公开(公告)号：US20240139950A1

公开(公告)日：2024-05-02

申请号：US18278286

申请日：2021-02-26

Applicant: NEC Corporation

Inventor： Hiroyuki OYAMA ,  Rin TAKANO

IPC: B25J9/16

CPC classification number: B25J9/1666 ,  B25J9/163

Abstract: A constraint condition learning device 1X mainly includes a conversion means 15X and a constraint condition estimation means 16X. The conversion means 15X converts first time series data regarding a state and an input of a robot system during an execution period of a task executed by the robot system into second time series data represented by propositions. The constraint condition estimation means 16X estimates a constraint condition on the task as a logical formula, based on the second time series data and the information regarding whether or not the task succeeded.

公开(公告)号：US20240123614A1

公开(公告)日：2024-04-18

申请号：US18278305

申请日：2021-02-26

Applicant: NEC Corporation

Inventor： Rin TAKANO ,  Hiroyuki OYAMA

IPC: B25J9/16

CPC classification number: B25J9/163 ,  B25J9/161

Abstract: A learning device 1X mainly includes an optimization problem calculation means 51X and an executable state set learning means 52X. The optimization problem calculation means 51X calculates a function value to be a solution for an optimization problem which uses an evaluation function for evaluating reachability to a target state, based on an abstract system model and a detailed system model concerning a system in which a robot operates. The executable state set learning means 52X learns an executable state set of an action of the robot to be executed by a controller based on a function value.

公开(公告)号：US20230364786A1

公开(公告)日：2023-11-16

申请号：US18029325

申请日：2020-10-09

Applicant: NEC Corporation

Inventor： Hiroyuki OYAMA ,  Rin Takano

IPC: B25J9/16

CPC classification number: B25J9/163 ,  B25J9/1653 ,  B25J9/1666

Abstract: A control device 1X mainly includes an abstract state setting means 31X, an environment map generation means 34X, an abstract model generation means 35X, and a control input generation means 36X. The abstract state setting means 31X sets an abstract state which abstractly represents a state of each object in a workspace where each robot works. The environment map generation means 34X generates an environment map which is a map representing accuracy of information in the workspace. The abstract model generation means 35X generates an abstract model which represents dynamics of the abstract state and a time change of the environment map. The control input generation means 36X generates a control input with respect to each robot based on the abstract model.

公开(公告)号：US20220105632A1

公开(公告)日：2022-04-07

申请号：US17426270

申请日：2019-01-30

Applicant: NEC Corporation

Inventor： Hiroyuki OYAMA ,  Takehiro lTOU

IPC: B25J9/16

Abstract: A control device includes a machine learning unit that performs machine learning of control for an operation of a control target device, an avoidance command value calculation unit that obtains an avoidance command value that is a control command value for the control target device, the control command value which satisfies constraint conditions including a condition for the control target device not to come into contact with an obstacle, and the control command value that an evaluation value obtained by applying the control command value to an evaluation function satisfies a prescribed end condition, and a device control unit that controls the control target device on the basis of the avoidance command value, in which a parameter value obtained through the machine learning in the machine learning unit is reflected in at least one of the evaluation function and the constraint condition.

公开(公告)号：US20230241770A1

公开(公告)日：2023-08-03

申请号：US18015621

申请日：2020-07-14

Applicant: NEC Corporation

Inventor： Takehiro ITOU ,  Hiroyuki OYAMA

IPC: B25J9/16 ,  G05B19/4155

CPC classification number: B25J9/163 ,  G05B19/4155 ,  G05B2219/50391

Abstract: The control device 200X functionally includes an operation policy acquisition means 21X and a policy combining means 23X. The operation policy acquisition means 21X is configured to acquire an operation policy relating to an operation of a robot. The operation policy acquisition means 21X is configured to acquire an operation policy relating to an operation of a robot.

公开(公告)号：US20220097231A1

公开(公告)日：2022-03-31

申请号：US17426240

申请日：2019-01-30

Applicant: NEC Corporation

Inventor： Hiroyuki OYAMA ,  Takehiro ITOU

IPC: B25J9/16

Abstract: An obstacle avoidance control device includes an avoidance command value calculation unit that obtains an avoidance command value that is a control command value for control target equipment, the control command value which satisfies constraint conditions including a condition sufficient for the control target equipment not to come into contact with an obstacle, and the control command value that an evaluation value obtained by applying the control command value to an evaluation function satisfies a prescribed end condition, and an equipment control unit that controls the control target equipment on the basis of a processing result of the avoidance command value calculation unit.

公开(公告)号：US20250130562A1

公开(公告)日：2025-04-24

申请号：US18688892

申请日：2021-09-22

Applicant: NEC Corporation

Inventor： Hiroyuki OYAMA ,  Rin TAKANO

IPC: G05B23/02

Abstract: A constraint condition acquisition device acquires success time time-series data, which is time-series data pertaining to control over a control target when a predetermined task carried out through the control is successful, and failure time time-series data, which is the time-series data in the case of task failure; acquires a constraint condition template, which is a constraint condition that includes a parameter; and determines the value of the parameter such that the constraint condition holds in the success time-series data and the constraint condition does not hold in the failure time-series data.

公开(公告)号：US20230364791A1

公开(公告)日：2023-11-16

申请号：US18029261

申请日：2020-10-09

Applicant: NEC Corporation

Inventor： Rin TAKANO ,  Hiroyuki OYAMA

IPC: B25J9/16 ,  B25J13/08

CPC classification number: B25J9/1664 ,  B25J13/089

Abstract: The temporal logic formula generation device 1X mainly includes a target relation logical formula generation means 331X and a target relation logical formula integration means 332X. The target relation logical formula generation means 331X is configured to generate, based on object-to-object relation information representing a relation between objects in a target state relating to a task of the robot, one or more target relation logical formulas that are temporal logic formulas representing relations, in the target state, between respective pair(s) of objects between which the relation is defined. The target relation logical formula integration means 332X is configured to generate a temporal logic formula into which the target relation logical formulas are integrated.

公开(公告)号：US20230099683A1

公开(公告)日：2023-03-30

申请号：US17801919

申请日：2020-02-28

Applicant: NEC Corporation

Inventor： Hiroyuki OYAMA

IPC: B25J9/16

Abstract: A control device 1B mainly includes a subgoal setting means 17B and an operation sequence generation means 18B. The subgoal setting means 17B is configured to set a subgoal “Sg” based on abstract states in which states in a workspace where a robot works are abstracted, the subgoal Sg indicating an intermediate goal for achieving a final goal or constraint conditions required to achieve the final goal. The operation sequence generation means 18B is configured to generate an operation sequence to be executed by the robot based on the subgoal.

公开(公告)号：US20220072708A1

公开(公告)日：2022-03-10

申请号：US17413635

申请日：2019-02-08

Applicant: NEC Corporation

Inventor： Takehiro ITOU ,  Hiroyuki OYAMA

IPC: B25J9/16

Abstract: What is disclosed is a motion model calculation device which easily creates a motion model for a drive device. The motion model calculation device is connected to a robot arm including a plurality of arms and a joint mechanism which pivotally joins the plurality of arms to a connection part, outputs a predetermined motion command to the joint mechanism, acquires a driving state of the joint mechanism caused by a motion corresponding to the motion command, and calculates, on the basis of the motion command and the driving state, a motion model representing the relationship between an input value representing an input to the joint mechanism and an output value of the joint mechanism with respect to the input.