Robotic Arm Synchronous Operation System and Method Based on Millimeter-Wave Radar Sensor

Abstract

The present invention discloses a robotic arm synchronous operation system and method based on a millimeter-wave radar sensor. The system includes: a metal device worn on the hand for enhancing the reflection of electromagnetic waves; a millimeter-wave radar sensor for transmitting electromagnetic waves and collecting radar data of the hand; and a host computer for performing intra-frame data processing and inter-frame data processing on the collected radar data to obtain intra-frame information and inter-frame information, acquiring the trajectory information of the hand according to the intra-frame information and the inter-frame information, and controlling the movement of the robotic arm according to the trajectory information. The present invention collects the radar data of the hand through the millimeter-wave radar sensor, and realizes the function of synchronous movement of the user's hand and the robotic arm with low latency under the condition of only based on the radar data. The present invention can be widely applied to the field of robot control technology.

Description

Technical Field

[0001] The present invention relates to the technical field of robot control, and in particular, to a robotic arm synchronous operation system and method based on a millimeter-wave radar sensor. Background Art

[0002] At present, industrial robotic arms are generally controlled by a host computer through a preset motion path, and rarely require real-time synchronous operation by technicians. On the one hand, this is because mechanical synchronous user operations are less applied in industrial practice, and on the other hand, there is no very mature synchronous technology at present. The current related research can be divided into two categories. One is to transmit motion data through wearable devices and let the robotic arm imitate the user's arm for synchronous motion; the other is to apply deep learning based on visual data to extract the skeletal map of the user's arm and then control the related motion of the robotic arm.

[0003] Regarding vision-based recognition, this technology is strongly interfered by environmental light, and the real-time analysis of the current state of the user's arm based on deep learning requires high computing power, which may cause large delays. In addition, ordinary cameras lack depth data and cannot perform flexible synchronous motion on the user's arm movement; regarding synchronization based on wearable devices, on the one hand, the wearable device will affect the user's flexible movement, and on the other hand, the current mainstream solutions generally use a large number of sensors, with high costs and inconvenient wearing. Summary of the Invention

[0004] To at least partly solve one of the technical problems existing in the prior art, the purpose of the present invention is to provide a robotic arm synchronous operation system and method based on a millimeter-wave radar sensor.

[0005] The technical solution adopted by the present invention is as follows:

[0006] A robotic arm synchronous operation system based on a millimeter-wave radar sensor, comprising:

[0007] A metal device, worn on the hand, for enhancing the reflection of electromagnetic waves;

[0008] A millimeter-wave radar sensor, for transmitting electromagnetic waves and collecting radar data of the hand;

[0009] A host computer, for performing in-frame data processing and inter-frame data processing on the collected radar data, obtaining in-frame information and inter-frame information, acquiring the trajectory information of the hand according to the in-frame information and the inter-frame information, and controlling the movement of the robotic arm according to the trajectory information.

[0010] Further, the millimeter-wave radar sensor is arranged on the base of the robotic arm.

[0011] Another technical solution adopted by the present invention is as follows:

[0012] A method for synchronous operation of a robotic arm based on a millimeter-wave radar sensor, comprising the following steps:

[0013] Collect radar data of the hand; wherein the radar data is obtained by the millimeter-wave radar sensor emitting electromagnetic waves and being reflected by the hand wearing a metal device;

[0014] Perform intra-frame data processing and inter-frame data processing on the collected radar data to obtain intra-frame information and inter-frame information;

[0015] Obtain the trajectory information of the hand according to the intra-frame information and the inter-frame information, and control the movement of the robotic arm according to the trajectory information.

[0016] Further, the intra-frame data processing of the collected radar data includes:

[0017] Arrange a frame of radar data in the fast time dimension - slow time dimension - channel dimension to form a three-dimensional array;

[0018] Perform coherent accumulation on the three-dimensional array in the channel dimension to obtain fast time dimension - slow time dimension data;

[0019] Perform a fast Fourier transform on the fast time dimension - slow time dimension data in the fast time dimension and the slow time dimension to obtain a range-Doppler map representing the range-velocity distribution in space;

[0020] Perform a constant false alarm rate algorithm processing on the two dimensions of the range-Doppler map respectively, and the detected points are used as target points;

[0021] According to the range index and velocity index of the target point, obtain the corresponding channel dimension of the target point, and perform fast Fourier transform processing to obtain the angle distribution of the target point relative to the radar sensor, and further obtain the position of the target point in the radar sensor rectangular coordinate system at this moment.

