OBJECT DETECTION BASED ON LIDAR INTENSITY
First Claim
1. An autonomous vehicle (AV) system comprising:
- one or more processors of a machine; and
a machine-storage medium storing instructions that, when executed by the one or more processors, cause the machine to perform operations comprising;
accessing an incoming data point output by a light detection and ranging (Lidar) unit during operation of the AV system;
inferring, using a reflectance inference model, a reflectance value of an object based on the incoming data point, the reflectance inference model comprising a mapping of a set of previously collected data points to a coordinate system using range and raw intensity values of the previously collected data points as coordinates, the reflectance value being interpolated from at least two previously collected data points of the set of previously collected data points mapped to the coordinate system, each of the two previously collected data points corresponding to one of multiple known reflectance values; and
determining one or more characteristics of the object based on the inferred reflectance value.
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Accused Products
Abstract
Aspects of the present disclosure involve systems, methods, and devices for determining reflectance properties of objects based on Lidar intensity values. A system includes one or more processors of a machine and a machine-storage medium storing instructions that, when executed by the one or more processors, cause the machine to perform operations comprising accessing an incoming data point output by a Lidar unit during operation of a vehicle. The operations may further include inferring, using a reflectance inference model, a reflectance value of an object based on the incoming data point. The reflectance inference model comprises a mapping of previously collected data points to a coordinate system using associated range values and raw intensity values. The operations may further include determining one or more characteristics of the object based on the inferred reflectance value.
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Citations
20 Claims
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1. An autonomous vehicle (AV) system comprising:
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one or more processors of a machine; and a machine-storage medium storing instructions that, when executed by the one or more processors, cause the machine to perform operations comprising; accessing an incoming data point output by a light detection and ranging (Lidar) unit during operation of the AV system; inferring, using a reflectance inference model, a reflectance value of an object based on the incoming data point, the reflectance inference model comprising a mapping of a set of previously collected data points to a coordinate system using range and raw intensity values of the previously collected data points as coordinates, the reflectance value being interpolated from at least two previously collected data points of the set of previously collected data points mapped to the coordinate system, each of the two previously collected data points corresponding to one of multiple known reflectance values; and determining one or more characteristics of the object based on the inferred reflectance value. - View Dependent Claims (2, 3, 4, 5, 6, 7)
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8. A light detection and ranging (Lidar) calibration system comprising:
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one or more processors of a machine; and a machine-storage medium storing instructions that, when executed by the one or more processors, cause the machine to perform operations comprising; collecting a data set comprising a plurality of data points output by Lidar unit, each of the data points corresponding to one of multiple targets, each target having a known reflectance value; and generating a reflectance inference model for the Lidar unit based on the data set, the generating of the reflectance inference model comprising mapping the plurality of data points to a coordinate system using range and raw intensity values of each data point as coordinates, the reflectance inference model operable to infer reflectance values from incoming data points output by the Lidar unit. - View Dependent Claims (9, 10, 11, 12)
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13. A method comprising:
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collecting a data set comprising a plurality of data points output by a light detection and ranging (Lidar) unit of an autonomous vehicle, each of the data points corresponding to one of multiple targets, each target having a known reflectance value; generating a reflectance inference model for the Lidar unit based on the data set, the generating of the reflectance inference model comprising mapping the plurality of data points to a coordinate system using range and raw intensity values of each data point as coordinates; accessing, by a vehicle computing system of the autonomous vehicle, an incoming data point output by the Lidar unit during operation of the autonomous vehicle; inferring, using the reflectance inference model, a reflectance value of an object based on the incoming data point, the reflectance value being interpolated from at least two data points mapped to the coordinate system; and determining, by the vehicle computing system, a motion plan for the autonomous vehicle based on the inferred reflectance value, the motion plan of the autonomous vehicle being used to control motion of the autonomous vehicle. - View Dependent Claims (14, 15, 16, 17, 18, 19, 20)
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Specification