Baidu Online Network Technology (beijing) Co., Ltd.

Apollo Intelligent Driving Technology (beijing) Co., Ltd.

Jiajia Chen

Tian Xia

Ji Wan

Yang Song

Huadong Li

Chi Tang

Weiyu Chen

Xunliang Cai

A ranging method based on a laser radar system, a device and a readable storage medium are provided. The ranging method includes receiving ranging data obtained by measuring via a plurality of laser radars of a laser radar system, where the ranging data includes distances between the laser radars and obstacles in measurement ranges of the laser radars; establishing a three-dimensional coordinate model according to the ranging data; and determining a distance between a target unmanned device and each obstacle according to the three-dimensional coordinate model. The ranging method can realize a ranging calibration task for a larger distance range, thereby effectively improving a calibration efficiency and accuracy of the visual image algorithm, compared with the existing method of ranging calibration of the visual image algorithm by a single laser radar.

Ranging method based on laser radar system, device and readable storage medium

The present application provides autonomous vehicle based position detection method and apparatus, a device and a medium, where the method includes: identifying an obtained first visual perception image according to an underlying neural network layer in a slender convolution kernel neural network model to determine feature information of the target linear object image, and identifying the feature information of the target linear object image by using a high-level neural network layer in the slender convolution kernel neural network model to determine size information of the target linear object image; further, matching the size information of the target linear object image with preset coordinate system map information to determine a position of the autonomous vehicle. Embodiments of the present application can accurately determine the position of the autonomous vehicle.

Autonomous vehicle based position detection method and apparatus, device and medium

The present disclosure provides a visual perception method, an apparatus, a device and a medium based on an autonomous vehicle, the method includes inputting an obtained first visual perception image collected by the autonomous vehicle into a first neural network model, recognizing multi-channel feature information of at least one target recognition object to be recognized, to eliminate redundant feature information in the first visual perception image; further, inputting the multi-channel feature information of the at least one target recognition object to be recognized into at least one sub-neural network model in a second neural network model respectively, to obtain at least one target recognition object; where there is a one to one correspondence between the target recognition object and the sub-neural network model. The present disclosure improves the speed of recognizing the target recognition object, thereby improving sensitivity of the autonomous vehicle and ensuring driving safety of the autonomous vehicle.

Visual perception method, apparatus, device, and medium based on an autonomous vehicle

An objective of the present invention is providing a method and apparatus for providing recommended information. A method according to the present invention comprises steps of: determining, based on one or more pieces of content information in one or more webpages, whether the one or more pieces of content information may be used as recommended information, respectively; obtaining feature information of the recommended information if the content information is recommended information; determining ordering information of the each piece of recommended information based on the feature information of each piece of recommended information; wherein the method further comprises the following step: if a user's browsing operation on the webpage corresponds to at least one piece of recommended information, presenting the at least one piece of recommended information.

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Beijing, China

Jiajia Chen