CN-116922381-B - Mechanical arm control method and device for surgical robot and terminal

CN116922381BCN 116922381 BCN116922381 BCN 116922381BCN-116922381-B

Abstract

The application relates to the technical field of communication networks, and provides a mechanical arm control method, a device and a terminal for a surgical robot. The method is applied to a control platform and comprises the steps of obtaining a first state value set corresponding to a mechanical arm of a surgical robot in operation, wherein the first state value set comprises a plurality of first state value sequences corresponding to the mechanical arm and respective first weights, sampling the first state value sequences to obtain a plurality of second state value sequences, determining the respective second weights of the second state value sequences according to importance sampling density and posterior probability corresponding to the first state value set, determining a target network slice according to the second state value sequences and all the second weights, and controlling the mechanical arm to operate through the target network slice. The target network slice determined by the method has the advantages of large bandwidth, low time delay and the like, and further, when the mechanical arm is controlled to operate according to the target network slice, the operation efficiency of the mechanical arm can be effectively improved.

Inventors

LI PEIRAN
SUN FANGJIE
MA HE
PAN SHIWEI
LIU SONGTAO
DAI WEI
PENG ZHAN
LI CHUANG
ZHANG RUI
XU ZHEFENG

Assignees

中国移动通信集团黑龙江有限公司
中国移动通信集团有限公司

Dates

Publication Date: 20260512
Application Date: 20230714

Claims (10)

1. A method of controlling a robotic arm for a surgical robot, applied to a control platform, the method comprising: Acquiring a first state value set corresponding to a mechanical arm of a surgical robot in operation, wherein the first state value set comprises a plurality of first state value sequences corresponding to the mechanical arm and first weights of the first state value sequences; sampling the plurality of first state value sequences to obtain a plurality of second state value sequences; determining respective second weights of the plurality of second state value sequences according to the importance sampling density and the posterior probability corresponding to the first state value set, including: ; Wherein, the Representing the first of a plurality of second state value sequences The second state value is in sequence of A second weight at the time instant, Representing the first of a plurality of second state value sequences The second state value is in sequence of A second weight at the time instant, Representing the posterior probability of the x factor after the y factor occurs, Represents the importance sampling density of the x factor after the y factor occurs, Indicating that the end effector of the mechanical arm is from 0 to The corresponding sequence of observations at runtime, Indicating that the end effector of the mechanical arm is from 0 to Corresponding first time of time operation A first sequence of state values is provided, Representing a robotic end effector slave To the point of Corresponding first time of time operation A first sequence of state values; Indicating that the end effector of the mechanical arm is in An observation value at a time; Wherein the posterior probability is determined based on the plurality of first state value sequences and all first weights; and determining a target network slice according to the second state value sequences and all the second weights, and controlling the mechanical arm to operate through the target network slice.
2. The method of claim 1, wherein determining the target network slice from the plurality of second state value sequences and all second weights comprises: For each second state value sequence, determining information entropy corresponding to the second state value sequence according to the second state value sequence and second weight of the second state value sequence; ordering the information entropy larger than a first preset entropy threshold value in all the information entropy in a descending order to obtain an entropy sequence; determining target information entropy meeting a second preset entropy threshold value from the entropy sequence; and determining the network slice corresponding to the target information entropy as the target network slice.
3. The method for controlling a robotic arm of claim 2, wherein the determining, from the entropy sequence, a target information entropy that satisfies a second preset entropy threshold comprises: Determining the absolute value of a difference value between a first information entropy and a second information entropy in the entropy sequence, wherein the first information entropy is smaller than the second information entropy, and the first information entropy is adjacent to the second information entropy; And determining the first information entropy as the target information entropy under the condition that the ratio between the absolute value of the difference value and the absolute value of the first information entropy is larger than the second preset entropy threshold.
4. A method of controlling a manipulator for a surgical robot according to claim 2 or 3, wherein the determining the network slice corresponding to the target information entropy as the target network slice includes: Acquiring an element information set in a network slice corresponding to the target information entropy; and removing redundancy from the element information set to obtain the target network slice.
5. A method of controlling a robotic arm for a surgical robot according to any of claims 1-3, wherein said determining a target network slice from said plurality of second state value sequences and all second weights comprises: Constructing a second state value set according to the plurality of second state value sequences and all second weights; The step of determining the second weight of each of the plurality of second state value sequences according to the importance sampling density and the posterior probability corresponding to the first state value set until the corresponding target state value set when the preset times are reached is determined; And determining the target network slice according to the target state value set.
6. A method of controlling a robotic arm for a surgical robot according to any one of claims 1-3, wherein said sampling the plurality of first state value sequences to obtain a plurality of second state value sequences comprises: determining a plurality of target first weights which are larger than a preset weight threshold value in all the first weights; and determining the first state value sequences of the first weights of the targets as the second state value sequences.
7. A robot arm control device for a surgical robot, characterized by being configured to perform the robot arm control method for a surgical robot according to claim 1, comprising: The state observation module is used for acquiring a first state value set corresponding to a mechanical arm of the surgical robot in operation, wherein the first state value set comprises a plurality of first state value sequences corresponding to the mechanical arm and first weights of the first state value sequences: The particle filtering calculation module is used for sampling the plurality of first state value sequences to obtain a plurality of second state value sequences, determining the second weights of the plurality of second state value sequences according to the importance sampling density and the posterior probability corresponding to the first state value set, wherein the posterior probability is determined based on the plurality of first state value sequences and all the first weights; and the network slice management module is used for controlling the mechanical arm to run through the target network slice.
8. A terminal comprising a memory, a transceiver, and a processor; A processor for reading the computer program in the memory and performing the steps of the robot arm control method for a surgical robot according to any one of claims 1 to 6.
9. A control platform comprising a processor and a memory storing a computer program, characterized in that the processor implements the steps of the robotic arm control method for a surgical robot according to any one of claims 1 to 6 when executing the computer program.
10. A computer program product comprising a computer program, characterized in that the computer program, when being executed by a processor, realizes the steps of the robot arm control method for a surgical robot according to any one of claims 1 to 6.

