公开(公告)号：US11673271B2

公开(公告)日：2023-06-13

申请号：US17166817

申请日：2021-02-03

Applicant: DENSO CORPORATION

Inventor： Kenichi Minoya

IPC: B25J9/16 ,  B25J13/08

CPC classification number: B25J9/1666 ,  B25J9/163 ,  B25J9/1607 ,  B25J13/089

Abstract: In a trajectory generation apparatus, position coordinates of an obstacle existing in a motion space of a robot arm is acquired. A hand position at a second time, which is a time next to a first time, is estimated by using a learning result of machine learning, based on the position coordinates of the obstacle, a subject joint state of the robot arm at the first time, and a target joint state of the robot arm. A non-interfering joint state of the robot arm at which the obstacle does not interfere with the robot arm at the second time is searched for by using the hand position as a restriction.

公开(公告)号：US11727308B2

公开(公告)日：2023-08-15

申请号：US17003276

申请日：2020-08-26

Applicant: DENSO CORPORATION

Inventor： Kenichi Minoya

IPC: G06N20/00 ,  G06N3/08 ,  G06N3/088

CPC classification number: G06N20/00 ,  G06N3/088

Abstract: A learning method explores, in a block space, a global path from a sub initial point to a sub goal candidate region for movement of an agent, and limits, based on the global path, an exploring space to thereby determine a limited space in the exploring space. The method arranges a sub goal in the limited space in accordance with a position of a goal point, and transforms absolute coordinates of each of at least one obstacle and a sub goal in the limited space into corresponding relative coordinates relative to a position of an agent located in the limited space. Then, the method explores, in the limited space, a target path from the initial point to the sub goal.

公开(公告)号：US20210237270A1

公开(公告)日：2021-08-05

申请号：US17166817

申请日：2021-02-03

Applicant: DENSO CORPORATION

Inventor： Kenichi Minoya

IPC: B25J9/16 ,  B25J13/08

Abstract: In a trajectory generation apparatus, position coordinates of an obstacle existing in a motion space of a robot arm is acquired. A hand position at a second time, which is a time next to a first time, is estimated by using a learning result of machine learning, based on the position coordinates of the obstacle, a subject joint state of the robot arm at the first time, and a target joint state of the robot arm. A non-interfering joint state of the robot arm at which the obstacle does not interfere with the robot arm at the second time is searched for by using the hand position as a restriction.

公开(公告)号：US10083153B2

公开(公告)日：2018-09-25

申请号：US14673962

申请日：2015-03-31

Applicant: DENSO CORPORATION

Inventor： Tomoaki Ozaki ,  Kenichi Minoya

IPC: G06F17/10 ,  G06N3/04 ,  G06F17/15

CPC classification number: G06F17/10 ,  G06F17/15 ,  G06N3/04

Abstract: An arithmetic processing apparatus performs arithmetic by a neural network in which multiple processing layers are hierarchically connected. The arithmetic processing apparatus corresponding to one of the multiple processing layers includes a convolution arithmetic portion and a pooling processing portion. The convolution arithmetic portion receives an input data from another of the plurality of processing layers, performs convolution arithmetic to the input data, and in each arithmetic cycle, outputs a part of all convolution arithmetic result data required for single pooling processing. The pooling processing portion performs the single pooling processing to the all convolution arithmetic result data before executing activation processing.