US 11,745,338 B2
Control apparatus, robot, learning apparatus, robot system, and method
Yoshihisa Ijiri, Tokyo (JP); Yoshiya Shibata, Tokyo (JP); Masashi Hamaya, Tokyo (JP); Kazutoshi Tanaka, Kumamoto (JP); Felix Vondrigalski, Tokyo (JP); and Chisato Saito, Tokyo (JP)
Assigned to OMRON Corporation, Kyoto (JP)
Filed by OMRON Corporation, Kyoto (JP)
Filed on Feb. 11, 2021, as Appl. No. 17/173,481.
Claims priority of application No. 2020-044422 (JP), filed on Mar. 13, 2020.
Prior Publication US 2021/0283771 A1, Sep. 16, 2021
Int. Cl. B25J 9/16 (2006.01); B25J 13/08 (2006.01)
CPC B25J 9/163 (2013.01) [B25J 9/1635 (2013.01); B25J 9/1664 (2013.01); B25J 9/1697 (2013.01); B25J 13/082 (2013.01); B25J 13/088 (2013.01)] 16 Claims
OG exemplary drawing
 
1. A control apparatus of a robot comprising:
a state obtaining unit configured to obtain state observation data comprising flexible related observation data, which is observation data regarding a state of at least one of a physically flexible portion, and a portion of the robot on a side of the physically flexible portion where a gripped object is gripped relative to the physically flexible portion, including the gripped object, wherein the robot comprises:
a gripper configured to grip the gripped object,
an arm configured to move the gripper, and
the physically flexible portion provided in at least one of an intermediate position of the gripper at a joint between a gripping surface and the gripper, a position between the gripper and the arm, and an intermediate position of the arm, the physically flexible portion introducing an uncertainty in the position of the gripper and the object; and
a controller configured to control the robot so as to output an action to be performed by the robot to perform predetermined work on the object, in response to receiving the state observation data, based on output obtained as a result of inputting the state observation data obtained by the state obtaining unit to a learning model, the learning model being learned in advance through machine learning and included in the controller, the machine learning comprising learning processing in which a state space of the robot and an action space of the robot are subjected to dimension reduction based on the uncertainty of the position of the gripper and the object introduced by the physically flexible portion.