Pioneer Corporation

Kabushiki Kaisha Toshiba

Fuji Xerox Co., Ltd.

Toshiba Materials Co., Ltd.

Sony Corporation

Pioneer Electronic Corporation

Osaka University

Fujifilm Corporation

Calsonic Kansei Corporation

Nec Corporation

Mitsubishi Heavy Industries Limited

Toshiba Electronic Devices & Storage Corporation

Marelli Corporation

Samsung Electronics Co., Ltd.

Nagoya University

Masahiro Kato

Eiji Muramatsu

Shoji Taniguchi

Yumi Fukuda

Keiko Albessard

Masahiro Miura

Kazuo Kuroda

Naotoshi Matsuda

Eisaku Kawano

Toshio Suzuki

Kunihiko Horikawa

Aoi Okada

Tatsuhiro Yone

Atsushi Yamaguchi

Masayoshi Yoshida

Naoharu Yanagawa

Iwao Mitsuishi

Ryosuke Hiramatsu

Yasushi Hattori

Tohru Kanegae

Katsuhiko Itonori

Shinya Nunoue

Kunio Ishida

Kazufumi Fujiya

Takeshi Koda

Shunichi Kimura

Keiji Katata

Masanori Satake

Hideaki Ashikaga

Tsuyoshi Hasebe

Hiroki Yoshimura

Tomoaki Iwai

Shinji Suzuki

Hiroaki Ikegami

Takao Tagiri

Seiro Oshima

Yuko Muramatsu

Kenji Essaki

Kazutoshi Kitano

Yoshikazu Takeuchi

Masanori Onda

Kazunobu Hashimoto

Toshihiko Takishita

Naotada Okada

Yoshio Sasaki

Yasuhiro Goto

Takayuki Fukasawa

Hidetoshi Fujii

Katsuhisa Homma

Makoto Sato

Yoshiaki Morisada

Kazuaki Nakagawa

Akira Shirota

Yutaka Abe

Sawako Yoshikawa

Atsuhiko Ishihara

Shigeru Kondo

Toshihiro Imada

Tsuyoshi Namiki

Shoko Suyama

Shigeru Yoshida

Yoshitaka Shimoda

Kazunori Masukawa

Kai Funaki

Masami Oishi

Takao Sawabe

Norikazu Ito

Yasuhiro Kato

Takahiro Sato

Hitoshi Kaneko

Akihiro Uchida

Tsuneo Sato

Hiroyuki Fujita

Akira Shimizu

Akira Imamura

Isao Ikeda

Toshiki Hikosaka

Shigeya Kimura

Jun Tamura

Hidehiro Ishii

Masatsugu Ogawa

Masami Suzuki

Yuichi Kojima

Tsuneji Kameda

Makoto Tanahashi

Hironori Asai

Hiroshi Masuichi

Takehiko Muramatsu

Shinichi Nagahara

Daisuke Tatsumi

Hidehiko Kobayashi

Haruyasu Sakata

Takashi Akaba

Yuya Konno

Tsutomu Asawa

Daigo Sugihara

Toshiaki Mizutani

Atsushi Hasebe

Kanji Ishihara

The controllerof the in-vehicle deviceacquires point cloud data outputted by a lidar. Then, the controllergenerates processed point cloud data obtained by down-sampling the point cloud data. The controllermatches the processed point cloud data with voxel data VD which represents a position of an object with respect to each voxel that is a unit area and thereby associates a measurement point of the processed point cloud data with the each voxel. Then, the controllerchanges the size of the subsequent down-sampling based on the associated measurement points number Nc which is the number of measurement points associated with the each voxel among the measurement points of the processed point cloud data.

Information processing device, control method, program, and storage medium

An information processing device includes an acquisition unit configured to acquire point cloud data outputted by a measurement device, an association unit configured to associate, through matching between the point cloud data and position information of an object for each of voxels into which a space is divided, measurement points constituting the point cloud data with the voxels, a position estimation unit configured to perform a position estimation of a moving body equipped with the measurement device, based on the measurement points associated with any of the voxels and the position information for the associated voxels, and a calculation unit configured to calculate a reliability index of a position acquired by the position estimation based on a ratio of a number of the measurement points associated with any of the voxels to a number of the measurement points constituting the point cloud data.

Information processing device, control method, program and storage medium

The above measurement device acquires output data from a sensor unit for detecting surrounding feature, and extracts, from the output data, data corresponding to detection result in a predetermined range in a predetermined positional relation with an own position. The predetermined range is determined in accordance with accuracy of the own position. Then, the measurement device executes predetermined processing based on the extracted data.

Measurement device, measurement method and program

The own vehicle position estimation unitof the in-vehicle deviceacquires the point cloud data which is the measurement result of the landmark by the rider, and acquires the feature information associated with the landmark in the map DB. Then, the own vehicle position estimation unitcalculates, on the basis of the difference between the size of the landmark specified based on the acquired point cloud data and the size of the landmark indicated by the feature information, calculates the reliability information indicative of the measurement accuracy of the landmark by the lidar

Measurement accuracy calculation device, self-position estimation device, control method, program and storage medium

A heat exchanger includes: flat tubes; a plate attached to the flat tubes; a medium tank configured to form a medium flow path by covering openings of flat tubes; and a reinforcing member to reinforce the openings. The reinforcing member includes a pair of leg portions and a connection portion that connects the leg portions. An insertion amount of the leg portions into the opening is larger than a sum of a gap between the connection portion and an inner surface and a length from the opening to a position corresponding to a brazed portion between the flat tube and the plate, or when a protruding portion protruding in a direction opposite an insertion direction is provided in the connection portion, larger than a sum of a gap between the protruding portion and the inner surface and a length from the opening to the position corresponding to the brazed portion.

