Toyota Jidosha Kabushiki Kaisha

Nobuhisa Otsuki

Makoto Kobayashi

Issei Nakashima

Manabu Yamamoto

Kunihiro Iwamoto

Tetsuya Taira

Yuta Watanabe

Shiro Oda

Satoshi Toyoshima

Yuhei Yamaguchi

Tomohisa Takai

Mikio Honda

Haeyeon Lee

Kota Oishi

Hirotaka Komura

Yuta Itozawa

Yutaro Takagi

Hodaka Kito

Masayuki Imaida

Hiroaki Daba

Wataru Kaku

Taiga Matsumoto

Masayoshi Tsuchinaga

Takuya Iwata

Natsuki Yamakami

Yoshiaki Kato

Masahiro Takahashi

Takuma Nakamura

Susumu Shimizu

Hiroshi Bito

Ai Kurokawa

Yoshie Nakanishi

A logistics system provides a logistics service utilizing a logistics robot that delivers packages by autonomous traveling. The logistics system includes one or more processors. When delivery destinations of the packages are dispersedly located on a plurality of floors of a building, the one or more processors execute a priority determination process that determines priority among the plurality of floors. Then, the one or more processors execute a logistics robot control process that controls the logistics robot so as to deliver the packages to the plurality of floors in an order of the priority.

Logistics system, logistics robot, and logistics robot control method

The learning system includes a data generation unit configured to generate learning data based on rehabilitation data and a learning unit configured to perform machine learning using the learning data. A sensor is provided to detect a plurality of motion amounts in a walking motion of a trainee, and it is evaluated that, when one of the motion amounts matches one of abnormal walking criteria, that the walking motion is an abnormal walking pattern that meets the matched abnormal walking criterion. The data generation unit generates each of the pieces of rehabilitation data before and after a change in the results of evaluation of the abnormal walking pattern as learning data. The learning unit sequentially inputs each of the pieces of rehabilitation data as one data set, thereby performing machine learning.

Learning system, walking training system, method, program, and trained model

An automated order processing for order items registered in advance as commodities targeted for automated order service is performed. In the automated order processing, it is determined whether any container/package for the order items exists in the disposal box, based on internal status data of a disposal box or identification data on the contents of the container/package existing in the disposal box. If it is determined that any container/package for the order items exists in the disposal box, the number of discarded containers/packages for the order items existing in the disposal box is calculated. Then, it is determined whether the number of discarded containers/packages is equal to or larger than an upper threshold set according to a sales mode of the order items. If it is determined that the number of discarded containers/packages is equal to or larger than the upper threshold, ordering data of the order items is generated.

Automated order apparatus and automated order method for commodities

A learning unit of a learning system generates the following learning model. That is, this learning model is a model that inputs rehabilitation data for each predetermined period and predicts a change in index data, the rehabilitation data being data about rehabilitation performed by a trainee using a rehabilitation support system, the index data indicating at least one of a symptom, a physical ability, and a degree of recovery of the trainee. This rehabilitation data includes at least the index data and training data of the trainee, the training data being acquired during the rehabilitation in the rehabilitation support system. Further, the learning unit generates the learning model by using, as teacher data, data obtained in a period until the index data reaches a predetermined target level.

Learning system, rehabilitation support system, method, program, and trained model

A learning apparatus, a walking training apparatus, a method, a system, a program, and a trained model for performing walking training at appropriate setting parameters are provided. A learning apparatus according to an embodiment includes: a data acquisition unit configured to acquire rehabilitation data from a walking training apparatus including an actuator configured to assist a walking motion of a trainee and a control unit configured to control the actuator in accordance with a setting parameter; and a data generation unit configured to generate an index indicating a degree of recovery of the trainee and the setting parameter as learning data; and a learning unit configured to generate a learning model that receives the index and outputs a recommended value of the setting parameter by performing machine learning using the learning data.

Learning system, walking training system, system, method, program, and trained model

A delivery method according to the present disclosure includes a step of delivering packages to designated destinations by mobile bodies traveling autonomously, each of the packages having a delivery priority level. The delivery method further includes a step of, when a number of mobile bodies gathered in a bottleneck section is larger than a number of mobile bodies capable of passing through the bottleneck section at the same time, preferentially causing a mobile body delivering a package of which the delivery priority level is higher than a package delivered by another mobile body to pass through the bottleneck section.

Delivery method, delivery management server, and mobile body

A home delivery system delivering objects to a residence comprises a moving body configured to move autonomously or remotely, a plurality of sensors placed in the residence, and the processing apparatus. The processing apparatus is configured to execute observing status of a resident including whether or not the resident is in the residence based on detection information acquired from the plurality of sensors. Then, the processing apparatus is configured to execute instructing the moving body to start a delivery at least condition that the resident is in the residence and instructing the moving body to complete the delivery on condition that the resident is available to response after the moving body arriving at the residence.

