Sensor control method, device and system

Abstract

The embodiment of the invention provides a sensor control method, device and system. The sensor control method comprises the following steps: acquiring movement information of intelligent equipment; determining frequency information and target bridges according to the movement information, wherein the M bridges comprise the target bridges; and sending the frequency information to the target bridge to indicate the target bridge to control the output frequency of the sensor connected with the target bridge according to the frequency information. According to the method and the device, the problem that the complexity of the controller is high due to the fact that the number of sensors on the intelligent equipment is large and the number of interfaces of the controller is large is solved, and the effects of reducing the number of the interfaces of the controller and reducing the complexity of the controller are achieved.

Description

Technical Field

[0001] Embodiments of the present invention relate to the field of communications, and more particularly, to a method and an apparatus. Background Art

[0002] With the development of artificial intelligence and the continuous progress of intelligent device technology (including devices controlled by artificial intelligence, such as robots and drones), higher requirements are put forward for their ability to move autonomously and avoid obstacles in complex environments.

[0003] In order to achieve all-directional autonomous movement and obstacle avoidance of intelligent devices, it is usually necessary to measure multiple directions of intelligent devices. For example, measure the six directions of the front, back, up, down, left, and right of the intelligent device, and use multiple sensors to measure each direction, so as to achieve autonomous movement and obstacle avoidance. In this way, a large number of sensors need to be accessed, which poses high requirements on the interface quantity and processing capacity of the controller for sensors, resulting in limitations in the selection of SOC, or the need to use multiple SOCs for data processing, thereby increasing the complexity, volume, weight, and power consumption of the system, and also increasing the cost. In addition, the data synchronization problem between sensors further affects the performance of the system.

[0004] In view of the above problems, there is currently no effective solution. Summary of the Invention

[0005] Embodiments of the present invention provide a sensor control method, apparatus, and system to at least solve the problem in related technologies that due to the large number of sensors on intelligent devices, a large number of controller interfaces are required, resulting in high controller complexity.

[0006] According to an embodiment of the present invention, a sensor control method is provided, which is applied to a controller in an intelligent device. The intelligent device includes N directions, and the N directions include N groups of sensors. The N groups of sensors are connected to the controller through M bridges. N is an integer greater than 0, and M is an integer greater than 0 and less than N. The method includes: obtaining movement information of the intelligent device; determining frequency information and a target bridge according to the movement information, where the M bridges include the target bridge; and sending the frequency information to the target bridge to instruct the target bridge to control the output frequency of the sensors connected thereto according to the frequency information.

[0007] In an exemplary embodiment, the movement information includes a movement speed. Determining the frequency information according to the movement information includes: mapping the movement speed to Z directions among the N directions of the intelligent device to obtain speed values in the Z directions, where Z is an integer greater than 0 and less than or equal to N; and determining the frequency information according to the speed values in the Z directions.

[0008] In an exemplary embodiment, determining the frequency information based on the velocity values in the Z directions includes: determining the main direction as the direction with the maximum velocity value among the Z directions, and determining the directions other than the main direction as secondary directions; determining first frequency information of the main direction and second frequency information of the secondary directions.

[0009] In an exemplary embodiment, determining the first frequency information of the main direction includes: determining a first trigger ratio of the main direction; or, determining a first trigger ratio and a first sampling ratio of the main direction; wherein, the first frequency information includes the first trigger ratio and the first sampling ratio.

[0010] In an exemplary embodiment, determining the first trigger ratio of the main direction includes: setting the first trigger ratio as a preset trigger ratio; determining the first sampling ratio of the main direction includes: setting the first sampling ratio as a first target value, the first target value being greater than a preset sampling ratio, and the greater the velocity value in the main direction, the greater the first target value.

[0011] In an exemplary embodiment, determining the second frequency information of the secondary direction includes: determining a second trigger ratio of the secondary direction; or, determining a second trigger ratio and a second sampling ratio of the secondary direction; wherein, the second frequency information includes the second trigger ratio and the second sampling ratio.

[0012] In an exemplary embodiment, determining the second frequency information of the secondary direction includes: determining the second sampling ratio of the secondary direction includes: setting the second sampling ratio as a preset sampling ratio; determining the second trigger ratio of the secondary direction includes: setting the second trigger ratio as a second target value, the second target value being less than a preset trigger ratio, and the smaller the velocity value in the secondary direction, the smaller the second target value.

[0013] In an exemplary embodiment, the movement information includes a movement direction, and determining a target bridge among the M bridges according to the movement information includes: mapping the movement direction to Z directions among the N directions of the intelligent device, where Z is an integer greater than 0 and less than or equal to N; determining the bridges connected to the Z sets of sensors in the Z directions as the target bridge, where the number of target bridges is one or more.

[0014] In an exemplary embodiment, a set of sensors includes K sensors, K being an integer greater than or equal to 1, and the K sensors in a set of sensors are arranged in one direction of the intelligent device.

