Object detection based on Lidar intensity
First Claim
1. An autonomous vehicle (AV) computing system comprising:
- a reflectance inference system comprising one or more processors, the reflectance inference system to perform operations comprising;
accessing an incoming data point output by a light detection and ranging (Lidar) unit during operation of the AV computing system;
determining, using a reflectance inference model generated by a Lidar calibration system, an inferred 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 inferred 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; and
a motion planning system comprising one or more processors, the motion planning system to determine a motion plan for an AV based on the one or more characteristics of the object, the motion plan being used to control motion of the AV.
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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
18 Claims
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1. An autonomous vehicle (AV) computing system comprising:
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a reflectance inference system comprising one or more processors, the reflectance inference system to perform operations comprising; accessing an incoming data point output by a light detection and ranging (Lidar) unit during operation of the AV computing system; determining, using a reflectance inference model generated by a Lidar calibration system, an inferred 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 inferred 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; and a motion planning system comprising one or more processors, the motion planning system to determine a motion plan for an AV based on the one or more characteristics of the object, the motion plan being used to control motion of the AV. - 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 a Lidar unit, each of the data points corresponding to one of multiple targets, each target having a known reflectance value, each channel of the Lidar unit being capable of operating at a plurality of power levels, the collecting of the data set including collecting data points output by each channel at each power level; 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, the generating of the reflectance inference model includes generating multiple mappings of the plurality of data points to the coordinate system, each mapping corresponding to a particular power level of a particular channel. - View Dependent Claims (9, 10)
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11. A method comprising:
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collecting, by a Lidar calibration system comprising at least a first hardware processor, 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, by the Lidar calibration system, 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 reflectance inference system of a vehicle computing system comprising at least a second hardware processor, an incoming data point output by the Lidar unit during operation of the autonomous vehicle; determining, by the reflectance inference system and using the reflectance inference model, an inferred reflectance value of an object based on the incoming data point, the inferred reflectance value being interpolated from at least two data points mapped to the coordinate system; and determining, by a motion planning system of 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 (12, 13, 14, 15, 16, 17, 18)
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Specification