CN114691579B - Heterogeneous processor of indoor unmanned vehicle and communication method thereof - Google Patents
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Abstract
The invention discloses a communication method of heterogeneous processors of an indoor unmanned aerial vehicle, which comprises heterogeneous processor components, a communication mode, a communication mechanism, an information inter-transmission mode and a data filtering algorithm, wherein the communication mode and the communication mechanism are used for establishing synchronous communication among the heterogeneous processors, completing data verification and maintaining long connection, the information inter-transmission mode comprises two information inter-transmission modes of bottom-layer state data and upper-layer control data, the data filtering algorithm is used for preprocessing laser point cloud and image pixels and assisting the indoor unmanned aerial vehicle to complete state estimation.
Description
Technical Field
The invention relates to a heterogeneous processor of an indoor unmanned vehicle and a communication method thereof, belonging to the technical field of communication.
Background
In recent years, in the field of indoor unmanned aerial vehicle, because the difference exists between the data and the realized functions which are required to be processed in the motion control and information processing links of the indoor unmanned aerial vehicle, the control and the processing are usually realized by adopting heterogeneous processors, but because the difference exists in system architecture among the heterogeneous processors, the data communication among the heterogeneous processors cannot be directly performed, so the data communication among the heterogeneous processors must be realized by means of a reliable, stable and high-speed communication mode, and the current communication scheme of the heterogeneous processors is generally too simple and can not maintain reliable long connection, so in order to ensure that the unmanned aerial vehicle realizes the full scheduling of software and hardware resources, a high-efficiency and feasible communication method and a communication mechanism are required to be introduced among the heterogeneous processors of the unmanned aerial vehicle.
The indoor unmanned vehicles have differences in the types of data to be processed when realizing motion control and information processing, most of communication methods at present do not distinguish information inter-transmission modes among heterogeneous processors, so that a plurality of redundancies are generated in the data transmission process, and the communication efficiency is often lower. The indoor unmanned vehicle has various interferences to the data received by various sensors, and the calculation cost can be greatly increased by directly delivering the sensor data which is not processed to a processor for calculation, so that the data processing process is complex and the operation is slow. Therefore, in order to improve the communication efficiency between heterogeneous processors and reduce the calculation cost of the processors, optimization of the information inter-transmission mode and the data filtering algorithm between heterogeneous processors is required.
Disclosure of Invention
In order to solve the problems in the prior art, the invention provides an indoor unmanned aerial vehicle heterogeneous processor and a communication method thereof, so as to realize stable and high-speed full duplex communication among indoor unmanned aerial vehicle heterogeneous processors.
In order to achieve the above purpose, the invention adopts the following technical scheme: a heterogeneous processor of an indoor unmanned vehicle, which comprises a bottom layer processor responsible for motion control and an upper layer processor responsible for data processing, wherein the bottom layer processor comprises and is not limited to all processors adopting a core-M kernel and similar kernel architecture, and the upper layer processor comprises and is not limited to all processors adopting an ARMv8-a system architecture and similar system architecture; the data of the bottom layer processor is output by a serial port, an output signal is converted into a USB signal through a CH340 module and is input to the upper layer processor, and a data buffer area in the upper layer processor is responsible for receiving the data and forwarding the data according to data verification information; and after the data synchronization is finished, the output USB signal is converted into a serial port signal through a CH340 module and is input to a bottom layer processor, and the bottom layer processor processes and forwards the data according to the data verification information.
A method of communication with a heterogeneous processor of an indoor drone as claimed in claim 1, comprising the specific steps of:
step 1, the communication method adopts a serial communication mode, and a bottom processor and an upper processor mutually start to send output data;
step 2, adding a synchronous character into serial communication data based on an external synchronous method, transmitting the synchronous character by a bottom layer processor and an upper layer processor before transmitting the data to the other side, and adjusting the time sequence of the processor by a receiver according to the transmission frequency of the synchronous character to finish rate synchronization;
step 3, judging whether the time sequence of the processor is consistent, if not, returning to the previous step to carry out time sequence adjustment again, and if so, sending a data packet;
step 4, adopting a heartbeat communication mechanism in ROS node communication of the upper layer processor, detecting whether a heartbeat packet exists in a transmitted data center in the communication process, if the existence of the heartbeat packet is not detected, adding the heartbeat packet, and if the existence of the heartbeat packet is detected, communicating and transmitting data between the lower layer processor and the upper layer processor;
step 5, adding check information into the serial communication data, and analyzing a check field;
and step 6, forwarding the data transmitted in the previous step, and finally completing the receiving between the bottom layer processor and the upper layer processor.
Further, in the step 4, a heartbeat packet added in the ROS node data packet in the upper layer processor is kept in long connection with the ROS master node server, so as to periodically detect whether other nodes connected to the ROS master node are disconnected, so that the orderly and normal transceiving of data is ensured; when the ROS master node does not receive data of a certain ROS node within 240 seconds, the node is automatically set to be disconnected and the TCP connection is attempted to be reestablished with the node.
Further, in the step 4, the state information uploaded by the bottom layer processor at least includes the linear speed, the angular speed, the mileage and the heading of the indoor unmanned aerial vehicle, the state data required by each indoor unmanned aerial vehicle is expanded according to the actual application of the indoor unmanned aerial vehicle, and the state data of the indoor unmanned aerial vehicle is calculated by the motion processing module of the bottom layer processor and output by the serial port, and is received by the USB serial port of the upper layer processor.
