Mitsubishi Heavy Industries Limited

Mitsubishi Heavy Industries Machinery Systems, Ltd.

Mitsubishi Logisnext Co. Ltd.

Kiichi Sugimoto

Kenta Nakao

Satoshi Iio

Tomohiro Matsumoto

Takuma Okazaki

Shogo Minami

Koji Shiizaki

Akira Ando

Kensuke Futahashi

Kenji Takao

Ryota Hiura

Akemi Takano

Takeshi Korenaga

Naruhisa Kameo

Takeshi Fukase

Yosuke Fujitomi

Yohei Kojima

Tsuyoshi Tomita

Hajime Kodaira

Atsushi Kiya

Hidenori Takeda

A movable body that moves automatically includes a plurality of sensors configured to detect an obstacle in a periphery of the movable body, a selection information acquisition unit configured to acquire selection information indicating a sensor, of the plurality of sensors, to be used for detection of the obstacle, the sensor being set based on a relationship between a reference position of the obstacle and a position of the movable body, and a detection control unit configured to cause the sensor indicated by the selection information to detect the obstacle, and identify a position of the obstacle from a detection result of the obstacle.

Movable body, movement control system, method for controlling movable body, and program

A processing device includes: a calculation unit that is configured to detect a position of an object that is a possible obstacle to a vehicle; a first detection unit that is configured to detect a direction of a line of sight of a driver of the vehicle; a decision unit that is configured to decide an aspect of an alarm on the basis of the position and the direction of the line of sight of the driver; and a control unit that is configured to control a speaker corresponding to the position such that a sound of the aspect is output.

Processing device, processing method, notification system, and recording medium

A program creation device includes training data including image data, a setting unit configured to set information of a frame specifying a region for each cell for detecting the presence or absence of the object from the image, and a learning unit configured to execute machine learning of the training data and to create a learned program for extracting the object from the image. The setting unit acquires information on a target region of the training data and on aspect ratios of the anchor, calculates a degree of matching between the anchor and the target region for each aspect ratio while changing a size of the anchor, and calculates an adoption rate of the target region whose degree of matching is a proportion no less than a threshold, and determines, based on a result of the calculation, the size of the anchor used in the learned program.

Program creation device, object detection system, anchor setting method, and anchor setting program

A control device includes a specifying unit that specifies one of a plurality of detection objects on the basis of a state of an industrial vehicle when the plurality of detection objects are detected around the industrial vehicle, and a control unit that causes a notification to be performed for the one detection object specified by the specifying unit in an aspect different from those of other detected detection objects.

Control device, control method, and computer readable medium

A vehicle image processing device includes: a plurality of buffers configured to accumulate pieces of image data input individually and sequentially from a plurality of cameras installed in a vehicle so as to associate the pieces of image data with the cameras; a processor configured to select the buffer based on the state information of the vehicle and acquire the piece of image data from the selected buffer so as to perform image processing thereon; a signal line for transferring the pieces of image data in the buffers to the processor; and a transfer controller configured to output the piece of image data in the buffer required from the processor to the signal line.

Vehicle image processing device, vehicle image processing method, program and storage medium

A map error detection system includes a map error position candidate calculation unit configured to calculate a map error candidate position which is a candidate for route information not included in map information on the basis of an aggregation of positional information not corresponding to route information included in the map information among time-series positional information of a moving object.

Map error detection system, map error detection method, and program

A navigation system includes: a traffic condition calculation unit () that calculates an evaluation value indicating a traffic condition of each road segment included in a target area; a guidance route determination unit () that determines a route in which a degree of non-congestion based on the traffic condition evaluation value of a road segment included in a route to a destination of each vehicle is the highest as a guidance route on the basis of the traffic condition evaluation value calculated by the traffic condition calculation unit and the destination of each vehicle; and a guidance route providing unit () that provides the guidance routes determined by the guidance route determination unit to a driver of the corresponding vehicle.

Navigation system and on-board unit

An image recognition device includes an edge direction evaluation unit configured to evaluate a direction of an edge at each coordinate by assigning points to the coordinate when a deviation amount between a direction of an outline of an abundance ratio higher than a predetermined abundance ratio threshold value among directions of an outline of a character available for the vehicle number plate and the direction of the edge at each coordinate of the image is less than a predetermined deviation amount threshold value and a vehicle number plate region extraction unit configured to extract a region of the vehicle number plate from the image based on a distribution of the points assigned by the edge direction evaluation unit.

Image recognition device, image recognition method, program, and recording medium

With an image processing device, a presence/absence of a product defect is judged based on detected-image data obtained by a radiographic device that detects radiation that has passed through a product, which is an inspection subject. With the image processing device, a position of a product feature in the detected-image data is identified based on a shape of the product feature indicated by feature data stored in a storage portion in advance, defect candidates are extracted with reference to the identified product feature in the detected-image data, and the presence/absence of a product defect is judged based on characteristic quantities of product defects indicated by a defect characteristic stored in the storage portion in advance and characteristic quantities of the defect candidates.

Growing community of inventors

Tokyo, Japan

Kiichi Sugimoto