A computer-implemented method, executed by data processing hardware of a robot, includes receiving sensor data for a space within an environment about the robot. The method includes receiving, from a user interface (UI) in communication with the data processing hardware, a user input indicating a user-selection of a location within a two-dimensional (2D) representation of the space. The location corresponds to a position of a target object within the space. The method includes receiving, from the UI, a plurality of grasping inputs designating an orientation and a translation for an end-effector of a robotic manipulator to grasp the target object. The method includes generating a three-dimensional (3D) location of the target object based on the received sensor data and the location corresponding to the user input. The method includes instructing the end-effector to grasp the target object using the generated 3D location and the plurality of grasping inputs.

A grasping error correction method includes a position information acquisition step of acquiring position information of a plurality of areas of a lower component 2, a grasping error value calculation step of calculating a grasping error value based on the position information at the time of the reproduction and the position information of the plurality of areas of the lower component 2 at the time of teaching, and an arm control step of controlling an operation of a multi-axis articulated arm 11a so as to correct the grasping error value. Further, in the grasping error value calculation step, the grasping error value is calculated so that a grasping error in a processing nearby area, which is one of the plurality of areas of the lower component 2 that is closest to the processing area, is preferentially eliminated over those in the other areas of the lower component 2.

A machine learning device that learns an operation of a robot for picking up, by a hand unit, any of a plurality of workpieces placed in a random fashion, including a bulk-loaded state, includes a state variable observation unit that observes a state variable representing a state of the robot, including data output from a three-dimensional measuring device that obtains a three-dimensional map for each workpiece, an operation result obtaining unit that obtains a result of a picking operation of the robot for picking up the workpiece by the hand unit, and a learning unit that learns a manipulated variable including command data for commanding the robot to perform the picking operation of the workpiece, in association with the state variable of the robot and the result of the picking operation, upon receiving output from the state variable observation unit and output from the operation result obtaining unit.

A machine learning device that learns an operation of a robot for picking up, by a hand unit, any of a plurality of objects placed in a random fashion, including a bulk-loaded state, includes a state variable observation unit that observes a state variable representing a state of the robot, including data output from a three-dimensional measuring device that obtains a three-dimensional map for each object, an operation result obtaining unit that obtains a result of a picking operation of the robot for picking up the object by the hand unit, and a learning unit that learns a manipulated variable including command data for commanding the robot to perform the picking operation of the object, in association with the state variable of the robot and the result of the picking operation, upon receiving output from the state variable observation unit and output from the operation result obtaining unit.

A sortation system is disclosed that includes a programmable motion device including an end effector, a perception system for recognizing any of the identity, location, and orientation of an object presented in a plurality of objects, a grasp selection system for selecting a grasp location on the object, the grasp location being chosen to provide a secure grasp of the object by the end effector to permit the object to be moved from the plurality of objects to one of a plurality of destination locations, and a motion planning system for providing a motion path for the transport of the object when grasped by the end effector from the plurality of objects to the one of the plurality of destination locations, wherein the motion path is chosen to provide a path from the plurality of objects to the one of the plurality of destination locations.

A sortation system is disclosed that includes a programmable motion device including an end effector, a perception system for recognizing any of the identity, location, and orientation of an object presented in a plurality of objects, a grasp selection system for selecting a grasp location on the object, the grasp location being chosen to provide a secure grasp of the object by the end effector to permit the object to be moved from the plurality of objects to one of a plurality of destination locations, and a motion planning system for providing a motion path for the transport of the object when grasped by the end effector from the plurality of objects to the one of the plurality of destination locations, wherein the motion path is chosen to provide a path from the plurality of objects to the one of the plurality of destination locations.

An information processor calculates, for a robot hand including a plurality of fingers, a gripping pose at which the robot hand grips a target object. The information processor includes a candidate single-finger placement position detector that detects, based on three-dimensional measurement data obtained through three-dimensional measurement of the target object and hand shape data about a shape of the robot hand, candidate placement positions for each of the plurality of fingers of the robot hand, a multi-finger combination searcher that searches for, among the candidate placement positions for each of the plurality of fingers, a combination of candidate placement positions to allow gripping of the target object, and a gripping pose calculator that calculates, based on the combination of candidate placement positions for each of the plurality of fingers, a gripping pose at which the robot hand grips the target object.

An apparatus including a combination possibility calculation unit to calculate a stable orientation in which, from three-dimensional shape data of a part, the part is stabilized on a flat surface, to calculate a grasping method for grasping the part with a hand, and to calculate a combination in which the hand does not interfere from system configuration data including information on a connection destination of the hand and a combination group of the grasping method and the stable orientation; a regrasping path calculation unit to calculate a regrasping path of the part by using the calculated combination; a path group calculation unit to calculate a path having the minimum number of teaching points from the regrasping path as a path group based on orientation data for designating an input orientation and an alignment orientation of the part; and a program generation unit to generate a program of a robot based on the path group.

A robot system includes workpiece phase detection units that detects a phase of a workpiece around an axis in a substantially vertical direction; a robot including a hand that holds the workpiece, and a wrist capable of rotating the hand around a rotation axis in the substantially vertical direction; and a control unit that controls the robot, wherein the control unit controls the robot based on the phase of the workpiece detected by the workpiece phase detection units, in such a way that the workpiece is held and picked by the hand in a reference phase, among a plurality of predetermined reference phases, closest to a current relative phase of the hand and the workpiece and the phase of the workpiece is aligned with a predetermined target phase by rotation of the wrist.

A conveying apparatus includes: an article detection device; a gripping device with base portion and palm portion, a suction portion, fingers, and a driving mechanism; a negative pressure supplying device; a moving device; a recognition device that measures the shape, the posture, and the size of the article; an operation plan generation device that selects a suction surface of the article, and plans a gripping posture; and a control device that controls an operation of the gripping device and an operation of the moving device to obtain a gripping posture planned by the operation plan generation device.