[0015] According to another embodiment of the present invention, a sensor control method is provided, which is applied to the target bridge in the above embodiment and includes: receiving the frequency information from the controller; controlling the output frequency of the target group of sensors connected to the target bridge according to the frequency information, where the target group of sensors is arranged in the target direction of the intelligent device, and the speed value of the intelligent device in the target direction is greater than 0.

[0016] In an exemplary embodiment, the frequency information includes a trigger ratio, or the frequency information includes the trigger ratio and a sampling ratio.

[0017] In an exemplary embodiment, controlling the output frequency of the target group of sensors connected to the target bridge according to the trigger ratio includes: obtaining a preset trigger frequency, and determining the product of the preset trigger frequency and the trigger ratio as the target trigger frequency, where the output frequency includes the target trigger frequency;

[0018] Controlling the output frequency of the target group of sensors connected to the target bridge according to the sampling ratio includes: obtaining a preset sampling frequency, and determining the product of the preset sampling frequency and the sampling ratio as the target sampling frequency, where the output frequency includes the target sampling frequency;

[0019] Wherein, the target trigger frequency is the frequency of a trigger signal, and the trigger signal is used to trigger the target group of sensors to collect data, and the target sampling frequency is used to sample the data collected by the target group of sensors.

[0020] According to another embodiment of the present invention, a sensor control device is provided, which is applied to the controller in the above embodiment and includes: an acquisition module, configured to acquire the movement information of the intelligent device; a determination module, configured to determine frequency information and a target bridge according to the movement information, where the M bridges include the target bridge; a sending module, configured to send the frequency information to the target bridge to instruct the target bridge to control the output frequency of the sensors connected thereto according to the frequency information.

[0021] According to another embodiment of the present invention, a sensor control device is provided, which is applied to the target bridge in the above embodiment and includes: a receiving module, configured to receive the frequency information from the controller; a control module, configured to control the output frequency of the target group of sensors connected to the target bridge according to the frequency information, where the target group of sensors is arranged in the target direction of the intelligent device, and the speed value of the intelligent device in the target direction is greater than 0.

[0022] According to another embodiment of the present invention, a sensor control system is provided, which includes the controller, M bridges and N groups of sensors in the above embodiment.

[0023] According to another embodiment of the present invention, there is also provided a computer-readable storage medium storing a computer program, wherein when the computer program is executed by a processor, the steps of the method described in any one of the above are implemented.

[0024] According to another embodiment of the present invention, there is also provided an electronic device including a memory and a processor, wherein a computer program is stored in the memory, and the processor is configured to run the computer program to execute the steps in any one of the above method embodiments.

[0025] According to another embodiment of the present invention, there is also provided a computer program product including a computer program, wherein when the computer program is executed by a processor, the steps of the method described in any one of the above are implemented.

[0026] Through the present invention, the intelligent device includes N directions, and the N directions include N groups of sensors. Since the N groups of sensors are connected to the controller through M bridges, where N is an integer greater than 0 and M is an integer greater than 0 and less than N. The purpose of reducing the number of controller interfaces is achieved.

[0027] The controller obtains the movement information of the intelligent device; determines the frequency information and the target bridge according to the movement information, and the M bridges include the target bridge; sends the frequency information to the target bridge to instruct the target bridge to control the output frequency of the sensors connected thereto according to the frequency information. Since the target bridge controls the output frequency of the sensors connected thereto, the complexity of the controller is reduced. Therefore, the problem of high controller complexity caused by the large number of sensors on the intelligent device requiring a large number of controller interfaces can be solved, and the effect of reducing the number of controller interfaces and lowering the controller complexity is achieved. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 is a hardware structure block diagram of a mobile terminal of a sensor control method according to an embodiment of the present invention;

[0029] Figure 2 is a flowchart of a sensor control method according to an embodiment of the present invention;

[0030] Figure 3 is an architecture diagram of a sensor control system according to an embodiment of the present invention;

[0031] Figure 4 is a schematic diagram of speed directions according to an embodiment of the present invention;

[0032] Figure 5 is a schematic diagram of bridge design of a drone according to an embodiment of the present invention;

[0033] Figure 6It is a structural block diagram of a device according to an embodiment of the present invention. Detailed implementation manners

[0034] In the following, embodiments of the present invention will be described in detail with reference to the accompanying drawings and in combination with embodiments.

[0035] It should be noted that the terms "first", "second", etc. in the description and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and do not necessarily need to be used to describe a specific order or sequence.

[0036] The method embodiments provided in the embodiments of the present application can be executed on a mobile terminal, a computer terminal or a similar computing device. Taking running on a mobile terminal as an example, Figure 1 It is a hardware structural block diagram of a mobile terminal of a sensor control method according to an embodiment of the present invention. As Figure 1 shown, the mobile terminal may include one or more ( Figure 1 only one is shown in the figure) processors 102 (the processor 102 may include, but is not limited to, a processing device such as a microprocessor MCU or a programmable logic device FPGA) and a memory 104 for storing data. Among them, the above-mentioned mobile terminal may further include a transmission device 106 for communication functions and an input / output device 108. Those of ordinary skill in the art can understand that Figure 1 the structure shown is only schematic and does not limit the structure of the above-mentioned mobile terminal. For example, the mobile terminal may further include more or fewer components than Figure 1 shown in the figure, or have a different configuration from Figure 1 shown in the figure.

