Data storage and backtracking platform for N3 sweepers

Abstract

The invention discloses a data storage and backtracking platform for N3 electric sweepers. The data storage and backtracking platform is composed of an online end and an offline end. The online end isused for carrying out data online acquisition and storage on the road garbage information, collecting the current upload gear operation of the sweeper, providing data for the upload gear selection module and providing the optimal upload gear selection under the current garbage scene for the online vehicle speed optimization control module so as to realize decoupling of the upload operation and vehicle speed control; the off-line end performs uploading gear selection algorithm training by utilizing the data collected by the on-line end to obtain relevant parameters in an uploading gear selection algorithm and send the relevant parameters to the on-line end uploading gear selection module for iteratively updating an uploading gear control algorithm of the on-line end; the neural network parameters from the online vehicle speed optimization control modules of the plurality of sweepers are fused and then transmitted to each sweeper; and the on-line end and the off-line end realize data transmission through a control information updating system.

Description

technical field [0001] The invention relates to the field of intelligent control of sweeping vehicles, in particular to a data storage and backtracking platform for N3 sweeping vehicles. Background technique [0002] At present, in order to realize the intelligentization of road operations of N3 pure electric sweepers, it is necessary to: (1) conduct a power matching test in advance, artificially arrange the scene and select the best gear to obtain the power matching test data; (2) use these power matching The test data trains a power matching model to simulate the driver's operating behavior; (3) During the actual cleaning operation, the types of road garbage in the current scene and the coverage information corresponding to each type based on the output of the visual sensor and the perception algorithm are input into the In the model obtained by power matching test data training, the bodywork system gear required by the current scene is automatically output. [0003] The ...

AI Technical Summary

Problems solved by technology

[0003] The technical route of the intelligent operation of this sweeping vehicle has the following problems: (1) The number and types of artificially arranged scenes cannot truly reflect the complex and diverse road conditions, resulting in the data of the power matching test cannot truly reflect the actual road surface, thus affecting The precision and accuracy of the trained power matching model; (2) Each power matching test needs to set up the scene first and then select the best gear for operation, which means that obtaining power matching data requires a lot of manpower, material resources and Time cost, which also makes the power matching model unable to be continuously updated

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