[0022] Further, the fast time domain and the slow time domain are obtained by the following method:

[0023] According to the preset frequency modulation period and radar frame period, divide the time-domain radar signal into three dimensions: fast time domain, slow time domain and ordinary time domain.

[0024] Further, obtaining the position of the target point in the radar sensor rectangular coordinate system at this moment includes:

[0025] Screen the detected target points, select several target points with the strongest energy amplitude as the target points representing the motion states of various parts of the user's hand at this moment, calculate the distances between these target points and normalize them to relative values;

[0026] Find an average centroid of these target points based on the relative values, which serves as the point representing the overall motion condition of the hand.

[0027] Furthermore, the inter-frame data processing of the collected radar data includes:

[0028] Use the average centroid output from each frame of radar data to represent the position of the hand in the coordinate system;

[0029] Use the Kalman filter algorithm to associate the average centroids between frames, track and predict the motion of the average centroid to obtain a smooth motion trajectory of the overall hand.

[0030] Furthermore, the use of the Kalman filter algorithm to associate the average centroids between frames includes:

[0031] Predict the distance D between the first average centroid of the previous frame of radar data and the second average centroid of the current frame of radar data based on the velocity value of the first average centroid th ,

[0032] When the measured distance between the first average centroid and the second average centroid is greater than the sum of the distance D th and the correction threshold R r , it is determined that there is an error in the second average centroid, discard the current frame of radar data, and enable the predicted value obtained by the Kalman filter of the previous frame; otherwise, input the second average centroid into the Kalman filter and predict the distance between the second average centroid and the average centroid of the next frame of radar data.

[0033] Furthermore, the tracking and prediction of the motion of the average centroid includes:

[0034] Perform cumulative processing on the data of the target points. When the accumulated number of radar frames reaches n frames, start relevant processing;

[0035] Accumulate the change in the relative distance of the target points in these n frames of data. When the accumulated change is greater than the motion threshold C th , output the change condition of the relative value to trigger the motion of the end of the robotic arm.

[0036] Furthermore, the control of the motion of the robotic arm according to the trajectory information includes:

[0037] After obtaining the trajectory information, convert the trajectory information from the radar sensor rectangular coordinate system to the robotic arm rectangular coordinate system, and perform a preset ratio conversion on the trajectory information to obtain the final motion trajectory for controlling the motion of the robotic arm.

[0038] The beneficial effects of the present invention are as follows: The present invention collects radar data of the hand through a millimeter-wave radar sensor, and realizes the function of low-latency synchronous movement of the user's hand and the robotic arm based only on the radar data. Description of the Drawings

[0039] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following introduces the relevant technical solution drawings in the embodiments of the present invention or the prior art. It should be understood that the drawings introduced below are only for conveniently and clearly presenting some embodiments of the technical solutions in the present invention. For those skilled in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0040] Figure 1 It is a relative position diagram of the millimeter-wave radar sensor and the robotic arm in the embodiment of the present invention;

[0041] Figure 2 It is a flowchart of in-frame data processing in the embodiment of the present invention;

[0042] Figure 3 It is a flowchart of inter-frame data processing in the embodiment of the present invention;

[0043] Figure 4 It is a schematic diagram of coordinate transformation of the robotic arm synchronous operation system in the embodiment of the present invention;

[0044] Figure 5 It is a schematic diagram of the relative position of the metal device and the millimeter-wave radar sensor in the embodiment of the present invention;

[0045] Figure 6 It is a step flowchart of a method for synchronous operation of a robotic arm based on a millimeter-wave radar sensor in the embodiment of the present invention. Detailed Embodiments

[0046] The following details the embodiments of the present invention. The examples of the embodiments are shown in the drawings, where the same or similar reference numerals represent the same or similar elements or elements with the same or similar functions throughout. The embodiments described below by referring to the drawings are exemplary and are only used to explain the present invention, and should not be construed as a limitation to the present invention. For the step numbers in the following embodiments, they are only set for the convenience of elaboration and explanation, and no limitation is made on the order between the steps. The execution order of each step in the embodiments can be adaptively adjusted according to the understanding of those skilled in the art.