[0037] The memory 104 can be used to store computer programs. For example, software programs and modules of application software, such as the computer program corresponding to the sensor control method in the embodiments of the present invention. The processor 102 executes various functional applications and data processing by running the computer program stored in the memory 104, that is, implements the above-mentioned method. The memory 104 may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memories, or other non-volatile solid-state memories. In some instances, the memory 104 may further include a memory remotely disposed relative to the processor 102, and these remote memories can be connected to the mobile terminal through a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an enterprise intranet, a local area network, a mobile communication network, and their combinations.

[0038] The transmission device 106 is used to receive or send data via a network. Specific examples of the above-mentioned network may include a wireless network provided by a communication provider of a mobile terminal. In one example, the transmission device 106 includes a network adapter (Network Interface Controller, abbreviated as NIC), which can be connected to other network devices through a base station and thus communicate with the Internet. In one example, the transmission device 106 can be a Radio Frequency (RF) module, which is used to communicate with the Internet wirelessly.

[0039] In this embodiment, a sensor control method running on the above-mentioned mobile terminal is provided for a controller in an intelligent device. The intelligent device includes N directions, and the N directions include N groups of sensors. The N groups of sensors are connected to the controller through M bridges. N is an integer greater than 0, and M is an integer greater than 0 and less than N. Figure 2 It is a flowchart of the sensor control method according to an embodiment of the present invention, as Figure 2 shown. The process includes the following steps:

[0040] Step S202, obtaining the movement information of the intelligent device;

[0041] Among them, the above-mentioned intelligent device can be an artificial intelligence-controlled device, such as a robot, a drone, etc. Sensors are arranged in N directions of the intelligent device, and a group of sensors is arranged in each direction. The specific directions of the N directions can be determined according to the actual situation. In this application, six directions, namely up, down, left, right, front, and back, are taken as examples. Each group of sensors arranged in each direction includes K sensors, where K is an integer greater than or equal to 1. The K sensors in a group of sensors are arranged in one direction of the intelligent device. The value of K can be determined according to the actual situation, such as 2, 3, 5, etc. In this application, 2 sensors are arranged in each direction of the intelligent device as an example.

[0042] As Figure 3 shown is an architecture diagram of a sensor control system, including: a controller (for example, a System on Chip, abbreviated as SOC), a bridge, and sensors (arranged in each direction of the intelligent device), such as Figure 3 in which Sensor (Front 1) and Sensor (Front 2) are sensors arranged in front of the intelligent device, Sensor (Left 1) and Sensor (Left 2) are sensors arranged on the left side of the intelligent device, and so on. The positions of the sensors arranged in each direction can be set according to the actual situation. In this embodiment, the bridge design (such as Bridge 1, Bridge 2, and Bridge 3 in the figure) is added to Figure 3For example, each bridge can connect sensors in two opposite directions. Taking Bridge 1 as an example, it connects two groups of sensors. One group is the sensors (Front 1), (Front 2) set in front of the intelligent device, and the other group is the sensors (Rear 1), (Rear 2) set behind the intelligent device.

[0043] In the above embodiment, through the bridge design, the connection method between the sensors and the controller is optimized, the number of interfaces to the controller is reduced, the total amount of data is reduced, thereby reducing the processing capacity requirements of the controller and reducing the load of the controller.

[0044] Step S204, determine frequency information and a target bridge according to the movement information, where the M bridges include the target bridge;

[0045] The above movement information includes the movement speed of the intelligent device. Map the movement speed to Z directions among the N directions of the intelligent device to obtain speed values in the Z directions, where Z is an integer greater than 0 and less than or equal to N; determine the frequency information according to the speed values in the Z directions.

[0046] Taking Figure 4 as an example, assume the movement speed of the intelligent device is V, and this movement speed is a directional speed. Map the movement speed V in six directions of front-back, up-down, and left-right. It can be seen from the figure that the directions to which the movement speed V is mapped are up, front, and right, and the speed values mapped to each direction are V 上 、V 前 、V 右 .

[0047] Determine the frequency information according to the speed values in the Z directions, including: determine the direction with the largest speed value among the Z directions as the main direction, and the directions other than the main direction as the secondary directions; determine the first frequency information of the main direction and the second frequency information of the secondary directions.

[0048] Taking the above embodiment as an example, compare V 上 、V 前 、V 右 of the speed values. Suppose V 前 > V 右 > V 上 . Then the front is the main direction, and the right and up are the secondary directions.

