Panasonic Intellectual Property Management Co., Ltd.

Megachips Corporation

Kyushu Institute of Technology

Kenta Nagamine

Akihiro Sakai

Hiromu Hasegawa

Norikazu Ikoma

Fumiya Shingu

Tetsuya Asano

Kenta Nishiyuki

Takashi Kubo

Seiji Nishiyama

Akinobu Miyazaki

Masashi Sakaida

Norihito Fujinoki

Kunihiko Mineya

Keita Mizuno

The positive electrode material according to an aspect of the present disclosure includes a first solid electrolyte, a positive electrode active material, and a coating material coating the surface of the positive electrode active material. The first solid electrolyte is represented by the following compositional formula: LiMOX. In the compositional formula, a, b, c, and d are positive real numbers; M is at least one selected from the group consisting of Ta and Nb; and X is at least one selected from the group consisting of Cl, Br, and I.

Positive electrode material and battery

A negative electrode material of the present disclosure includes a negative electrode active material, a solid electrolyte, and a coating material coating the negative electrode active material. The coating material is represented by the following composition formula (1), where a, b, and c are each a positive real number, A is at least one selected from the group consisting of P and S, and X is F and O.LiAX  (1)

Negative electrode material and battery

A solid electrolyte consists essentially of Li, M, and X. M includes at least one element selected from the group consisting of Gd, Tb, and Sm. X is at least one element selected from the group consisting of Cl, Br, and I.

Solid electrolyte and battery using same

A solid electrolyte material includes Li, Ca, Y, Gd, and X wherein X is at least one element selected from the group consisting of F, Cl, Br, and I. A battery uses the solid electrolyte material.

Solid electrolyte material and battery using same

A solid electrolyte material is composed of Li, M, and X, where M is at least one kind of element selected from the group consisting of metalloid elements and metallic elements other than Li, and X is at least one kind of element selected from the group consisting of F, Cl, Br and I. In the solid electrolyte material, the mathematical formula FWHM/2&#x3b8;&#x2264;0.015 is satisfied, where FWHM represents a half bandwidth of an X-ray diffraction peak having the highest intensity within a range of a diffraction angle 2&#x3b8; of not less than 25 degrees and not more than 35 degrees in an X-ray diffraction pattern provided by an X-ray diffraction measurement of the solid electrolyte material; the X-ray diffraction measurement using a Cu-K&#x3b1; ray; and 2&#x3b8;represents a diffraction angle of a center of the X-ray diffraction peak.

Provided is a solid electrolyte material represented by the following composition formula (1):Li(YM)X&#x2003;&#x2003;Formula (1)

Solid electrolyte material and battery

The position of a moving object is estimated with high accuracy using landmark information, and highly accurate state estimation is performed appropriately at high speed. A landmark detection unit obtains a distance between the moving object and each of two or more landmarks as landmark distance information based on observation data obtained by an observation obtaining unit. A candidate area obtaining unit determines a candidate area for a position of the moving object based on the landmark distance information obtained by the landmark detection unit, and obtains candidate area information indicating the determined candidate area. A state estimation unit estimates an internal state of the moving object based on the observation data, the landmark distance information, and the candidate area information to obtain moving object internal state estimation data, and estimates the environmental map based on the candidate area information and the landmark distance information to obtain environmental map data.

Moving object controller, landmark, and moving object control method

The position of a moving object is estimated with high accuracy based on landmark information, and highly accurate state estimation is performed appropriately at high speed. A landmark detection unit obtains a distance between the moving object and each of two or more landmarks as landmark distance information based on observation data obtained by an observation obtaining unit. A candidate area obtaining unit determines a candidate area for a position of the moving object based on the landmark distance information obtained by the landmark detection unit, and obtains candidate area information indicating the determined candidate area. A state estimation unit estimates an internal state of the moving object based on the observation data, the landmark distance information, and the candidate area information to obtain moving object internal state estimation data, and estimates the environmental map based on the candidate area information and the landmark distance information to obtain environmental map data.

A moving object controller efficiently generates an environmental map and performs highly accurate state estimation in a short time to appropriately control a moving object. An observation obtaining unit obtains observation data from an observable event. A landmark prediction unit generates a landmark prediction signal including predictive information about a landmark at a current time. A landmark detection unit detects information about the landmark at the current time, and generates a landmark detection signal indicating the detection result. A state estimation unit estimates an internal state of the moving object to obtain data indicating an estimated internal state of the moving object at the current time, and estimates the environmental map based on the landmark detection signal to obtain data indicating an estimated environmental map at the current time.

Moving object controller, moving object control method, and integrated circuit

A feature image generation apparatus includes circuitry. The circuitry generates, on the basis of a processing target image in which an object appears, a first image showing the object, and generates, as a feature image showing a feature of the object, at least a part of a rotational composite image obtained by composition of a plurality of rotated images obtained by rotating the first image.

Feature image generation apparatus, classification apparatus and non-transitory computer-readable memory, and feature image generation method and classification method

A state estimation apparatus appropriately estimates the internal state of an observation target by calculating a likelihood from observation data, and tracks, for example, multiple objects in a moving image and detects a new object and adds the object as a tracking target in an appropriate manner. A labeling unit detects a closed area from an observation image, and adds a label number to the closed area to generate a label image. A likelihood obtaining unit generates an object-erased image for new object detection by erasing image areas corresponding to all the currently-tracked objects. The apparatus performs the process for detecting a new object using the object-erased image for new object detection based on label numbers. The apparatus is appropriately prevented from erroneously determining that an area of the object-erased image for new object detection corresponding to the currently-tracked object and remaining after the erasure corresponds to a new object.

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Osaka, Japan

Kenta Nagamine