[0047] In the description of the present invention, it should be understood that regarding the orientation description, such as the orientation or positional relationship indicated by up, down, front, back, left, right, etc., is based on the orientation or positional relationship shown in the drawings. It is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation. Therefore, it should not be construed as a limitation to the present invention.

[0048] In the description of the present invention, the meaning of several is one or more, the meaning of multiple is more than two, and understandings such as greater than, less than, exceeding, etc. do not include the number itself, and understandings such as above, below, within, etc. include the number itself. If there is a description of first and second, it is only for the purpose of distinguishing technical features, and cannot be understood as indicating or implying relative importance or implicitly indicating the quantity of the indicated technical features or the sequence relationship of the indicated technical features.

[0049] In the description of the present invention, unless otherwise clearly defined, words such as setting, installing, connecting, etc. should be understood in a broad sense, and those skilled in the art can reasonably determine the specific meanings of the above words in the present invention in combination with the specific content of the technical solution.

[0050] See Figure 1 , this embodiment provides a robotic arm synchronous operation system based on a millimeter-wave radar sensor, including:

[0051] A metal device, worn on the hand, for enhancing the reflection of electromagnetic waves;

[0052] A millimeter-wave radar sensor, for emitting electromagnetic waves and collecting radar data of the hand;

[0053] A host computer, for performing in-frame data processing and inter-frame data processing on the collected radar data, obtaining in-frame information and inter-frame information, acquiring the trajectory information of the hand according to the in-frame information and the inter-frame information, and controlling the movement of the robotic arm according to the trajectory information.

[0054] In this embodiment, the user wears a metal device on the hand that can enhance the reflection ability of electromagnetic waves, and the millimeter-wave radar sensor collects the motion data of the user's hand in real time; the data of the millimeter-wave radar sensor will be transmitted to the host computer in real time for processing to obtain the point where the current arm is located in the global coordinate system. After accumulating a certain amount of radar frame data, a trajectory is formed, and the host computer controls the robotic arm to move to the specified position according to the specified trajectory. Among them, the metal device can be a metal patch, or a metal glove, etc.

[0055] As an alternative embodiment, the millimeter-wave radar sensor is disposed on the base of the robotic arm. The millimeter-wave radar sensor can be disposed at any position. Specifically, disposing the millimeter-wave radar sensor on the base of the robotic arm facilitates subsequent coordinate system transformation and reduces the amount of computation.

[0056] As Figure 6 shown, this embodiment provides a method for synchronous operation of a robotic arm based on a millimeter-wave radar sensor, including the following steps:

[0057] S1. Collect radar data of the hand; wherein the radar data is obtained by the millimeter-wave radar sensor emitting electromagnetic waves and being reflected by the hand wearing a metal device.

[0058] S2. Perform intra-frame data processing and inter-frame data processing on the collected radar data to obtain intra-frame information and inter-frame information.

[0059] S3. Obtain the trajectory information of the hand according to the intra-frame information and the inter-frame information, and control the movement of the robotic arm according to the trajectory information.

[0060] Referring to Figure 2 , according to the detection principle of a frequency-modulated continuous-wave radar (FMCW radar), the radar echo signal reflected from the target can be analyzed in the time dimension and the space dimension. For the analysis in the time dimension, the time-domain radar signal can be divided into three dimensions, namely the fast time domain, the slow time domain, and the ordinary time domain, according to a predefined chirp period and a radar frame period. These three dimensions respectively correspond to the distance, speed of the target, and the distribution of the above two data over time. For the observation within the radar's field of view, it is usually in units of radar frames, which characterizes the distribution of targets within the radar's field of view at that moment in the distance dimension and the speed dimension. For the analysis in the space dimension, it generally refers to the relationship between the radar echo signals obtained on different receiving channels (channels) and the distribution angle of the target point relative to the radar. The data processing within one radar frame period is called intra-frame processing (intra frame processing), and through this process, the distance, speed, and angle distribution information of the target point can generally be obtained.

[0061] For intra-frame data processing, fast Fourier transform (FFT) is performed on the radar data of the frame in the fast-time domain and slow-time domain dimensions respectively to obtain a range-Doppler map (RDM). Subsequently, a constant false alarm rate (CFAR) algorithm is performed in the two dimensions respectively to extract over-detected points as target points. Subsequently, FFT is performed on the channel dimension corresponding to the target points to obtain the angular data of the target points relative to the radar distribution, thereby obtaining the distribution status and motion speed of the target in the actual space at this moment.