[0049] The above frequency information includes: trigger ratio trigger_ratio, sampling ratio sample_ratio. Determine the first frequency information of the main direction, including: determine the first trigger ratio of the main direction; or, determine the first trigger ratio and the first sampling ratio of the main direction; where the first frequency information includes the first trigger ratio, the first sampling ratio.

[0050] Determining a first trigger ratio for the main direction includes: setting the first trigger ratio to a preset trigger ratio; determining a first sampling ratio for the main direction includes: setting the first sampling ratio to a first target value, the first target value being greater than the preset sampling ratio, and the greater the speed value in the main direction, the greater the first target value.

[0051] The preset trigger ratio can be determined according to the actual situation. For example, it can be 1. It can be determined according to the actual situation. For example, it can be 1, 1 / 2, etc.

[0052] For example, in the main direction, the trigger_ratio is 1, the Sample_ratio is proportional to the moving speed of the mobile device in the main direction. The greater the moving speed in the main direction, the greater the Sample_ratio in the main direction, and the Sample_ratio in the main direction is greater than the preset sampling ratio.

[0053] Determining second frequency information for the secondary direction includes: determining a second trigger ratio for the secondary direction; or, determining a second trigger ratio and a second sampling ratio for the secondary direction; wherein, the second frequency information includes the second trigger ratio and the second sampling ratio.

[0054] Determining second frequency information for the secondary direction includes: determining a second sampling ratio for the secondary direction includes: setting the second sampling ratio to the preset sampling ratio; determining a second trigger ratio for the secondary direction includes: setting the second trigger ratio to a second target value, the second target value being less than the preset trigger ratio, and the smaller the speed value in the secondary direction, the smaller the second target value.

[0055] For example, in the secondary direction, the Sample_ratio is 1, the trigger_ratio is proportional to the moving speed of the mobile device in the secondary direction. The smaller the moving speed in the secondary direction, the smaller the trigger_ratio in the secondary direction, and the trigger_ratio in the secondary direction is less than the preset trigger ratio.

[0056] The movement information includes the movement direction. Determining a target bridge among the M bridges according to the movement information includes: mapping the movement direction to Z directions among the N directions of the intelligent device, where Z is an integer greater than 0 and less than or equal to N; determining the bridges connected to the Z groups of sensors in the Z directions as the target bridge, where the number of the target bridges is one or more.

[0057] The above movement direction can be the direction of the moving speed, so as to Figure 4For example, assume that the moving speed of the intelligent device is V, and this moving speed is a directional speed. The moving speed V is mapped in six directions: front-back, up-down, and left-right. As can be seen from the figure, the directions to which the moving speed V is mapped are up, front, and right. Combining Figure 3 The bridges connected to the sensors in the three directions of up, front, and right include Bridge 1, Bridge 2, and Bridge 3. Then the target bridges are Bridge 1, Bridge 2, and Bridge 3.

[0058] Step S206: Send the frequency information to the target bridge to instruct the target bridge to control the output frequency of the sensors connected thereto according to the frequency information.

[0059] Optionally, the execution subject of the above steps may be a background processor, or other devices with similar processing capabilities, or may also be a machine at least integrated with an image acquisition device and a data processing device. Among them, the image acquisition device may include a graphic acquisition module such as a camera, and the data processing device may include terminals such as a computer and a mobile phone, but is not limited thereto.

[0060] Through the above steps, the problem that the complexity of the controller is relatively high due to the large number of sensors on the intelligent device requiring a large number of controller interfaces is solved, achieving the effect of reducing the number of controller interfaces and reducing the complexity of the controller.

[0061] According to another embodiment of the present invention, a sensor control method is provided, which is applied to the target bridge in the above embodiment and includes: receiving the frequency information from the controller; controlling the output frequency of the target group of sensors connected to the target bridge according to the frequency information, where the target group of sensors is arranged in the target direction of the intelligent device, and the speed value of the intelligent device in the target direction is greater than 0.

[0062] In an exemplary embodiment, the frequency information includes a trigger ratio, or the frequency information includes the trigger ratio and a sampling ratio.

[0063] In an exemplary embodiment, controlling the output frequency of the target group of sensors connected to the target bridge according to the trigger ratio includes: obtaining a preset trigger frequency, and determining the product of the preset trigger frequency and the trigger ratio as the target trigger frequency, where the output frequency includes the target trigger frequency;

[0064] The preset trigger frequency trigger_freq can be determined according to the actual situation, and the target trigger frequency is the product of trigger_freq and the above trigger_ratio.

[0065] Controlling the output frequency of the target group of sensors connected to the target bridge according to the sampling ratio includes: obtaining a preset sampling frequency and determining the product of the preset sampling frequency and the sampling ratio as the target sampling frequency, where the output frequency includes the target sampling frequency.

[0066] The preset sampling frequency Sample_freq can be determined according to the actual situation, and the target sampling frequency is the product of Sample_freq and the above Sample_ratio.

[0067] Wherein, the target trigger frequency is the frequency of the trigger signal, and the trigger signal is used to trigger the target group of sensors to collect data, and the target sampling frequency is used to sample the data collected by the target group of sensors.

