Provided is an information processing apparatus that processes information for implementing the best gripping operation suitable for a characteristic of a gripper.

The information processing apparatus includes: a grip information analysis unit that analyzes an object and generates generalized grip shape information; and a generalized grip shape information accumulation unit that accumulates the generalized grip shape information. The information processing apparatus further includes a grip objective planning unit that plans a grip objective of the object on the basis of the generalized grip shape information of the object and a characteristic of a gripper to be used for a grip. The grip objective planning unit plans the grip objective regarding how to grip which portion of the object.

The purpose of the present invention is to provide a device for outputting holding detection results by a highly accurate simulation in consideration of parameters related to a holding member. A user enters workpiece information through an input UI unit. A selection control unit executes an automatic selection process of a suction pad based on the workpiece information input through the input UI unit, an automatic selection process of a workpiece physical model, an automatic selection process of a robot, and a confirmation process of a vibration tolerance, and then displays the selection results. The selection control unit determines whether there is a problem with the selection results based on an input instruction from the user.

A region-based robotic grasp generation technique for machine tending or bin picking applications. Part and gripper geometry are provided as inputs, typically from CAD files, along with gripper kinematics. A human user defines one or more target grasp regions on the part, using a graphical user interface displaying the part geometry. The target grasp regions are identified by the user based on the user's knowledge of how the part may be grasped to ensure that the part can be subsequently placed in a proper destination pose. For each of the target grasp regions, an optimization solver is used to compute a plurality of quality grasps with stable surface contact between the part and the gripper, and no part-gripper interference. The computed grasps for each target grasp region are placed in a grasp database which is used by a robot in actual bin picking operations.

Disclosed is a method of providing performance indicators of a robot hand and a method of optimizing a structure of the robot hand, and more particularly to a method of providing performance indicators of a robot hand, in which the performance indicators are to objectively compare a plurality of robot hands with respect to performance, and a method of optimizing a structure of the robot hand, in which engineering design criteria are provided to determine essential factors in developing the structure of the robot hand.

The purpose of the present invention is to provide a device for outputting holding detection results by a highly accurate simulation in consideration of parameters related to a holding member. A user enters workpiece information through an input UI unit. A selection control unit executes an automatic selection process of a suction pad based on the workpiece information input through the input UI unit, an automatic selection process of a workpiece physical model, an automatic selection process of a robot, and a confirmation process of a vibration tolerance, and then displays the selection results. The selection control unit determines whether there is a problem with the selection results based on an input instruction from the user.

An information processing apparatus according to an embodiment of the present technology includes a region calculation unit. The region calculation unit calculates, on the basis of operation information regarding an operation performed on a target object and an image of the target object, a hand area when the operation is performed on the target object by using an image generator or a predictor. This enables a high-precision operation. Moreover, a dataset used for the image generator and the predictor can be collected more easily. Therefore, a massive amount of datasets can be built and can be applied to various target objects.