[0062] As an alternative implementation, since the user wears a metal device that enhances the reflection intensity on the hand, the over-detected target points are screened, and several target points with the strongest energy amplitude are selected as the target points representing the motion states of each part of the user's hand at this moment. The distances between these target points are calculated and normalized to relative values; and an average centroid of these target points is obtained as the point representing the overall motion status of the user's hand.

[0063] See Figure 3 , inter-frame processing, is mainly used to associate the target points detected at each moment in the ordinary time domain, thereby completely describing the motion state of the target points in time series. For this invention patent, the average centroid output at each moment is used to abstractly represent the position of the user's hand in the coordinate system. The Kalman filtering algorithm is used to associate the inter-frame average centroids and track and predict the motion of the average centroid, thereby obtaining the smooth motion trajectory of the user's hand as a whole, which is used to control the overall motion of the robotic arm.

[0064] As an alternative implementation, for 3 frames of data, the change value C of the relative value of the target points in each frame is accumulated and output together with the coordinates and speed of the smoothed centroid point.

[0065] For the output of the inter-frame processing result, as Figure 1 shown, the data is converted into data for driving the motion of the robotic arm. In this embodiment, it is necessary to convert the radar coordinate system data to the robotic arm coordinate system. The coordinate system relationship is related to the relative position of the hardware. The hardware relationship between the sensor device and the robotic arm is as Figure 4 shown. For the radar sensor data, after accumulating the average centroid movement trajectories of three radar frame periods at the control end, the motion control planning of the robotic arm is performed; according to the specific control planning algorithm, the top of the robotic arm is moved to the average centroid for relevant control. The control planning algorithm of the robotic arm can be implemented by using existing methods.

[0066] The above technical solutions will be explained in detail below in conjunction with specific embodiments.

[0067] See Figure 4 , this embodiment provides a robotic arm synchronous operation system based on a millimeter-wave radar sensor. This system captures the hand movement data of the user based on the millimeter-wave radar sensor, and the host computer makes a robotic arm movement path planning according to these data, and finally controls the robotic arm to perform synchronous movement.

[0068] (1) Hardware arrangement of the robotic arm synchronous operation system

[0069] In this embodiment, the focus is on obtaining the movement trajectory data of the user's hand in a short time from the radar sensor, and controlling the robotic arm to move synchronously with the movement trajectory after reasonable coordinate transformation. Therefore, the hardware arrangement shown in Figure 4 is just an example; when the deployment of the sensor device and the robotic arm changes, only the relevant formulas for coordinate transformation need to be changed. As shown in Figure 4 , the radar sensor is placed on the left side of the robotic arm; when operating, the user's hand wears a metal device and moves within the visible range of the sensor shown in Figure 4 , and the sensor can capture the movement trajectory of the hand at this time.

[0070] (2) In-frame processing of radar raw data

[0071] In this embodiment, this process is mainly a general radar signal processing process; arranging a radar frame data in the fast time dimension - slow time dimension - channel dimension to form a three-dimensional array; first, performing coherent accumulation on this data in the channel dimension to obtain the fast time dimension - slow time dimension data; then performing FFT on this two-dimensional data in the fast time dimension and the slow time dimension respectively, so as to obtain the range-doppler map (RDM) data representing the distance-velocity distribution in space; performing CFAR processing on the two dimensions of the RDM data respectively, and the detected points obtained are the positions where targets may exist in the distance-velocity space; according to the range index and Doppler index of this target, find the corresponding channel dimension of this target point for FFT processing, so as to obtain the angle distribution of this target point relative to the radar sensor, and further obtain the positions of these target points in the right-angle coordinate system of the radar sensor at this moment.

[0072] After solving for the target points, since a metal device is equipped on the user's hand to enhance the reflection intensity of the key points, only several points with the strongest reflection intensity are selected from the over-detected target points as the points representing the hand movement for output; the coordinates of the selected target points are used to calculate the distance and normalize it to represent the relative distances of these points. At the same time, the average centroid of these points is calculated; in summary, the output data of this step are several target points with the strongest intensity and the coordinates, corresponding speeds, and reflection intensities of their average centroid in the right-angle coordinate system of the radar sensor, as well as the relative distances between these several target points.

