Abstract: The robot teaching method includes a pre-registration step, robot operation step, and teaching step. The pre-registration step is for specifying a relative self-position of a measuring device with respect to surrounding environment by measuring the surrounding environment using the measuring device, and registering an environment teaching point that is a teaching point of the robot specified using the relative self-position. The robot operation step for automatically operating the robot so that the relative self-position of the robot with respect to the surrounding environment become equal to the environment teaching point in a state where the measuring device is attached to the robot. The teaching step for registering a detection value of a position and a posture of the robot measured by an internal sensor as teaching information in a state where the relative self-position of the robot with respect to the surrounding environment become equal to the environment teaching point.

Abstract: A recess detection device includes a reference value decision processor that extracts, from distance image information, pieces of reference information respectively corresponding to reference regions at different positions within a detection range with a distance from a three-dimensional sensor being within a predetermined range, and determines a reference value based on the reference information, and a presence identification processor that extracts, from the distance image information, pieces of comparison information respectively corresponding to comparison regions within the same detection range, respectively, derives comparison values based on the respective pieces of comparison information, and indicates a presence of a recess when a difference between the reference value and the comparison value exceeds a predetermined threshold.

Abstract: A carrier for carrying an object includes a fork that is vertically movable to carry the object and that is able to be inserted into an opening of a flat portion of the object, a sensor that obtains actual measured values at a plurality of points on the flat portion of the object, and an object state identification device that identifies, based on the actual measured values, an object state including at least one of a position and a posture of the object with respect to the sensor.

Abstract: An object state identification method of identifying a position and a posture of an object by obtaining actual measured values at a plurality of points on a flat portion including an opening on a surface of the object by a sensor includes generating a model value group that is a set of model values indicating the positions of a plurality of points present on surfaces of a corner model, calculating a model feature value based on at least one model value included in the model value group, calculating an actual feature value by the same method used to calculate the model feature value, extracting a corresponding point value indicating a position of an edge of the opening based on the actual feature value that matches the model feature value, and identifying the position and posture of the object based on the corresponding point value.

Abstract: A recess detection device includes a reference value decision processor that extracts, from distance image information, pieces of reference information respectively corresponding to reference regions at different positions within a detection range with a distance from a three-dimensional sensor being within a predetermined range, and determines a reference value based on the reference information, and a presence identification processor that extracts, from the distance image information, pieces of comparison information respectively corresponding to comparison regions within the same detection range, respectively, derives comparison values based on the respective pieces of comparison information, and indicates a presence of a recess when a difference between the reference value and the comparison value exceeds a predetermined threshold.

Abstract: An object state identification method of identifying a position and a posture of an object by obtaining actual measured values, which are three-dimensional data, at points on a flat portion including an opening on a surface of the object by a sensor includes extracting a corresponding point value indicating the position of an edge of the opening based on a predetermined feature value, calculating a plane equation indicating a plane including the flat portion based on the corresponding point value to determine a virtual plane, extracting, as a stable point, an actual measured value that is in the virtual plane, and identifying the position, posture, etc., of the object based on the stable point.

Abstract: An object state identification method of identifying a position and a posture of an object by obtaining actual measured values at a plurality of points on a flat portion including an opening on a surface of the object by a sensor includes generating a model value group that is a set of model values indicating the positions of a plurality of points present on surfaces of a corner model, calculating a model feature value based on at least one model value included in the model value group, calculating an actual feature value by the same method used to calculate the model feature value, extracting a corresponding point value indicating a position of an edge of the opening based on the actual feature value that matches the model feature value, and identifying the position and posture of the object based on the corresponding point value.

Abstract: An autonomous vehicle includes a travel vehicle main body, a model data storage, a photographic device, a search region determiner, an image feature point detector, a feature amount calculator and a position detector. The travel vehicle main body autonomously travels to a target position. The model data storage stores model data related to a geometric feature of an object. The photographic device photographs a periphery of the travel vehicle main body at the target position to acquire image data. The search region determiner predicts a position of the object based on the image data, and determines a search region of a predetermined range including the predicted position of the object. The image feature point detector detects a feature point of the image data with respect to the search region. The feature amount calculator calculates a feature amount of a matching candidate point extracted from the feature point.

Abstract: An autonomous vehicle includes a travel vehicle main body, a model data storage, a photographic device, a search region determiner, an image feature point detector, a feature amount calculator and a position detector. The travel vehicle main body autonomously travels to a target position. The model data storage stores model data related to a geometric feature of an object. The photographic device photographs a periphery of the travel vehicle main body at the target position to acquire image data. The search region determiner predicts a position of the object based on the image data, and determines a search region of a predetermined range including the predicted position of the object. The image feature point detector detects a feature point of the image data with respect to the search region. The feature amount calculator calculates a feature amount of a matching candidate point extracted from the feature point.