[0068] In the above embodiment, the trigger ratio (including the first trigger ratio and the second trigger ratio) is the ratio of sending the trigger signal to the sensor, and the trigger signal is used to trigger the sensor to collect data, indicating that the sensor triggers the sensor to collect data according to the above target trigger frequency. The sampling ratio is the ratio of sampling the data collected by the sensor. Taking the intelligent device as a drone and the sensor as a camera as an example, the above trigger signal is used to instruct the camera to capture an image. The drone captures images according to the above target trigger frequency and samples the captured images according to the target sampling frequency.

[0069] It can be seen from the first frequency information (the first trigger ratio, the first sampling ratio) and the second frequency information (the second trigger ratio, the second sampling ratio) in the above embodiment that for the trigger ratio and the sampling ratio, the main direction is higher than the secondary direction, that is, the frequency of collecting data in the main direction is higher than that in the secondary direction, and the sampling frequency in the main direction is also higher than that in the secondary direction. Taking the drone as an example, the drone mainly uses the sensors in the main direction to collect images in the main direction and reduces the image collection frequency in the secondary direction. By adjusting the frequencies of collecting data in the main direction and the secondary direction, the exposure signal frequency can be controlled to reduce the overall power consumption.

[0070] Taking the intelligent device as a drone and the sensor as a camera as an example, a method for implementing a multi-channel vision sensor obstacle avoidance system for a drone is provided. By optimizing the connection method between the sensor and the SOC, the number of camera interfaces of the SOC is reduced, the total amount of data is reduced, thereby reducing the processing power requirement of the SOC, and at the same time solving the problem of sensor data synchronization.

[0071] Implement a sensor bridge between multiple cameras (sensors) and an SOC (controller) using an FPGA. The sensor bridge has multiple sensor input interfaces and one sensor output interface. Each input interface is connected to a camera. The multiple cameras receive data in parallel and integrate it into one stream (the mux process), and then it is fed into the sensor input interface of the SOC through the one output interface. After receiving the data, the SOC demultiplexes (demuxes) it to obtain the independent data streams of each camera. This design effectively solves the bottleneck in the number of cameras that can be connected in traditional designs.

[0072] The sensor bridge has the function of adjusting the sampling ratio of sensors in each direction in real time, thereby indirectly controlling the output frame rate of the sensors. At the same time, it has the function of adjusting the frequency of the trigger signal in real time to control the output frame rate of the sensors.

[0073] As Figure 5 shown, only one sensor bridge is shown in the figure. In the figure, the FMU is the flight controller of the drone, Speed V is the flight speed (moving speed) of the drone. The SOC sends the sampling ratio sample_ratio and the trigger ratio trigger_ratio of the trigger signal to the sensor bridge through the control interface. The sensor bridge adjusts the sampling rate of sensors in different directions. The trigger ratio and sampling ratio of sensors in the same direction are the same, and the output frame rates of sensors in the same direction are the same.

[0074] Sensors with opposite orientations are connected through the same sensor bridge (for example, Figure 5 the sensors in the front and rear in [example] are connected to the same bridge), and sensors in the same direction share the same trigger signal. The sensors in the front and rear directions are connected to the same sensor bridge. Similarly, the left and right, and the up and down pairs are each connected to the same sensor bridge.

[0075] As Figure 5 shown, taking one direction as an example, the FMU (flight controller) measures the flight speed SpeedV of the drone itself and sends the speed V to the SOC. The SOC calculates three pairs of parameters of the sensor bridge based on the speed V, including (sample_ratio, trigger_ratio). The value range of sample_ratio is between (-0.5, 0.5), and the value range of trigger_ratio is between (0, 1). The calculation method is as follows:

[0076] In the main flight direction (primary direction), the trigger_ratio is a preset trigger ratio (e.g., 1). The sample_ratio is set to a first target value, which is greater than the preset sampling ratio, and the greater the speed value in the primary direction, the greater the first target value.

[0077] In the secondary flight direction (secondary direction), the sample_ratio is the preset sampling ratio (e.g., 1), and the trigger_ratio is set to a second target value, which is less than the preset trigger ratio. The smaller the speed value in the secondary direction, the smaller the second target value.

[0078] Send the sample_ratio to the sensor bridge through the control interface. The sensor bridge adjusts the sampling ratio in different directions according to the sample_ratio. F is the frame rate of each sensor (preset value). The total output frame rate is F*(K + ratio) + F*(K – ratio) => F*2*K (K takes a value around 0.5). It can be seen that the output frame rate of the sensor bridge in the current primary direction is approximately equal to F. There is no significant increase in the total amount of data in the main movement direction. For the left-right and up-down directions, the amount of data is reduced by reducing the trigger signal frequency. Finally, the computational load of the SOC is between (F, 3F), or even lower. Compared with the 6F amount of data in the traditional scheme, the overall amount of data is significantly reduced, and the computational load is also reduced accordingly.