[0073] (3) Inter-frame processing of radar raw data

[0074] In this embodiment, this process is mainly for the correlation processing of data between different radar frames, mainly deployed on the host computer that controls the radar sensor and the robotic arm. This process mainly further processes the data output from the intra-frame data processing, which can be roughly divided into two parts: smooth centroid calculation and relative value calculation.

[0075] For the smooth centroid part, the average centroid obtained from the processing within each frame is first associated with the average centroid of the previous frame. According to the speed value of the average centroid of the previous frame, the distance D between it and the average centroid of this frame can be roughly predicted. th , when the distance between the two average centroids is greater than the sum of D th and the correction threshold R r , it is determined that the average centroid of this frame is misjudged, and the data of this frame is discarded, and the predicted value obtained by the Kalman filter of the previous frame is enabled; otherwise, the value of this frame is input into the Kalman filter to calculate the smooth centroid of this frame and the predicted value of the next frame; for the relative value calculation part, the received sensor target point data is cumulatively processed, and when the accumulated radar frames reach 3 frames, relevant processing starts. The relative distances of the target points in these 3 frames of data are cumulatively changed. When the cumulative change is greater than the motion threshold C th , the change condition of the relative value is output to trigger the movement of the metal clamp at the top of the robotic arm; except for the initialization part, subsequent calculations are all performed in the form of a sliding window with a step size of 1, taking 3 frames for relative value calculation.

[0076] (4) Target point trajectory - robotic arm synchronous movement

[0077] In this embodiment, this process is mainly used to convert the data representing the user's hand movement trajectory processed by the host computer from the right-angle coordinate system of the radar sensor to the right-angle coordinate system of the robotic arm and control the robotic arm to perform synchronous movement. In Figure 5 's example of hardware placement, the relationship between the right-angle coordinate system of the radar sensor and the right-angle coordinate system of the robotic arm is as Figure 4As shown. Therefore, in this example, the target point needs to be additionally rotated and transformed into the coordinate system of the robotic arm. The host control terminal calculates the next movement trajectory of the robotic arm according to the movement trajectory reflected in the past 7 radar frames and the movement trajectory control algorithm of the robotic arm, and then controls the robotic arm to move according to this trajectory. In addition, according to application requirements, there is a proportional conversion from the movement trajectory of the hand to the movement trajectory depicted by the robotic arm, which specifically depends on the specific settings in the host drive. In this embodiment, it is tentatively determined to depend on the ratio between the robotic arm and the human arm.

[0078] In addition, the host computer converts and controls the real-time opening and closing movement of the metal clamp at the top of the robotic arm according to the change of the relative value in the output data to realize the function of the robotic arm grasping objects. The overall movement of the robotic arm is relatively independent of the movement of the metal clamp.

[0079] It should be noted that, in an ideal situation, this system still has a delay of 5 - 7 radar frames with the movement of the user's hand in theory. However, considering that the radar frame period is generally at the millisecond (ms) level, the user can basically not perceive such a delay. Therefore, the movement of the hand and the movement of the robotic arm are still approximately synchronized in time. In addition to low delay, synchronization also means that the robotic arm can keep the same actions as the user's hand movement in real time.

[0080] In the above description of this specification, the description with reference to terms such as "one embodiment", "another embodiment" or "certain embodiments" etc. means that the specific features, structures, materials or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic expressions of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in a suitable manner in any one or more embodiments or examples.

[0081] Although the embodiments of the present invention have been shown and described, those of ordinary skill in the art can understand that various changes, modifications, substitutions and variations can be made to these embodiments without departing from the principles and purposes of the present invention. The scope of the present invention is defined by the claims and their equivalents.

[0082] The above has specifically described the preferred embodiments of the present invention, but the present invention is not limited to the above embodiments. Those skilled in the art can also make various equivalent deformations or substitutions without departing from the spirit of the present invention, and these equivalent deformations or substitutions are all included in the scope defined by the claims of this application.

