Unmanned vehicle positioning method, device, equipment and medium based on multi-feature mapping
An unmanned vehicle and multi-feature technology, which is applied in the directions of measuring devices, electromagnetic wave reradiation, character and pattern recognition, etc., can solve the problems of poor scalability and large storage space
Active Publication Date: 2021-01-12
NAT UNIV OF DEFENSE TECH
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[0005] Based on this, it is necessary to address the above technical problems and provide an unmanned vehicle positioning method, device, and computer based on multi-feature mapping that can solve the problems of large storage space and poor scalability for unmanned vehicle high-precision positioning technology. Devices and Storage Media
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[0041] In order to make the purpose, technical solution and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present application, and are not intended to limit the present application.
[0042] The unmanned vehicle positioning method based on multi-feature mapping provided by this application can be applied in the following application environments. Collect various sensor data when the unmanned vehicle is driving in different locations, including image data, radar data, etc. For each position of the unmanned vehicle, a variety of features are extracted respectively, and the features are represented as feature vectors, and each feature vector is used as a training sample, and the hierarchical clustering method is used for clustering, and the corresponding f...
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The present application relates to an unmanned vehicle positioning method, device, computer equipment and storage medium based on multi-feature mapping. The method includes: extracting multiple feature vectors from sensor data collected in the driving environment of the unmanned vehicle, and using each feature vector as a training sample, performing clustering using a hierarchical clustering method, and obtaining each feature corresponding to The decision tree of the decision tree, and for each branch node of the decision tree, train a two-category support vector machine to obtain the decision tree classifier corresponding to each feature. Extract a variety of real-time feature vectors corresponding to the sensor data collected in real time, and input the feature vectors into the corresponding decision tree classifiers to obtain the uncertainty ranges corresponding to each feature. The intersection of uncertain ranges determines the positioning result of the unmanned vehicle. The method described in this application has the advantages of small required storage space and good scalability.
Description
technical field [0001] The present application relates to the technical field of unmanned vehicle positioning, in particular to a method, device, computer equipment and storage medium for unmanned vehicle positioning based on multi-feature mapping. Background technique [0002] As an emerging technology combining artificial intelligence and automation technology, unmanned driving technology has gradually become an important driving force to promote the upgrading of the automobile industry and the penetration of robot technology into ordinary people's homes. High-precision positioning is the first problem that needs to be solved in today's unmanned driving system. [0003] Among the existing high-precision positioning technologies for unmanned vehicles, there are satellite signal (GNSS) and inertial navigation system INS (Inertial Navigation System) combined positioning methods, the use of lidar to build high-precision maps and then matching positioning methods, and the use o...
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IPC IPC(8): G06K9/62G01S17/89G01S17/86G01S7/48
CPCG01S17/89G01S17/86G01S7/4802G06F18/2411G06F18/24323G06F18/253G06F18/214
Inventor 吴涛李侍珍付浩叶磊
Owner NAT UNIV OF DEFENSE TECH