An information processing device for estimating a self-position of a mobile body based on a map of environment where the mobile body travels, comprising: a detection section including at least one of a laser scanner, a distance sensor, and an imaging device configured to detect, as detection information, a distance to an object at a periphery of the mobile body and a direction of the object; and a control section configured to control the detection section, wherein the control section includes a storage configured to store the detection information, which has been detected by the detection section, in chronological order and store a map, a map producer configured to produce a map of the periphery of the mobile body based on the detection information stored in the storage and store the map in the storage, characterized by: an existing map self-position estimator configured to estimate a current self-position of the mobile body by matching an existing map previously produced and stored in the storage with the detection information, the matching being made based on the shape of a point cloud on the existing map and the shape of a point cloud in the scan information detected by the detection section, using an iterative closest point algorithm, a current map self-position estimator configured to estimate the current self-position of the mobile body by matching a current map being currently produced and stored in the storage with the detection information, the matching being made based on the shape of a point cloud on the current map and the shape of the point cloud in the scan information detected by the detection section, using an iterative closest point algorithm, a reliability evaluator configured to evaluate a reliability of each self-position estimated by the existing map self-position estimator and the current map self-position estimator, and a self-position updater configured to update either one of the self-positions based on the reliability evaluated by the reliability evaluator. a detection section including at least one of a laser scanner, a distance sensor, and an imaging device configured to detect, as detection information, a distance to an object at a periphery of the mobile body and a direction of the object; and a control section configured to control the detection section, wherein the control section includes a storage configured to store the detection information, which has been detected by the detection section, in chronological order and store a map, a map producer configured to produce a map of the periphery of the mobile body based on the detection information stored in the storage and store the map in the storage, characterized by: an existing map self-position estimator configured to estimate a current self-position of the mobile body by matching an existing map previously produced and stored in the storage with the detection information, the matching being made based on the shape of a point cloud on the existing map and the shape of a point cloud in the scan information detected by the detection section, using an iterative closest point algorithm, a current map self-position estimator configured to estimate the current self-position of the mobile body by matching a current map being currently produced and stored in the storage with the detection information, the matching being made based on the shape of a point cloud on the current map and the shape of the point cloud in the scan information detected by the detection section, using an iterative closest point algorithm, a reliability evaluator configured to evaluate a reliability of each self-position estimated by the existing map self-position estimator and the current map self-position estimator, and a self-position updater configured to update either one of the self-positions based on the reliability evaluated by the reliability evaluator. an existing map self-position estimator configured to estimate a current self-position of the mobile body by matching an existing map previously produced and stored in the storage with the detection information, the matching being made based on the shape of a point cloud on the existing map and the shape of a point cloud in the scan information detected by the detection section, using an iterative closest point algorithm, a current map self-position estimator configured to estimate the current self-position of the mobile body by matching a current map being currently produced and stored in the storage with the detection information, the matching being made based on the shape of a point cloud on the current map and the shape of the point cloud in the scan information detected by the detection section, using an iterative closest point algorithm, a reliability evaluator configured to evaluate a reliability of each self-position estimated by the existing map self-position estimator and the current map self-position estimator, and a self-position updater configured to update either one of the self-positions based on the reliability evaluated by the reliability evaluator.