An artificial intelligence (AI) device, such as a robot, comprises: an output interface to output content in response to a request of a user; a camera to acquire an image of the user; a microphone to acquire a voice signal including a voice content uttered by the user; a processor to determine a characteristic of the user based on the content, the image, and/or the voice signal, and recognize the voice content through a voice recognition mode corresponding to the determined characteristic. The AI device may include a communication interface to forward the voice signal to a remote computer that identifies the characteristic and recognizes the voice content based on the characteristic. According to an embodiment, when an irregular voice is recognized from the acquired voice signal, the processor may recognize a regular voice corresponding to the irregular voice using an artificial intelligence-based learning model.

An artificial intelligence (AI) device, such as a robot, comprises: an output interface to output content in response to a request of a user; a camera to acquire an image of the user; a microphone to acquire a voice signal including a voice content uttered by the user; a processor to determine a characteristic of the user based on the content, the image, and/or the voice signal, and recognize the voice content through a voice recognition mode corresponding to the determined characteristic. The AI device may include a communication interface to forward the voice signal to a remote computer that identifies the characteristic and recognizes the voice content based on the characteristic. According to an embodiment, when an irregular voice is recognized from the acquired voice signal, the processor may recognize a regular voice corresponding to the irregular voice using an artificial intelligence-based learning model.

A control system for a neck mechanism includes a perception system configured to track movement of an object, and a perception control system that controls a rotary motor to yaw a platform and controls a first linear actuator and a second linear actuator that is in parallel with the first linear actuator to pitch and roll the platform according to a target position of the platform. The perception system tracks movement of the object by estimating its position and pose in 3D space and the platform is moved according to a vision-based position and pose estimation result.

A control system for a neck mechanism includes a perception system configured to track movement of an object, and a perception control system that controls a rotary motor to yaw a platform and controls a first linear actuator and a second linear actuator that is in parallel with the first linear actuator to pitch and roll the platform according to a target position of the platform. The perception system tracks movement of the object by estimating its position and pose in 3D space and the platform is moved according to a vision-based position and pose estimation result.

In a robot, an actuator causes the robot to operate. A processor is configured to acquire, when a holding portion is held by a predetermined target, physical information on a physical function of the predetermined target, and cause, by controlling the actuator depending on the acquired physical information, the robot to perform at least one of an examination operation for examining the physical function of the predetermined target and a training support operation for training the physical function of the predetermined target.

In a robot, an actuator causes the robot to operate. A processor is configured to acquire, when a holding portion is held by a predetermined target, physical information on a physical function of the predetermined target, and cause, by controlling the actuator depending on the acquired physical information, the robot to perform at least one of an examination operation for examining the physical function of the predetermined target and a training support operation for training the physical function of the predetermined target.

An object detection device detects, when a camera that generates an image representing a target object and the target object do not satisfy a predetermined positional relationship, a position of the target object on the image by inputting the image to a classifier, and detects, when the camera and the target object satisfy the predetermined positional relationship, a position of the target object on the image by comparing, with the image, a template representing a feature of an appearance of the target object when the target object is viewed from a predetermined direction.

An object detection device detects, when a camera that generates an image representing a target object and the target object do not satisfy a predetermined positional relationship, a position of the target object on the image by inputting the image to a classifier, and detects, when the camera and the target object satisfy the predetermined positional relationship, a position of the target object on the image by comparing, with the image, a template representing a feature of an appearance of the target object when the target object is viewed from a predetermined direction.

An image recognition method includes obtaining measurement data of a target object, comparing a 3D model having a plurality of feature points and the measurement data and updating importance degrees of the plurality of feature points based on differences between the 3D model and the measurement data, performing learning using the updated importance degrees, and performing object recognition for the target object based on a result of the learning.

An image recognition method includes obtaining measurement data of a target object, comparing a 3D model having a plurality of feature points and the measurement data and updating importance degrees of the plurality of feature points based on differences between the 3D model and the measurement data, performing learning using the updated importance degrees, and performing object recognition for the target object based on a result of the learning.