Heat exchanger and method for manufacturing heat exchanger

A control unitof an in-vehicle deviceconfigured to acquire, from landmark data LD that is map data including position information of one or more features, plural pieces of position information of a feature which is drawn on a road surface and which exists at or around a vehicle. Then, the control unitis configured to calculate a normal vector of an approximate plane calculated based on the acquired plural pieces of the position information. Then, the control unitis configured to calculate at least one of a pitch angle or a roll angle of the vehicle based on the orientation of the vehicle and the normal vector.

The control unitof the in-vehicle deviceis configured to extract, from voxel data VD that is position information of an object for each of unit areas (voxels) into which a space is divided, the voxel data VD of plural voxels located at or around an own vehicle. Then, the control unitis configured to calculate a normal vector of an approximate plane calculated based on the extracted voxel data VD of the plural voxels. Then, the control unitis configured to calculate at least one of a pitch angle of the own vehicle or a roll angle of the own vehicle based on an orientation of the own vehicle and the normal vector.

A self-position estimation device is mounted on a mobile body and acquires a predicted position of the mobile body. Additionally, the self-position estimation device calculates a difference value between a predicted position of an end point of a lane division line that is obtained based on information on the end point of the lane division line acquired from map information and a measured position of the end point of the lane division line measured in such a manner that a measurement unit mounted on the mobile body performs scanning with a light in a predetermined direction. The self-position estimation device estimates a self-position of the mobile body by correcting the predicted position with a value obtained by multiplying the difference value by a coefficient. Further, the self-position estimation device corrects the coefficient based on an interval of scanning positions of the measurement unit at a position where the end point of the lane division line is detected.

Self-position estimation device, self-position estimation method, program, and recording medium

An onboard deviceis provided with an own vehicle position estimation unitand an autonomous driving control unit. The own vehicle position estimation unitestimates the own vehicle position by collating a detection result of a road marking by a lidarwith map DB. The autonomous driving control unitacquires, from the map DB, the road marking information including detection accuracy information Idet indicative of the accuracy of the collation with respect to each road marking. On the basis of the detection accuracy information Idet, the autonomous driving control unitoutputs, to an electronic control device or an information output unitof the vehicle, information for controlling the vehicle so that the accuracy of the collation is equal to or larger than a predetermined value.

Output device, control method, program and storage medium for control of a moving body based on road marking detection accuracy

The own vehicle position estimatorof the in-vehicle deviceacquires the predicted own vehicle position X(t) that is a predicted value of the present position and the orientation of the moving body. Then, the own vehicle position estimatoracquires: the relative angle L(t) that is first orientation information indicative of the orientation of the landmark with respect to the vehicle specified based on the measurement data of the landmark by the lidarand the relative angle L(t) that is second orientation information indicative of the orientation of the landmark with respect to the vehicle into which the orientation of the landmark indicated by the landmark information is converted. The own vehicle position estimatorcorrects the predicted own vehicle position X(t) based on the difference between the relative angle L(t) and the relative angle L(t).

Position estimation device, estimation device, control method, program and storage media

The measurement device acquires output data from a sensor unit for detecting road surface lines around, and determines a predetermined range based on an own position and positional information of broken-line type road surface lines. Then, the measurement device extract, from the output data, data corresponding to detection result of the predetermined range, and executes predetermined processing based on the extracted data.

A measurement device includes a processor coupled to a memory storing instructions. The processor is configured to acquire positional information of a measurement object stored in a storage unit, acquire point group information of points indicating a surrounding feature acquired by an external sensor, output reliability of the positional information of the measurement object indicating a center position of the measurement object existing in a predetermined range based on the point group information of points existing in the predetermined range, the predetermined range being determined based on a position of a movable body, and estimate a movable body position based on the positional information of the measurement object and the center position of the measurement object, wherein the processor determines the center position by calculating an average value of the point group information existing in the predetermined range.

A friction stir welding tool member according to the present embodiment has a shoulder portion and a probe portion concentrically projecting from an upper surface of the shoulder portion. The shoulder portion includes a curved surface processed portion that is curved to have a curved shape on an outer peripheral edge of the shoulder portion. A space occupancy occupied by the two-dimensional space in which neither the shoulder portion nor the probe portion exists is in a range of 30% to 70%, the space occupancy being determined based on a projection drawing of a side surface region surrounded from a tip of the probe portion to the curved surface processed portion of the shoulder portion.

Friction stir welding tool member, and friction stir welding method using the same

A motor drive device of an embodiment includes a first drive circuit, a second drive circuit, a first detection circuit, a second detection circuit, a third detection circuit, a fourth detection circuit, and an output circuit. The first drive circuit drives a first phase of a motor. The second drive circuit drives a second phase of the motor. The first detection circuit detects a first anomaly of the first phase. The second detection circuit detects the first anomaly of the second phase. The third detection circuit detects a second anomaly of the first phase. The fourth detection circuit detects the second anomaly of the second phase. The output circuit outputs an occurred anomaly as a flag signal based on results of detection by the first to fourth detection circuits.

Motor drive device and motor drive system

Growing community of inventors

Tokorozawa, Japan

Masahiro Kato