Description

Mechanical arm control method and device for surgical robot and terminal Technical Field The application relates to the technical field of communication networks, in particular to a mechanical arm control method, a device and a terminal for a surgical robot. Background Teleoperated surgical robots based on the fifth generation communication technology (the 5 Generation mobile communication technology,5G) are a new type of robots proposed to improve the complexity and limitations of traditional surgery. The 5G has the characteristic of large bandwidth, can effectively acquire three-dimensional (3D) high-definition images so as to improve the image definition of an operation part, and the 5G has the characteristic of low time delay, can effectively eliminate the problem of vibration of the mechanical arm end effector, and at the moment, the mechanical arm end effector can surpass a human hand to carry out fine operation in a narrow space which cannot be touched originally. In addition, 5G Network slicing (Network Slice) is a functional definition implemented by a number of custom software functions including geographic coverage area, duration, capacity, speed, latency, reliability, security, availability, and the like. In the process of controlling the operation of the mechanical arm of the surgical robot, a better 5G network slice needs to be configured to meet the technical requirements of large bandwidth, low time delay and the like so as to improve the operation efficiency of the mechanical arm. Disclosure of Invention The embodiment of the application provides a mechanical arm control method, a device and a terminal for a surgical robot, which are used for solving the technical problem that the operation efficiency is low when the mechanical arm of the surgical robot is operated due to certain limitation of the existing network slice. And after resampling the state value sequence of the mechanical arm, determining a target network slice according to the resampled state value sequence. In the process of resampling the state value sequence, the state value sequence is reassigned from a low-density region to a high-density region, so that the degradation problem of the state value sequence is solved, the state value sequence is optimized to a great extent, and the optimal network slice corresponding to the mechanical arm of the surgical robot in operation, namely a target network slice, is determined, and has the advantages of large bandwidth, low time delay and the like, so that the operation efficiency of the mechanical arm can be effectively improved when the mechanical arm is controlled to operate according to the target network slice. In a first aspect, an embodiment of the present application provides a method for controlling a mechanical arm of a surgical robot, applied to a control platform, the method including: Acquiring a first state value set corresponding to a mechanical arm of a surgical robot in operation, wherein the first state value set comprises a plurality of first state value sequences corresponding to the mechanical arm and first weights of the first state value sequences; sampling the plurality of first state value sequences to obtain a plurality of second state value sequences; Determining second weights of the second state value sequences according to importance sampling density and posterior probability corresponding to the first state value set, wherein the posterior probability is determined based on the first state value sequences and all the first weights; and determining a target network slice according to the second state value sequences and all the second weights, and controlling the mechanical arm to operate through the target network slice. In one embodiment, determining the target network slice according to the plurality of second state value sequences and all second weights includes determining, for each second state value sequence, an information entropy corresponding to the second state value sequence according to the second state value sequence and the second weights of the second state value sequence, ordering information entropies greater than a first preset entropy threshold in all information entropies in a descending order to obtain an entropy sequence, determining a target information entropy meeting a second preset entropy threshold from the entropy sequence, and determining the network slice corresponding to the target information entropy as the target network slice. In one embodiment, the determining the target information entropy meeting the second preset entropy threshold from the entropy sequence comprises determining an absolute value of a difference value between a first information entropy and a second information entropy in the entropy sequence, wherein the first information entropy is smaller than the second information entropy, the first information entropy is adjacent to the second information entropy, and determining the first information entropy a