A bag-shaped actuator system includes: a bag-shaped actuator including an airtight bag member and flowable particulates filled in the bag member; a bag-member communication pipe configured to communicate with an inside of the bag member; a low-air-pressure-source communication pipe configured to communicate with a low air pressure source; a high-air-pressure-source communication pipe configured to communicate with a high air pressure source; a switching mechanism configured to perform switching between communication destinations of the bag member such that the inside of the bag member communicates with any of external air, the low-air-pressure-source communication pipe, and the high-air-pressure-source communication pipe via the bag-member communication pipe; and a switching controlling portion configured to control the switching between the communication destinations by the switching mechanism.

In variants, a method for robot control can include: receiving sensor data of a scene, modeling the physical objects within the scene, determining a set of potential grasp configurations for grasping a physical object within the scene, determining a reach behavior based on the potential grasp configuration, determining a trajectory for the reach behavior, and grasping the object using the trajectory.

The purpose of the present invention is to provide a workpiece unloading device that can stabilize cycle time even when work for reversing a workpiece is involved. A workpiece unloading system comprises a workpiece unloading device for unloading a workpiece, and a control device for setting workpiece unloading order. The control device comprises: a storage unit that stores a set posture representing a posture of a workpiece when the workpiece is set on a jig; a current posture detection unit that detects a current posture representing the current posture of the workpiece; a change amount calculation unit that calculates a change amount between the set posture and the current posture; an unloading candidate identification unit that compares the change amount with a threshold value, and identifies, on the basis of the comparison result, a workpiece as an unloading candidate with priority; and an unload instruction unit that outputs, to the workpiece unloading device, a first instruction to unload the workpiece as the unloading candidate with priority.

The method for increasing the accuracy of grasping an object can include: labelling an image based on an attempted object grasp by a robot and generating a trained graspability network using the labelled images. The method can additionally or alternatively include determining a grasp point using the trained graspability network; executing an object grasp at the grasp point S400; and/or any other suitable elements.

A system and method for identifying a shape and pose of an object is provided. The system includes a controller and a grasping device. The grasping device includes a plurality of fingers that are moveable relative to a base. The fingers include one or more tactile sensors attached thereto. The tactile sensors are configured to collect data, such as a 2D image or 3D point cloud, based on points of contact with the object when the object is grasped. The grasping device is configured to roll the object within the fingers and collect additional data. The controller may combine the data and determine the shape and pose of the object based on the combined data.

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 touch sensation sensor is mounted to a hand part of a robot and includes: an obtaining means, obtaining at least one of visual sensation information, which is target object information relating to a target object operated by using the hand part, and touch sensation information, which is the target object information at a time when the target object operated by using the hand part is gripped; and a control device, changing a sensitivity mode of the touch sensation sensor in accordance with the target object information that is obtained.

A robotic line kitting system is disclosed. In various embodiments, a signal associated with an unsafe condition is received via a communication interface. In response to the signal, a controlled operation to reduce a speed of movement of a robotic instrumentality is performed prior to a safety stop of the robotic instrumentality being triggered.

A learning device and other techniques allow accurate diagnosis of a production facility. A learning device (10) includes a data acquirer that acquires data for learning, and a model generator that generates a learning model for inferring a condition of a workpiece (3) handled in a production facility (2) on the basis of the data for learning. The data for learning includes setting data indicating a setting of the production facility (2), image data indicating an image of the production facility (2) captured by a camera (4), temperature data indicating a surface temperature of the production facility (2) measured by a temperature sensor (5), distance data indicating a distance from a range sensor (6) to the production facility (2) measured by the range sensor (6), and condition data indicating the condition of the workpiece (3) handled in the production facility (2).

A robotic system is disclosed to control multiple robots to cooperatively load/unload a truck or other container. In various embodiments, image data is received and used to control a first robotic arm and a second robotic arm to load or unload objects into or from the truck or other container, including by loading or unloading one or more of the objects using the first robotic arm and the second robotic arm together to cooperatively to grasp and move each of one or more of the objects along a corresponding trajectory.