Device, system and method for calibration of camera and laser sensor
US-9470548-B2 · Oct 18, 2016 · US
US11460563B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-11460563-B2 |
| Application number | US-202017247304-A |
| Country | US |
| Kind code | B2 |
| Filing date | Dec 7, 2020 |
| Priority date | Apr 28, 2017 |
| Publication date | Oct 4, 2022 |
| Grant date | Oct 4, 2022 |
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Automatic calibration of laser sensors carried by a mobile platform, and associated systems and methods are disclosed herein. A representative method includes determining an overlapping region of point cloud data generated by laser sensors, comparing surface features of the point clouds within the overlapping region, and generating calibration rules based thereon.
Opening claim text (preview).
We claim: 1. A computer-implemented method for calibrating a first sensor and a second sensor, both carried by a mobile platform, the method comprising: determining an overlapping region between a first point cloud and a second point cloud based at least in part on identifying at least a nearest neighbor in the second point cloud for at least one point in the first point cloud, the first and second point clouds being transformed into a coordinate system of the mobile platform, wherein the first point cloud is determined from data generated by the first sensor and the second point cloud is determined from data generated by the second sensor; comparing surface attributes of the first and second point clouds in the overlapping region; generating a calibration rule for calibration between the first sensor and the second sensor based at least in part on comparing the surface attributes; and determining whether to take one or more further actions based on comparing the calibration rule with a previously generated calibration rule. 2. The method of claim 1 , wherein determining whether to take the one or more further actions comprises: comparing a difference between the calibration rule and the previously generated calibration rule with a threshold. 3. The method of claim 2 , wherein determining whether to take the one or more further actions comprises: determining to take the one or more further actions when the difference between the calibration rule and the previously generated calibration rule exceeds the threshold. 4. The method of claim 1 , wherein the one or more further actions comprise at least one of: issuing a warning to be provided to a user of the mobile platform; or initiating a safety mechanism to restrict navigation or other functions of the mobile platform. 5. The method of claim 1 , wherein the calibration rule or the previously generated calibration rule comprises at least one of a translational transformation or a rotational transformation. 6. The method of claim 1 , wherein determining the overlapping region comprises creating a tree-structured. data structure for at least one of the first or second point clouds. 7. The method of claim 6 , wherein the tree-structured data structure comprises a K-Dimensional (KD) tree data structure. 8. The method of claim 1 , wherein comparing surface attributes comprises matching a surface associated with the first point cloud with a surface associated with the second point cloud. 9. The method of claim 8 , wherein matching a surface associated with the first point cloud with a surface associated with the second point cloud comprises determining normal vector information with respect to at least a portion of the first point cloud. 10. The method of claim 1 , wherein comparing surface attributes further comprises evaluating a target function defined at least in part by a plurality of points of the first and second point clouds that are within the overlapping region, wherein the target function comprises a rotational component and a translational component. 11. The method of claim 10 , wherein comparing surface attributes further comprises keeping the translational component fixed. 12. The method of claim 10 , wherein generating the calibration rule comprises optimizing the target function based at least in part on a least squares method. 13. A mobile platform including a controller programmed to at least partially control one or more motions of the mobile platform, wherein the programmed controller includes one or more processors configured to: determine an overlapping region between a first point cloud and a second point cloud based at least in part on identifying at least a nearest neighbor in the second point cloud for at least one point in the first point cloud, the first and second point clouds being transformed into a coordinate system of the mobile platform that carries a first sensor and a second sensor, wherein the first point cloud is determined from data generated by the first sensor and the second point cloud is determined from data generated by the second sensor; compare surface attributes of the first and second point clouds in the overlapping region; generate a calibration rule for calibration between the first sensor and the second sensor based at least in part on comparing the surface attributes; and determining whether to take one or more further actions based on comparing the calibration rule with a previously generated calibration rule. 14. The mobile platform of claim 13 , wherein the first sensor or the second sensor comprises at least one laser sensor. 15. The mobile platform of claim 13 , wherein the first sensor or the second sensor comprises a plurality of laser sensors rigidly fixed relative to each other. 16. The mobile platform of claim 13 , wherein the mobile platform includes at least one of an unmanned aerial vehicle (UAV), a manned aircraft, a vehicle, an autonomous car, a self-balancing vehicle, a robot, a smart wearable device, a virtual reality (VR) head-mounted display, or an augmented reality (AR) head-mounted display. 17. The mobile platform of claim 13 , wherein when determining whether to take the one or more further actions, the one or more processors are further configured to: determine to take the one or more actions when a difference between the calibration rule and the previously generated calibration rule exceeds a threshold. 18. The mobile platform of claim 17 , wherein the one or more further actions comprise at least one of: issuing a warning to be provided to a user of the mobile platform; or initiating a safety mechanism to restrict navigation or other functions of the mobile platform. 19. A non-transitory computer-readable medium storing computer executable instructions that, when executed, cause one or more processors associated with a mobile platform to perform actions comprising: determining an overlapping region between a first point cloud and a second point cloud based at least in part on identifying at least a nearest neighbor in the second point cloud for at least one point in the first point cloud, the first and second point clouds being transformed into a coordinate system of the mobile platform that carries a first sensor and a second sensor, wherein the first point cloud is determined from data generated by the first sensor and the second point cloud is determined from data generated by the second sensor; comparing surface attributes of the first and second point clouds in the overlapping region; generating a calibration rule for calibration between the first sensor and the second sensor based at least in part on comparing the surface attributes; and determining whether to take one or more further actions based on comparing the calibration rule with a previously generated calibration rule. 20. The computer-readable medium of claim 19 , wherein when determining whether to take the one or more further actions, the computer executable instructions that, when executed, further cause the one or more processors associated with the mobile platform to perform actions comprising: determining to take the one or more further actions when a difference between the calibration rule and the previously generated calibration rule exceeds a threshold.
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