[0079] When the drone moves in a certain direction, decompose the speed into the relevant three directions, increase the sampling ratio of the sensors in the positive direction, and decrease the sampling ratio of the sensors in the reverse direction, thereby indirectly increasing the frame rate in the positive direction and decreasing the frame rate in the reverse direction. The specific adjustment amplitude is dynamically adjusted according to the flight speed. The faster the speed, the greater the adjustment amplitude. When the speed is not fast, especially when hovering, the overall frame rate is reduced by adjusting the frequency of the exposure signal, which more extremely reduces the computational load, thereby reducing power consumption and extending the flight time. This innovation ensures that the system can adapt to different flight environments and mission requirements, maintains the stability of the overall computational load, reduces power consumption, and balances performance and computational load.

[0080] Through the design of the sensor bridge in this application, the requirements for the SOC sensor interface are reduced, and the ability of the SOC to access sensors is improved; the sampling ratio is controlled in real time to adjust the frame rate, and the exposure signal period is controlled in real time to control the sensor frame rate; the control strategy of the sensor bridge decouples according to the flight speed into three motion directions, increases the sampling ratio in the positive motion direction, and reduces the sampling ratio in the reverse direction, so that the overall data volume remains unchanged and the calculation load remains unchanged. When the motion speed is low, the exposure frequency can be reduced to reduce the calculation load, reduce power consumption, and extend the flight time; by controlling the sampling ratio of the sensor bridge in real time, the frame rates of each camera are controlled in real time, improving the data acquisition and processing capabilities of the system in a dynamic environment and enhancing the adaptability of the drone. The overall calculation load of the system is optimized, reducing the pressure on the SOC's calculation and processing capabilities, making the system more advantageous in terms of performance and cost. It solves the complexity and cost problems caused by multiple SOCs in traditional systems and provides a more stable and flexible solution. An efficient data synchronization mechanism is implemented, improving the accuracy of obstacle avoidance results, and reducing the overall power consumption by controlling the exposure signal frequency. The requirement for the number of SOC interfaces is significantly reduced, simplifying the physical connection of the device.

[0081] Through the description of the above embodiments, those skilled in the art can clearly understand that the method according to the above embodiments can be implemented by means of software plus a necessary general hardware platform. Of course, it can also be implemented by hardware, but in many cases, the former is a better implementation method. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes several instructions for causing a terminal device (which can be a mobile phone, computer, server, or network device, etc.) to execute the methods described in various embodiments of the present invention.

[0082] In this embodiment, a sensor control system is further provided, including the controller, M bridges, and N groups of sensors in the above embodiments.

[0083] In this embodiment, a sensor control device is further provided. This device is used to implement the above embodiments and preferred implementation manners, and those that have been described will not be repeated. As used below, the term "module" can be a combination of software and / or hardware that can achieve a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, implementation in hardware, or a combination of software and hardware is also possible and contemplated.

[0084] Figure 6It is a structural block diagram of a device according to an embodiment of the present invention, which is applied to the controller in the above embodiment. The device includes: an acquisition module 62, configured to acquire the movement information of the intelligent device; a determination module 64, configured to determine frequency information and a target bridge according to the movement information, where the M bridges include the target bridge; a sending module 66, configured to send the frequency information to the target bridge to instruct the target bridge to control the output frequency of the sensor connected thereto according to the frequency information.

[0085] In an exemplary embodiment, the movement information includes a movement speed, and the above device is further configured to map the movement speed to Z directions among the N directions of the intelligent device to obtain speed values in the Z directions, where Z is an integer greater than 0 and less than or equal to N; and determine the frequency information according to the speed values in the Z directions.

[0086] In an exemplary embodiment, the above device is further configured to determine the direction with the largest speed value among the Z directions as the main direction, and the directions other than the main direction as the secondary directions; determine first frequency information of the main direction and second frequency information of the secondary directions.

[0087] In an exemplary embodiment, the above device is further configured to determine a first trigger ratio of the main direction; or determine a first trigger ratio and a first sampling ratio of the main direction; where the first frequency information includes the first trigger ratio and the first sampling ratio.

[0088] In an exemplary embodiment, the above device is further configured to set the first trigger ratio to a preset trigger ratio; set the first sampling ratio to a first target value, where the first target value is greater than the preset sampling ratio, and the greater the speed value in the main direction, the greater the first target value.

[0089] In an exemplary embodiment, the above device is further configured to determine a second trigger ratio of the secondary direction; or determine a second trigger ratio and a second sampling ratio of the secondary direction; where the second frequency information includes the second trigger ratio and the second sampling ratio.

[0090] In an exemplary embodiment, the above device is further configured to set the second sampling ratio to the preset sampling ratio; determine the second trigger ratio of the secondary direction, and set the second trigger ratio to a second target value, where the second target value is less than the preset trigger ratio, and the smaller the speed value in the secondary direction, the smaller the second target value.

