause the material handling system to identify the item in the first orientation, based on the one or more characteristics of the item, initiate, by the repositioning system, picking of the item in the first orientation, and re-orient the item in the second orientation.

Article takeout apparatus and article takeout method capable of eliminating unnecessary measurements. The article takeout apparatus includes a sensor, a position/posture detector to detect a position/posture of an article in a working area, a robot configured to take out the article, a data storage to store evaluation data to evaluate a plurality of sensor measurement positions corresponding to respective positions at which the sensor measures a plurality of measurement areas, a data update section to update the evaluation data after the measurement area is measured by the sensor and after the article is taken out by the robot, an evaluation value calculator to calculate a comprehensive evaluation value of the working area on the basis of the updated evaluation data, and a sensor position selector to select a next sensor measurement position from among the plurality of sensor measurement positions on the basis of the calculated comprehensive evaluation value.

According to one embodiment, a transporter includes a holder, a moving mechanism, a sensor, an operation controller, and a parameter estimator. The holder is configured to hold an object. The moving mechanism is configured to move the holder. The sensor is provided at the holder or the moving mechanism. The operation controller is configured to execute a test operation of moving the holder in a state in which the object is held by the holder. The parameter estimator is configured to estimate at least one parameter relating to the object based on a result of detection acquired by the sensor during the test operation.

Various embodiments of the present technology generally relate to robotic devices and artificial intelligence. More specifically, some embodiments relate to a robotic device for picking items from a bin and perturbing items in a bin. The robotic device may include one or more picking elements and one or more perturbation elements for disturbing a present arrangement of items in the bin. In an exemplary embodiment, a perturbation element comprises a compressed air valve. In some implementations, the robotic device may also include one or more computer-vision systems. Based on image data from the one or more computer-vision systems, a strategy for picking up items from the bin is determined. When no strategies with high probability of success exist, the robotic device may perturb the contents of the bin to create new available pick-up points.

A system for controlled distribution of components, the system including a vibrating bowl provided with an enclosure having a wall extending right around an axis of revolution of the bowl and in which the components are placed in bulk, and an articulated gripping arm provided to distribute the components to the automatic assembly installation, the vibrating bowl including an ascending helical ramp extending along an internal face of the wall between a base and an upper edge of the vibrating bowl constituting an exit of the ramp, the components being able to travel along this ramp towards a supply platform, particularly a slide, on which at least one component is arranged in advance of its seizure by the articulated gripping arm, the supply platform being connected to the exit and extending above or in the enclosure of the vibrating bowl.