JP2005128959A5 - - Google Patents

Claims (9)

In a robot apparatus having a movable part,
Imaging means for imaging the external environment of the robot apparatus;
Learning target object setting means for setting a learning target object to be learned using an image captured by the imaging means;
An image extracting means for extracting an object region image occupied by the learning target object in a captured image by moving a part of the movable part to move the learning target object;
A robot apparatus comprising: a feature amount holding unit that extracts and holds a feature amount group including a plurality of feature amounts from the object region image extracted by the image extraction unit.   The image extracting means extracts a motion region image that is a region that has changed before and after moving the learning target object from the captured image, and extracts the object region image from the motion region image. Item 2. The robot device according to Item 1.   The said image extraction means masks the area | region corresponding to a part of said movable part which contacted at least the said learning object from the said movement area image, and extracts the said object area image, It is characterized by the above-mentioned. The robot apparatus described. The image extraction means extracts the time-series object region image by repeatedly moving the learning target object,
The feature amount holding means extracts a feature amount group from each of the time-series object region images, and selects a feature amount of the learning target object from all the extracted feature amount groups of the time-series object region image. The robot apparatus according to claim 1, wherein:   The feature amount holding means is a feature amount group having more feature amounts similar to the feature amount of the object region image at different times out of all the feature amount groups of the time-series object region image. 6. The robot apparatus according to claim 5, wherein only a feature quantity similar to the feature quantity is selected. Feature quantity extraction means for extracting a feature quantity group from an input image captured by the imaging means;
The feature quantity group of the learned object held in the feature quantity holding means is compared with the feature quantity group extracted by the feature quantity extraction means, and the learned object exists in the input image. The robot apparatus according to claim 1, further comprising: feature amount comparison means for detecting whether or not.   As a result of the comparison by the feature amount comparison unit, when a feature amount similar to the feature amount included in the feature amount group of the input image exists among the feature amounts included in the feature amount group of the learned object, The feature quantity comparison means outputs the ratio of the similar feature quantity in the feature quantity group of the learned object as a certainty factor that the learned object exists in the input image. The robot apparatus according to claim 6.   As a result of the comparison by the feature amount comparison means, there are three or more feature amounts similar to the feature amounts included in the feature amount group of the input image among the feature amounts included in the feature amount group of the learned object. The robot apparatus according to claim 6, further comprising posture estimation means for estimating the position and posture of the learned object in the input image. In an object learning method of a robot apparatus having a movable part,
An imaging step of imaging the external environment of the robot apparatus by an imaging means;
A learning target object setting step of setting a learning target object to be a learning target using the image captured in the imaging step;
An image extraction step of extracting an object region image occupied by the learning target object in a captured image by moving the learning target object by bringing a part of the movable part into contact;
A feature amount holding step of extracting and holding a feature amount group consisting of a plurality of feature amounts from the object region image extracted in the image extraction step.