Abstract: A course generation device generates course information indicating a course on which a moving body moves. The device outputs a course that the moving body is traveling and a course in the movement destination, generates the course connecting the course that the moving body is traveling to the movement destination, as a curve, estimates or detects an avoidance area to be avoided in traveling, based on an image captured by a camera, and selects again at least one of a start point and an end point of the course to be regenerated, in a case where a distance between the avoidance area and the course is shorter than a predetermined distance, and generates again the course for the distance to be equal to or longer than the predetermined distance.

Abstract: A moving object acquires three-dimensional point cloud data in surroundings of the moving object; and generates a grid map based on the three-dimensional point cloud data, the moving object maps point clouds of the three-dimensional point cloud data to a grid on a horizontal plane parallel to a road surface on which the moving object travels and generates the grid map in which each grid indicates whether a three-dimensional object having a predetermined height or a step exists. The moving object determines, for each grid of the grid map, whether the three-dimensional object exists based on a point density when a point cloud corresponding to each grid of the three-dimensional point cloud data is projected on the horizontal plane.

Abstract: The present invention directs to a moving object control system comprising acquiring a captured image; detecting an obstacle included in the captured image; dividing a region around a moving object and generate an occupancy map indicating occupancy of the obstacle detected for each of divided regions; and generating a global path from a current position to a target position for avoiding the detected obstacle based on a first cost, a second cost, and a third cost, the first cost being higher as a distance from the current position is longer on the occupancy map, the second cost being higher as a distance from the target position is longer on the occupancy map, and the third cost being higher as a distance from a past path is longer on the occupancy map.

Abstract: Provided is an image recognition device configured to execute using a first trained model, which is trained to receive input of an image including a road surface to output areas estimated to have road surfaces with the same attribute in the image as one area, and a second trained model, which is trained to receive input of an image including the road surface as an input to output boundaries of a plurality of the areas in the image, and recognizing a travelable area in which a moving body is capable of traveling on the basis of the areas and the boundaries obtained by inputting an image including a road surface captured by a camera mounted in the moving body to the first trained model and the second trained model.

Abstract: A white line recognition device includes a storage medium storing computer-readable instructions and a processor connected to the storage medium, the processor executing the computer-readable instructions to recognize a linear feature located in an image captured by a monocular camera as a contour of a white line drawn on a road surface, and detect a linear object located at a distance from the road surface based on an output of a distance measurement sensor provided to have at least a detection range in the same direction as the monocular camera. Recognizing the linear feature includes preventing the linear feature from being recognized as the contour of the white line.

Abstract: Provided is a control device for a mobile object capable of moving on a roadway and a predetermined area different from the roadway, the control device comprising a storage device storing a program and a hardware processor connected to the storage device, the hardware processor executing the program stored in the storage device to: recognize whether the mobile object is moving on the roadway or the predetermined area based on an output of an acceleration sensor for detecting an acceleration of the mobile object; and recognize that the mobile object is moving on the predetermined area when the mobile object is determined to reach a braille block based on the output of the acceleration sensor.

Abstract: A control device is mounted on a moving body, and the control device is configured to display, on a display unit, a display of a traffic signal included in an image that has been captured by an imaging unit for imaging an external field of the moving body. The control device comprises a recognition unit configured to recognize the display of the traffic signal from the image; a communication unit configured to receive display information of the traffic signal through wireless communication; and a control portion configured to determine the display of the traffic signal, based on the display of the traffic signal that has been recognized by the recognition unit and the display information that has been received by the communication unit, and configured to display, on the display unit, the display of the traffic signal that has been determined.

Abstract: The present invention provides a recognition device that is mounted on a moving object and recognizes a lighting situation of a traffic signal, the recognition device comprising: an imaging unit that periodically images an external environment of the moving object; at least one processor with a memory comprising instructions cause the at least one processor to at least: sequentially detect, for each image periodically obtained by the imaging unit, a lighting mode of the traffic signal included in the image; and determine, in a case where a same lighting mode of the traffic signal is continuously detected for a predetermined time, the lighting mode as a lighting situation of the traffic signal, wherein the predetermined time is twice or more as long as an imaging cycle of the imaging unit.

Abstract: In a driving assistance device, a human body specifying unit acquires, as human body information, an image of a human body existing around a host vehicle in image data acquired by a camera. A quasi-skeleton estimation unit estimates a quasi-skeleton of the human body from the human body information. The radar or the LiDAR measures a distance to a part of the human body that corresponds to the quasi-skeleton.

Abstract: In a driving assistance device, a human body specifying unit acquires, as human body information, an image of a human body existing around a host vehicle in image data acquired by a camera. A quasi-skeleton estimation unit estimates a quasi-skeleton of the human body from the human body information. The radar or the LiDAR measures a distance to a part of the human body that corresponds to the quasi-skeleton.