A controller that allows reteaching of a machine made up of a plurality of mechanisms to be easily performed is provided. The controller includes a machine position acquiring section that acquires the current positions of mechanisms, a reteach block search section that assigns rank order numbers to linkage information that indicates linkage between blocks of a plurality of machine control programs on the basis of relation between the current positions of the mechanisms and taught positions in blocks in the machine control programs that are indicated as being linked to one another by the linkage information, a search result output section that outputs blocks relating to the linkage information on the basis of the rank order numbers assigned by the reteach block search section, and a reteach result reflecting section that reflects, in blocks of the plurality of machine control programs that are selected as blocks to be retaught, the current positions of the mechanisms as positions to be retaught.

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 for providing processing of homogenous and non-homogenous objects in both structured and cluttered environments. The sortation system 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 robot system includes: at least one non-learned robot that has not learned a learning compensation amount of position control based on an operation command; at least one learned robot that has learned the learning compensation amount of the position control based on the operation command; and a storage device that stores the operation command and the learning compensation amount of the learned robot, the non-learned robot comprising a compensation amount estimation unit that compensates the learning compensation amount of the learned robot stored in the storage device based on a difference between the operation command of the learned robot stored in the storage device and an operation command of an own robot, and estimates the compensated learning compensation amount as a learning compensation amount of the own robot.

A machine learning device includes: a state observation unit that observes component arrangement data representing an arrangement of components on a component serving place, component data representing information of the components, and operator status data representing status information of an operator, as state variables representing a current state of an environment; a determination data acquisition unit that acquires product quality determination data for determining quality of the product which is assembled based on an arrangement of the components and takt time determination data for determining takt time for assembly of the product as determination data; and a learning unit that performs learning based on the state variables and the determination data in a manner to associate information of the components used for assembling the product and status information of the operator with respect to an arrangement of the components on the component serving place.

A robot system includes a robot including leading end, base, and multi-articular arm, and circuitry that controls the atm to move the end based on motion control program specifying transition over time of target position and posture of the end, the transition including correction target portion starting and ending in the transition; controls the arm to move the end in response to guided manipulation applying external force to the robot while the circuitry controls the arm; obtains relative command information based on the target position and posture at start of the correction portion and specifying the target position and posture at points in the correction portion including start and end in the correction portion; and controls the arm to move the end from the position and posture based on the information, beginning at time when movement of the arm controlled by the circuitry in response to the manipulation has ended.

A machine tool includes an operation evaluation section that evaluates an operation thereof and a machine learning device that performs the machine learning of a movement amount of an axis thereof. The machine learning device calculates a reward based on state data including the output of the operation evaluation section, performs the machine learning of the determination of the movement amount of the axis, and determines the movement amount of the axis based on a machine learning result and outputs the determined movement amount. The machine learning device performs the machine learning of the determination of the movement amount of the axis based on the determined movement amount of the axis, the acquired state data, and the calculated reward.

A robot system includes: at least one non-learned robot that has not learned a learning compensation amount of position control based on an operation command; at least one learned robot that has learned the learning compensation amount of the position control based on the operation command; and a storage device that stores the operation command and the learning compensation amount of the learned robot, the non-learned robot comprising a compensation amount estimation unit that compensates the learning compensation amount of the learned robot stored in the storage device based on a difference between the operation command of the learned robot stored in the storage device and an operation command of an own robot, and estimates the compensated learning compensation amount as a learning compensation amount of the own robot.

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 processing apparatus includes a first obtaining unit configured to obtain a holding position and orientation of a manipulator when holding of a target object is performed and holding success or failure information of the target object in the holding position and orientation, a second obtaining unit configured to obtain an image in which the target object is imaged when the holding of the target object is performed, and a generation unit configured to generate learning data when the holding of the target object by the manipulator is learnt on a basis of the holding position and orientation and the holding success or failure information obtained by the first obtaining unit and the image obtained by the second obtaining unit.