[0091] In an exemplary embodiment, the movement information includes a movement direction, and the apparatus is further configured to map the movement direction to Z directions among the N directions of the smart device, where Z is an integer greater than 0 and less than or equal to N; determine the bridges connected to Z groups of sensors in the Z directions as the target bridges, where the number of the target bridges is one or more.

[0092] In an exemplary embodiment, a group of sensors includes K sensors, where K is an integer greater than or equal to 1, and the K sensors in a group of sensors are disposed in one direction of the smart device.

[0093] In this embodiment, a sensor control apparatus is further provided, which is applied to the target bridge in the above embodiment, and includes: a receiving module, configured to receive the frequency information from the controller; a control module, configured to control the output frequency of the target group of sensors connected to the target bridge according to the frequency information, where the target group of sensors is disposed in the target direction of the smart device, and the speed value of the smart device in the target direction is greater than 0.

[0094] In an exemplary embodiment, the frequency information includes a trigger ratio, or the frequency information includes the trigger ratio and a sampling ratio.

[0095] In an exemplary embodiment, the apparatus is further configured to obtain a preset trigger frequency, and determine a target trigger frequency as the product of the preset trigger frequency and the trigger ratio, where the output frequency includes the target trigger frequency;

[0096] The apparatus is further configured to obtain a preset sampling frequency, and determine a target sampling frequency as the product of the preset sampling frequency and the sampling ratio, where the output frequency includes the target sampling frequency;

[0097] Wherein, the target trigger frequency is the frequency of a trigger signal, and the trigger signal is used to trigger the target group of sensors to collect data, and the target sampling frequency is used to sample the data collected by the target group of sensors.

[0098] It should be noted that the above-mentioned various modules can be implemented by software or hardware. For the latter, it can be implemented in the following ways, but not limited thereto: the above-mentioned modules are all located in the same processor; or, the above-mentioned various modules are respectively located in different processors in any combination form.

[0099] An embodiment of the present invention further provides a computer-readable storage medium, where a computer program is stored in the computer-readable storage medium, and when the computer program is executed by a processor, the steps of the method described in any one of the above are implemented.

[0100] In an exemplary embodiment, the above-mentioned computer-readable storage medium may include, but is not limited to: various media capable of storing computer programs, such as USB flash drives, read-only memory (ROM for short), random access memory (RAM for short), mobile hard disks, magnetic disks, or optical discs.

[0101] An embodiment of the present invention further provides an electronic device, including a memory and a processor. A computer program is stored in the memory, and the processor is configured to run the computer program to execute the steps in any one of the above method embodiments.

[0102] In an exemplary embodiment, the above-mentioned electronic device may further include a transmission device and an input / output device. Among them, the transmission device is connected to the above-mentioned processor, and the input / output device is connected to the above-mentioned processor.

[0103] Specific examples in this embodiment may refer to the examples described in the above embodiments and exemplary embodiments, and will not be repeated here.

[0104] An embodiment of the present invention further provides a computer program product, including a computer program, and when the computer program is executed by a processor, the steps of the methods in various embodiments of the present application are implemented.

[0105] Obviously, those skilled in the art should understand that the above-mentioned modules or steps of the present invention can be implemented by a general-purpose computing device. They can be concentrated on a single computing device or distributed on a network composed of multiple computing devices. They can be implemented by program codes executable by the computing device. Thus, they can be stored in a storage device and executed by the computing device. And in some cases, the steps shown or described can be executed in a different order than here, or they can be separately fabricated into individual integrated circuit modules, or multiple modules or steps among them can be fabricated into a single integrated circuit module to implement. In this way, the present invention is not limited to any specific combination of hardware and software.

[0106] The above are only the preferred embodiments of the present invention and are not used to limit the present invention. For those skilled in the art, the present invention can have various changes and modifications. Any modification, equivalent replacement, improvement, etc. made within the principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A sensor control method, characterized in that, A controller applied to an intelligent device, the intelligent device including N directions, the N directions including N groups of sensors, the N groups of sensors being connected to the controller through M bridges, N being an integer greater than 0, M being an integer greater than 0 and less than N, including: Obtain the movement information of the intelligent device; Determine frequency information and a target bridge according to the movement information, where M bridges include the target bridge; Send the frequency information to the target bridge to instruct the target bridge to control the output frequency of the sensors connected thereto according to the frequency information.

2. The method according to claim 1, characterized in that, The movement information includes a movement speed, and determining the frequency information according to the movement information includes: Map the movement speed to Z directions among the N directions of the intelligent device to obtain speed values in the Z directions, where Z is an integer greater than 0 and less than or equal to N; Determine the frequency information according to the speed values in the Z directions.

3. The method according to claim 2, wherein Determining the frequency information according to the speed values in the Z directions includes: Determine the main direction as the direction with the largest speed value among the Z directions, and determine the directions other than the main direction as secondary directions; Determine the first frequency information of the main direction and the second frequency information of the secondary directions.

