Abstract: A system capable of recognizing position, a shape, a posture and the like of an object present in a marginal environment of a device such as a robot in order to make the device perform operations on the object as a subject. In an environment recognition system, 3D information and physical information (color information and the like) of a subject are associated by using camera parameters of each of a 3D image sensor and a 2D image sensor. Thereby, the position, the posture and the shape related to the subject and the physical information of the subject present in the environment of a robot are obtained.

Abstract: There is disclosed a mobile robot including an image processor that generates recognition information regarding a target object included in a taken image, and a main controller integrally controlling the robot based on this recognition information.

Abstract: There is disclosed a mobile robot including an image processor that generates recognition information regarding a target object included in a taken image, and a main controller integrally controlling the robot based on this recognition information.

Abstract: A neural network has an input layer, a hidden layer, and an output layer. The neural network includes a lower neural network model composed of hidden layer neurons and input layer neurons for learning a plurality of linearly separable patterns, and a higher neural network model composed of hidden layer neurons and output layer neurons for combining the linearly separable patterns into a linearly unseparable pattern.

Abstract: A motor vehicle is controlled with a neural network which has a data learning capability. A present value of the throttle valve opening of the engine on the motor vehicle and a rate of change of the present value of the throttle valve opening are periodically supplied to the neural network. The neural network is controlled to learn the present value of the throttle valve opening when the rate of change of the present value of the throttle valve opening becomes zero so that a predicted value of the throttle valve opening approaches the actual value of the throttle valve opening at the time the rate of change thereof becomes zero. An operating condition of the motor vehicle is controlled based on the predicted value of the throttle valve opening, which is represented by a periodically produced output signal from the neural network.