Home delivery system, moving body, and home delivery method

When an autonomous mobile robot is acquires enters a stuck state in which the autonomous mobile robot cannot autonomosly move, an autonomous mobile apparatus control system according to the present disclosure transmits an autonomous cancel notification for notifying the higher-level management apparatus that the autonomous mobile robot cannot autonomosly move, waits for an operation instruction from the higher-level management apparatus after the transmission of the autonomous cancel notification. The higher-level management apparatus gives an operation instruction to the autonomous mobile robot in response to receiving the autonomous cancel notification based on information acquired from at least one of the plurality of environment cameras. The autonomous mobile robot is configured to resume autonomous driving in response to safety confirmation based on a proximity sensor provided in the autonomous mobile robot after operating in accordance with the operation instruction.

Autonomous mobile apparatus control system, control method thereof, and control program thereof

A walking training apparatus is a motion support system that includes a walking assistance apparatus as an assistance apparatus, a selected assistance level setting unit, a load data acquisition unit, an angle sensor as a displacement sensor, and an overall control unit as a control unit. The assistance apparatus assists a motion of a joint performed by a user. The assistance level setting unit sets an assistance level that is a level of a force exerted by the assistance apparatus. The load data acquisition unit acquires load data related to a load of the assistance apparatus. The displacement sensor detects a displacement of the joint. The control unit determines a recommended assistance level, which is an assistance level to be recommended, based on the assistance level, the load data, and an output of the displacement sensor, and outputs information about the determined recommended assistance level.

Motion support system, action support method, program, learning apparatus, trained model, and learning method

To effectively enhance the operation efficiency of an autonomous mobile robot, an autonomous mobile robot control system includes a processor and a plurality of environmental cameras. The processor estimates a moving route of each of a plurality of moving bodies on the basis of characteristics of each of the plurality of moving bodies and sets a subset of the plurality of moving bodies whose moving routes overlap among the detected moving bodies as avoidance processing target moving bodies. The processor generates an avoidance procedure for the avoidance processing target moving bodies so the motion of the avoidance processing target moving bodies does not interfere with the motion of other avoidance target moving bodies.

Autonomous mobile robot control system, control method thereof, a non-transitory computer readable medium storing control program thereof, and autonomous mobile robot control device

The traveling unit main body and the accommodation unit are adapted to be uncoupled and re-coupled. The traveling unit main body includes a first driving unit and a second driving unit configured to perform at least one of operations of taking out or storing the article from or in the accommodation unit and transporting the article taken out from the accommodation unit. The traveling unit main body performs at least one of the operations of taking out, storing, and transporting the article using the first driving unit and the second driving unit in a state in which the traveling unit main body and the accommodation unit are uncoupled.

Transportation system, transportation method and program

A logistics system provides a logistics service utilizing a logistics robot that delivers a package by autonomous traveling. The logistics system includes one or more processors configured to execute a delivery route determination process that determines a delivery route along which the logistics robot delivers the package. When there are a plurality of delivery route candidates from a position of the logistics robot to a delivery destination of the package, the one or more processors select the delivery route from the plurality of delivery route candidates based on at least one of a congestion degree of each of the plurality of delivery route candidates, a time of day, a weather condition, and energy consumption of the logistics robot along each of the plurality of delivery route candidates.

Logistics system and logistics robot control method

A service management device manages a service delivered in a predetermined area. The service management device has an operator interface including a display that displays information for an operator and receiving an input from the operator. The service management device communicates with an autonomous robot used for delivering the service in the predetermined area to acquire, from the autonomous robot, service robot information indicating at least a position and a status of the autonomous robot. The service management device displays a map of the predetermined area and the position of the autonomous robot on the display, based on the service robot information. When the autonomous robot displayed on the display is specified by the operator through the operator interface, the service management device displays a status window indicating the status of the autonomous robot specified by the operator on the display, based on the service robot information.

Service management device

Learning system, walking training system, method, program and trained model

The learning apparatus includes a data generation unit configured to generate learning data based on rehabilitation data and a learning unit configured to perform machine learning using the learning data. A sensor is provided to detect a plurality of motion amounts in a walking motion of a trainee, and it is evaluated that, when one of the motion amounts matches one of abnormal walking criteria, that the walking motion is an abnormal walking pattern that meets the matched abnormal walking criterion. The data generation unit generates each of the pieces of rehabilitation data before and after a change in the results of evaluation of the abnormal walking pattern as learning data. The learning unit sequentially inputs each of the pieces of rehabilitation data as one data set, thereby performing machine learning.

Growing community of inventors

Toyota, Japan

Nobuhisa Otsuki