4. The method according to claim 3, wherein Determining the first frequency information of the main direction includes: Determine the first trigger ratio of the main direction; or, Determine the first trigger ratio and the first sampling ratio of the main direction; Wherein, the first frequency information includes the first trigger ratio and the first sampling ratio.

5. The method according to claim 4, wherein Determining the first trigger ratio of the main direction includes: setting the first trigger ratio as a preset trigger ratio; Determining the first sampling ratio of the main direction includes: setting the first sampling ratio as a first target value, the first target value being greater than a preset sampling ratio, and the larger the speed value in the main direction, the larger the first target value.

6. The method according to claim 4, characterized in that, Determining the second frequency information of the secondary directions includes: Determine the second trigger ratio of the secondary direction; or, Determine the second trigger ratio and the second sampling ratio of the secondary direction; Wherein, the second frequency information includes the second trigger ratio and the second sampling ratio.

7. The method according to claim 6, characterized in that, Determining the second frequency information of the secondary directions includes: Determining the second sampling ratio of the secondary direction includes: setting the second sampling ratio as a preset sampling ratio; Determining the second trigger ratio of the secondary direction includes: setting the second trigger ratio as a second target value, the second target value being less than the preset trigger ratio, and the smaller the speed value in the secondary direction, the smaller the second target value.

8. The method according to claim 1, characterized in that The movement information includes a movement direction, and determining the target bridge among M bridges according to the movement information includes: Map the movement direction to Z directions among the N directions of the intelligent device, where Z is an integer greater than 0 and less than or equal to N; Determine the bridges connected to the Z groups of sensors in the Z directions as the target bridge, where the number of the target bridges is one or more.

9. The method according to claim 1, wherein A set of sensors includes K sensors, where K is an integer greater than or equal to 1, and the K sensors in the set of sensors are arranged in one direction of the intelligent device.

10. A sensor control method, characterized in that, Applied to a target bridge, including: Receiving the frequency information from the controller; Controlling the output frequency of a target set of sensors connected to the target bridge according to the frequency information, where the target set of sensors is arranged in the target direction of the intelligent device, and the speed value of the intelligent device in the target direction is greater than 0.

11. The method according to claim 10, wherein The frequency information includes a trigger ratio, or the frequency information includes the trigger ratio and a sampling ratio.

12. The method according to claim 11, wherein: Controlling the output frequency of a target set of sensors connected to the target bridge according to the trigger ratio includes: obtaining a preset trigger frequency, and determining the product of the preset trigger frequency and the trigger ratio as the target trigger frequency, where the output frequency includes the target trigger frequency; Controlling the output frequency of a target set of sensors connected to the target bridge according to the sampling ratio includes: obtaining a preset sampling frequency, and determining the product of the preset sampling frequency and the sampling ratio as the target sampling frequency, where the output frequency includes the target sampling frequency; Wherein, the target trigger frequency is the frequency of a trigger signal for triggering the target set of sensors to collect data, and the target sampling frequency is used to sample the data collected by the target set of sensors.

13. A sensor control device, characterized in that, Applied to the controller of any one of claims 1 to 9, including: An acquisition module for acquiring the movement information of the intelligent device; A determination module for determining frequency information and a target bridge according to the movement information, where the M bridges include the target bridge; A sending module for sending the frequency information to the target bridge to instruct the target bridge to control the output frequency of the sensors connected thereto according to the frequency information.

14. A sensor control device, characterized in that, Applied to the target bridge of any one of claims 10 to 12, including: A receiving module for receiving the frequency information from the controller; A control module for controlling the output frequency of a target set of sensors connected to the target bridge according to the frequency information, where the target set of sensors is arranged in the target direction of the intelligent device, and the speed value of the intelligent device in the target direction is greater than 0.

15. A sensor control system, characterized in that, Including: A controller, M bridges and N sets of sensors, the intelligent device includes N directions, the N directions include N sets of sensors, the N sets of sensors are connected to the controller through M bridges, N is an integer greater than 0, and M is an integer greater than 0 and less than N; The controller is configured to acquire the movement information of the intelligent device; Determine frequency information and a target bridge according to the movement information, where the M bridges include the target bridge; send the frequency information to the target bridge to instruct the target bridge to control the output frequency of the sensors connected thereto according to the frequency information; The target bridge is used to receive the frequency information from the controller; control the output frequency of a target group of sensors connected to the target bridge according to the frequency information, wherein the target group of sensors is arranged in a target direction of the intelligent device, and the speed value of the intelligent device in the target direction is greater than 0.

16. A computer-readable storage medium, characterized in that, A computer program is stored in the computer-readable storage medium, wherein when the computer program is executed by a processor, the steps of the method described in any one of claims 1 to 9 or 10 to 12 are implemented.

17. An electronic device, comprising a memory and a processor, characterized in that, A computer program is stored in the memory, and the processor is configured to run the computer program to execute the method described in any one of claims 1 to 9 or 10 to 12.

18. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, the steps of the method described in any one of claims 1 to 9 or 10 to 12 are implemented.

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