Claims

1. A method for the synchronous operation of a robotic arm based on a millimeter-wave radar sensor, characterized in that, It includes the following steps: Collect radar data of the hand; wherein the radar data is obtained by the millimeter-wave radar sensor emitting electromagnetic waves and being reflected by the hand wearing a metal device; Perform intra-frame data processing and inter-frame data processing on the collected radar data to obtain intra-frame information and inter-frame information; Obtain the trajectory information of the hand according to the intra-frame information and the inter-frame information, and control the movement of the robotic arm according to the trajectory information; The intra-frame data processing of the collected radar data includes: Arrange a frame of radar data in the fast time dimension - slow time dimension - channel dimension to form a three-dimensional array; Perform coherent accumulation on the three-dimensional array in the channel dimension to obtain fast time dimension - slow time dimension data; Perform fast Fourier transform on the fast time dimension - slow time dimension data in both the fast time dimension and the slow time dimension to obtain a range-Doppler map representing the range-velocity distribution in space; Perform constant false alarm rate algorithm processing on the two dimensions of the range-Doppler map respectively, and the detected points are used as target points; according to the range index and velocity index of the target points, obtain the corresponding channel dimension of the target points, and perform fast Fourier transform processing to obtain the angle distribution of the target points relative to the radar sensor, and then obtain the position of the target points in the radar sensor rectangular coordinate system in the current radar frame.

2. The method for synchronous operation of a robotic arm based on a millimeter-wave radar sensor according to claim 1, wherein The fast time domain and the slow time domain are obtained by the following method: According to a preset frequency modulation period and radar frame period, divide the time-domain radar signal into three dimensions: fast time domain, slow time domain, and ordinary time domain.

3. The method for synchronous operation of a robotic arm based on a millimeter-wave radar sensor according to claim 1, wherein Obtaining the position of the target points in the radar sensor rectangular coordinate system in the current radar frame includes: Screen the detected target points, select several target points with the strongest energy amplitude as the target points representing the movement states of various parts of the user's hand in the current radar frame, calculate the distances between these target points and normalize them to relative values; Find an average centroid of these target points according to the relative values as the point representing the overall movement condition of the hand.

4. The method for synchronous operation of a robotic arm based on a millimeter-wave radar sensor according to claim 1, wherein The inter-frame data processing of the collected radar data includes: Use the average centroid output by each frame of radar data to represent the position of the hand in the coordinate system; Use the Kalman filter algorithm to correlate the average centroids between frames, track and predict the movement of the average centroids to obtain a smooth movement trajectory of the whole hand.

5. The method for synchronous operation of a robotic arm based on a millimeter-wave radar sensor according to claim 4, wherein The use of the Kalman filter algorithm to correlate the average centroids between frames includes: Predict the distance D between the first average centroid and the second average centroid of the current frame radar data based on the velocity value of the first average centroid of the previous frame radar data th , When the measured distance between the first average centroid and the second average centroid is greater than the sum of the distance D th and the correction threshold R r it is determined that there is an error in the second average centroid, the current frame of radar data is discarded, and the predicted value obtained by the Kalman filter of the previous frame is enabled; otherwise, the second average centroid is input into the Kalman filter, and the distance between the second average centroid and the average centroid of the next frame of radar data is predicted.

6. The method for synchronous operation of a robotic arm based on a millimeter-wave radar sensor according to claim 4, wherein The tracking and prediction of the movement of the average centroid includes: Accumulate the data of the target point, and start relevant processing when the accumulated radar frames reach n frames; Accumulate the change in the relative distance of the target point in these n frames of data. When the accumulated change is greater than the motion threshold C th , then output the change condition of the relative value to trigger the motion of the end of the robotic arm.

7. A method for synchronous operation of a robotic arm based on a millimeter-wave radar sensor according to claim 1, characterized in that Controlling the movement of the robotic arm according to the trajectory information includes: After obtaining the trajectory information, convert the trajectory information from the radar sensor rectangular coordinate system to the robotic arm rectangular coordinate system, and perform a conversion of a preset ratio on the trajectory information to obtain the final movement trajectory for controlling the movement of the robotic arm.

8. A robotic arm synchronous operation system based on a millimeter-wave radar sensor, which is applied to a robotic arm synchronous operation method based on a millimeter-wave radar sensor according to any one of claims 1-7, characterized in that, including: A metal device, worn on the hand, for enhancing the reflection of electromagnetic waves; A millimeter-wave radar sensor, for emitting electromagnetic waves and collecting radar data of the hand; A host computer, for performing intra-frame data processing and inter-frame data processing on the collected radar data, obtaining intra-frame information and inter-frame information, acquiring the trajectory information of the hand according to the intra-frame information and the inter-frame information, and controlling the movement of the robotic arm according to the trajectory information.

9. A robotic arm synchronous operation system based on a millimeter-wave radar sensor according to claim 8, characterized in that, The millimeter-wave radar sensor is arranged on the base of the robotic arm.

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