Disclosed is a method for using a virtual representation of an indoor environment to identify contents that have been damaged (e.g., by flooding). A virtual representation of a physical scene of an indoor environment is processed to identify a list of contents in the physical scene. The virtual representation may include 2-dimensional representations of the physical scene (e.g., images or video) or a 3-dimensional representation of the physical scene (e.g., 3D digital model). A reference line is determined in the virtual representation that is indicative of a maximum vertical extent of the damage in the physical scene. The position of the reference line is compared with the position of the identified contents in the virtual representation to determine contents that are likely to be damaged. For example, the contents that are at or below a plane represented by the reference line in the virtual representation may be identified as damaged.

Disclosed are 3D LiDAR based target object recognizing method, apparatus, and a mobile object using the same.

A target object recognizing method according to an exemplary embodiment of the present invention includes an irradiating step of irradiating laser light to a reference target object; an acquiring step of acquiring LiDAR data generated based on a reflection signal reflected from the reference target object; a learning step of generating a reference map and virtual LiDAR data based on the LiDAR data and determining a weight for recognizing a target object by performing the deep learning based on the virtual LiDAR data; and recognizing a new target object by applying the weight when new LiDAR data with respect to the new target object is acquired.

Disclosed are 3D LiDAR based target object recognizing method, apparatus, and a mobile object using the same.

A target object recognizing method according to an exemplary embodiment of the present invention includes an irradiating step of irradiating laser light to a reference target object; an acquiring step of acquiring LiDAR data generated based on a reflection signal reflected from the reference target object; a learning step of generating a reference map and virtual LiDAR data based on the LiDAR data and determining a weight for recognizing a target object by performing the deep learning based on the virtual LiDAR data; and recognizing a new target object by applying the weight when new LiDAR data with respect to the new target object is acquired.

An irradiation apparatus may include: an irradiation unit configured to emit a light beam toward a photoelectric conversion unit of a vehicle, the photoelectric conversion unit being configured to convert light energy into electric energy to charge the power storage unit; an adjustment mechanism configured to adjust at least one of a position or a posture of at least one of the irradiation unit or the vehicle; a detector including a light receiving unit configured to receive reflected light of the light beam, and configured to detect a positional relationship between the photoelectric conversion unit and the irradiation unit based on a light receiving result of the reflected light by the light receiving unit; and a controller configured to control the adjustment mechanism based on a detection result of the detector so that the positional relationship between the photoelectric conversion unit and the irradiation unit becomes a predetermined positional relationship.

An irradiation apparatus may include: an irradiation unit configured to emit a light beam toward a photoelectric conversion unit of a vehicle, the photoelectric conversion unit being configured to convert light energy into electric energy to charge the power storage unit; an adjustment mechanism configured to adjust at least one of a position or a posture of at least one of the irradiation unit or the vehicle; a detector including a light receiving unit configured to receive reflected light of the light beam, and configured to detect a positional relationship between the photoelectric conversion unit and the irradiation unit based on a light receiving result of the reflected light by the light receiving unit; and a controller configured to control the adjustment mechanism based on a detection result of the detector so that the positional relationship between the photoelectric conversion unit and the irradiation unit becomes a predetermined positional relationship.

A calibration method implemented by a computer, includes: measuring, with a laser ranging sensor, markers attached to at least two predetermined positions of a bed portion of a trampoline and calculating coordinates of the markers in a first coordinate system with a position of the laser ranging sensor being an origin; and calculating a conversion parameter to convert coordinates of respective positions of the first coordinate system into coordinates of respective positions of a second coordinate system with a center position of the bed portion being an origin based on a relationship between the calculated coordinates of the markers and the at least two predetermined positions of the bed portion.

A calibration method implemented by a computer, includes: measuring, with a laser ranging sensor, markers attached to at least two predetermined positions of a bed portion of a trampoline and calculating coordinates of the markers in a first coordinate system with a position of the laser ranging sensor being an origin; and calculating a conversion parameter to convert coordinates of respective positions of the first coordinate system into coordinates of respective positions of a second coordinate system with a center position of the bed portion being an origin based on a relationship between the calculated coordinates of the markers and the at least two predetermined positions of the bed portion.

An outside sensor unit includes an outside sensor, a main bracket, a support bracket, a rotation device, and a position adjustment device. The outside sensor detects the outside of a vehicle. The main bracket is attached to a vehicle body. The support bracket supports the outside sensor and is attached to the main bracket. The rotation device has a rotation axis line which is substantially parallel to a roll axis of the vehicle and connects the support bracket and the main bracket together rotatably around the rotation axis line. The position adjustment device is capable of adjusting the relative rotation position between the support bracket and the main bracket around the rotation axis line.

An outside sensor unit includes an outside sensor, a main bracket, a support bracket, a rotation device, and a position adjustment device. The outside sensor detects the outside of a vehicle. The main bracket is attached to a vehicle body. The support bracket supports the outside sensor and is attached to the main bracket. The rotation device has a rotation axis line which is substantially parallel to a roll axis of the vehicle and connects the support bracket and the main bracket together rotatably around the rotation axis line. The position adjustment device is capable of adjusting the relative rotation position between the support bracket and the main bracket around the rotation axis line.

The present disclosure relates to systems, vehicles, and methods for adjusting a pointing direction and/or a scanning region of a lidar. An example method includes determining a plurality of points of interest within an environment of a vehicle. The method also includes assigning, to each point of interest of the plurality of points of interest, a respective priority score. The method additionally includes partitioning at least a portion of the environment of the vehicle into a plurality of sectors. Each sector of the plurality of sectors includes at least one point of interest. For each sector of the plurality of sectors, the method includes adjusting a scanning region of a lidar unit based on the respective sector and causing the lidar unit to scan the respective sector.