Megachips Corporation

Kyushu Institute of Technology

Kabushiki Kaisha Topcon

Norikazu Ikoma

Hiromu Hasegawa

Kenta Nagamine

Fumiya Shingu

Hitoshi Otani

Takahiro Komeichi

Kazuhiko Kawamoto

Provided is a state determination apparatus that appropriately performs pattern classification processing and/or pattern determination processing even when a map generated by the SOM technique includes discontinuous image regions. In the state determination apparatus, the matching processing unit obtains adaptability data indicating a correlation degree between template data indicating a state and the SOM output data. The state determination unit obtains a state evaluation value based on an activity value obtained by the activity value obtaining unit and the adaptability value. The time series estimation unit determines a state of an input data based on the state evaluation value and state transition probability between states. This allows for appropriately performing pattern classification processing and/or pattern determination processing even when a map generated by the SOM technique includes discontinuous image regions.

State determination apparatus, state determination method, and integrated circuit

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

A state estimation apparatus obtains observation data sets for a tracking target object, and estimates an internal state of the object using likelihoods obtained from the observation data sets and the reliability of each observation data set. A first observation obtaining unit obtains first observation data. A second observation obtaining unit obtains second observation data. A first likelihood obtaining unit obtains a first likelihood based on the first observation data. A second likelihood obtaining unit obtains a second likelihood based on the second observation data. A likelihood combining unit obtains a combined likelihood based on the first and second likelihoods, first reliability data indicating the reliability of the first observation data, and second reliability data indicating the reliability of the second observation data. A posterior probability distribution obtaining unit obtains posterior probability distribution data indicating a probability distribution of the internal state of the observation target at current time t from the combined likelihood and predictive probability distribution data.

State estimation apparatus, state estimation method, integrated circuit, and non-transitory computer-readable storage medium

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

The purpose of the present invention is to provide a state estimation apparatus that appropriately estimates the internal state of an observation target by determining likelihoods from a plurality of observations. An observation obtaining unit of the state estimation system obtains, at given time intervals, a plurality of observation data obtained from an observable event. The observation selecting unit selects a piece of observation data from the plurality of pieces of observation data obtained by the observation obtaining unit based on a posterior probability distribution data obtained at a preceding time t&#x2212;1. The likelihood obtaining unit obtains likelihood data based on the observation data selected by the observation selecting unit and predicted probability distribution data obtained through prediction processing using the posterior probability distribution data. The posterior probability distribution estimation unit estimates posterior probability distribution data representing a state of the observable event based on the predicted probability distribution data obtained by the likelihood obtaining unit and the likelihood data. The prior probability distribution output unit outputs prior probability distribution data based on the posterior probability distribution data estimated by the posterior probability distribution estimation unit as prior probability distribution data at a next time t+1.

State estimation apparatus, state estimation method, and integrated circuit with calculation of likelihood data and estimation of posterior probability distribution data

Provided is a state estimation apparatus that enables more accurate and robust detection and tracking of an object by obtaining a plurality of sets of observation data for a tracking target object and estimating the internal state of the object using a plurality of likelihoods calculated from the obtained sets of observation data. The state estimation apparatus obtains first observation data and second observation data, each of which is composed of a plurality of pieces of observation data, and obtains possibility measurement data and necessity measurement data from the obtained plurality of pieces of observation data. In the state estimation apparatus, a likelihood obtaining unit obtains a first likelihood wp and a second likelihood wn from the possibility measurement data and the necessity measurement data. Using the obtained first likelihood wp and second likelihood wn enables the internal state of the object to be estimated.

State estimation apparatus, state estimation method, and integrated circuit

A method of automatic tracking of a target is disclosed. This method includes a light spot detecting step of detecting a light spot from a target supported on a moving object, a step of taking a moving image of the target and the moving object, a step of target tracking based on the detection of the light spot, a step of performing image tracking based on the moving image in parallel to the target tracking, a step of comparing a position of the target obtained by the target tracking with a position of the image obtained by the image tracking, and a step of tracking the target based on a result of the target tracking in case where the target position and the image position are within a predetermined range.

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Fukuoka, Japan

Norikazu Ikoma