PATH OPTIMIZATION METHOD AND SYSTEM FOR MOBILE ROBOT

    公开(公告)号:US20240208543A1

    公开(公告)日:2024-06-27

    申请号:US18545979

    申请日:2023-12-19

    IPC分类号: B60W60/00

    CPC分类号: B60W60/0023 B60W60/0021

    摘要: A path optimization method for a mobile robot is provided, including: acquiring path information of the mobile robot; processing the path information through a preset path optimization model to obtain path optimization nodes; calculating an optimal path of the mobile robot through the path optimization nodes and feeding the optimal path back to a control terminal; and extracting optimization parameters of the optimal path of the mobile robot, and transmitting the optimization parameters to the preset path optimization model for iterations.

    CONTROL METHOD AND CONTROL SYSTEM BASED ON MOBILE ROBOT

    公开(公告)号:US20240123628A1

    公开(公告)日:2024-04-18

    申请号:US18474790

    申请日:2023-09-26

    摘要: A control method and a control system based on a mobile robot are provided, which correspondingly obtain first feature information and second feature information according to a specific target object and a face region of the user present in region environment, and a delivery request message is sent to the mobile robot; the obstacle presence information is obtained during moving process of mobile robot along the moving path so as to adjust moving state of mobile robot; the corresponding third feature information is obtained according to the image of current region of mobile robot; whether the mobile robot performs an article unloading operation is controlled according to a comparison result between the third feature information and the second feature information; the efficient transportation paths are chose according to the moving path of the mobile robot, and the real-time situation of the destinations may be verified.

    METHOD FOR DETECTING INFECTION STAGE OF ANTHRACNOSE PATHOGENIC WITH PRE-ANALYSIS CAPACITY

    公开(公告)号:US20230133055A1

    公开(公告)日:2023-05-04

    申请号:US17710918

    申请日:2022-03-31

    IPC分类号: G06T7/00

    摘要: Disclosed is a method for detecting an infection stage of anthracnose pathogen with pre-analysis capacity, comprising: obtaining a plurality of sample sensing data sequences; obtaining a sample citrus leaf image; obtaining a first prediction result; if the first prediction result is that the sample citrus crop is not infected by anthracnose, obtaining sample Raman spectral data and sample hyperspectral data; obtaining a first judgment result, and obtaining a second judgment result; performing labeling to obtain second training data; training a neural network model to obtain a second anthracnose prediction model; obtaining a plurality of to-be-analyzed sensing data sequences; obtaining a to-be-analyzed citrus leaf image; obtaining a second prediction result; if the second prediction result is that the to-be-analyzed citrus crop is not infected by anthracnose, obtaining a third prediction result.

    Method and apparatus for differentially optimizing quality of service QoS

    公开(公告)号:US11616702B2

    公开(公告)日:2023-03-28

    申请号:US17729318

    申请日:2022-04-26

    摘要: A method and apparatus for differentially optimizing a quality of service (QoS) includes: establishing a system model of a multi-task unloading framework; acquiring a mode for users executing a computation task, executing, according to the mode for users executing the computation task, the system model of the multi-task unloading framework; and optimizing a quality of service (QoS) on the basis of a multi-objective optimization method for a multi-agent deep reinforcement learning. According to the present invention, an unloading policy is calculated on the basis of a multi-user differentiated QoS of a multi-agent deep reinforcement learning, and with the differentiated QoS requirements among different users in a system being considered, a global unloading decision is performed according to a task performance requirement and a network resource state, and differentiated performance optimization is performed on different user requirements, thereby effectively improving a system resource utilization rate and a user service quality.

    METHOD AND APPARATUS FOR DIFFERENTIALLY OPTIMIZING QUALITY OF SERVICE QoS

    公开(公告)号:US20220400062A1

    公开(公告)日:2022-12-15

    申请号:US17729318

    申请日:2022-04-26

    摘要: A method and apparatus for differentially optimizing a quality of service (QoS) includes: establishing a system model of a multi-task unloading framework; acquiring a mode for users executing a computation task, executing, according to the mode for users executing the computation task, the system model of the multi-task unloading framework; and optimizing a quality of service (QoS) on the basis of a multi-objective optimization method for a multi-agent deep reinforcement learning. According to the present invention, an unloading policy is calculated on the basis of a multi-user differentiated QoS of a multi-agent deep reinforcement learning, and with the differentiated QoS requirements among different users in a system being considered, a global unloading decision is performed according to a task performance requirement and a network resource state, and differentiated performance optimization is performed on different user requirements, thereby effectively improving a system resource utilization rate and a user service quality.