Further, in the step 4, the control information issued by the upper processor at least includes motor speed regulation, steering angle and braking signals of the indoor unmanned vehicles, the control data required by each indoor unmanned vehicle is expanded according to the motion control architecture thereof, and the control data of the indoor unmanned vehicles are calculated by the motion planning module of the upper processor and are output by the USB serial port of the upper processor, and are received by the serial port of the bottom processor.
Further, in the step 5, the data verification information sent by the bottom layer processor to the upper layer processor includes a data type field, a signaling rate field and a redundancy check field; the data buffer area in the upper processor completes synchronization, forwarding and calibration of data according to the information of each field; the data verification information sent to the bottom layer processor by the upper layer processor comprises a control type field, a signaling rate field and a redundancy verification field, and the bottom layer processor completes synchronization, preprocessing, forwarding and calibration of data according to the information of each field.
Furthermore, a data preprocessing module is further arranged in the upper processor and is responsible for filtering preprocessing of sensor signals, and preprocessing is performed on laser point clouds and image pixels through a data filtering algorithm so as to assist the indoor unmanned vehicle in completing state estimation.
Further, the filtering pretreatment process is as follows: external sensors such as a laser radar and a camera are connected to the upper layer processor through a USB serial port, a data preprocessing module in the upper layer processor filters the laser sensor and the camera data, and the processed sensing data is transmitted to a real-time positioning and navigation unit of the upper layer processor for relevant calculation.
Further, the data preprocessing module calculates a distance set between a neighborhood of each point cloud and a k neighborhood thereof by adopting a statistical filtering algorithm to the laser point cloud data input by the laser sensor, and calculates a mean value mu and a standard deviation sigma of the distances from all points to the k neighborhood thereof, so as to obtain a distance threshold d max Can be expressed as d max =μ+α×σ, where α is a scaling factor, processing all point clouds, and comparing the culling with the average distance of k neighboring points is largeAt d max Finishing the filtering treatment of the laser point cloud;
the data preprocessing module adopts Kalman filtering to image pixel points input by the visual sensor, and takes a pixel matrix of the image as a observed quantity Z of a system state k Calculating the state observation matrix H of the system according to the observed quantity attribute, and calculating the Kalman gain K of the system at the moment K k From this, a state estimator is calculatedIs>Estimating covariance matrix P k Finally, to make covariance matrix P k Minimum solving for the optimization objective the optimal state estimator at a certain moment K +.>And circulating the process, and outputting the state estimation value of the indoor unmanned vehicle to a calculation processing module in an upper layer processor in real time by a data preprocessing module according to the observed value of the image pixel input by the vision sensor.
Further, the data preprocessing module predicts visual characteristics, the calculation processing module in the upper processor comprises a real-time positioning and mapping system and a motion planning system, the real-time positioning and mapping system completes positioning of the unmanned vehicles and reconstruction of the environment according to the processed visual pixel characteristics, and the motion planning system completes path planning according to the positioning information of the unmanned vehicles.
Compared with the prior art, the invention has the beneficial effects that: the invention ensures stable data communication among heterogeneous processors through a serial port communication mode and a synchronous heartbeat and verification mechanism, improves the communication efficiency of state data and control data among the heterogeneous processors through an information mutual transmission mode, carries out filtering pretreatment on laser point cloud data and image pixels through a data filtering algorithm, effectively reduces the calculation cost of hardware, and improves the efficiency and precision of the unmanned vehicle in the positioning and navigation processes, so that the heterogeneous processor of the indoor unmanned vehicle has higher communication quality and data processing efficiency.
Drawings
FIG. 1 is a block diagram of the system components of the present invention.
Fig. 2 is a flow chart of data communication according to the present invention.
FIG. 3 is a flow chart of the sensor data preprocessing of the present invention.
Detailed Description
Embodiments of the present invention are described in detail below, examples of which are illustrated in the accompanying drawings, wherein the same or similar reference numerals refer to the same or similar elements or elements having the same or similar functions throughout. The embodiments described below by referring to the drawings are exemplary only for explaining the present invention and are not to be construed as limiting the present invention.
As shown in fig. 1 to 3, the embodiment includes a heterogeneous processor, a communication mode, a communication mechanism, an information inter-transmission mode and a data filtering algorithm, where the communication mode and the communication mechanism are used for establishing synchronous communication between heterogeneous processors, completing data verification and maintaining long connection, the information inter-transmission mode includes two information inter-transmission modes of bottom layer state data and upper layer control data, and the data filtering algorithm is used for preprocessing laser point cloud and image pixels to assist the indoor unmanned vehicle in completing state estimation.
In particular, in order to ensure the stability of the communication between heterogeneous processors, the present invention describes the heterogeneous processor composition, as shown in fig. 1, where the heterogeneous processor to which the communication method is applicable includes a bottom layer processor responsible for motion control and an upper layer processor responsible for data processing, where the bottom layer processor includes, but is not limited to, all processors adopting a core-M kernel and similar kernel architecture, and the upper layer processor includes, but is not limited to, all processors adopting an ARMv8-a system architecture and similar system architecture.
In a specific implementation, in order to ensure an efficient and stable communication process, as shown in fig. 1, a serial communication mode is adopted in the communication method, when a bottom processor pre-outputs data, the data is required to wait for data synchronization, after the synchronization is finished, the data is output by a serial port, an output signal is converted into a USB signal through a CH340 module and is input into an upper processor, a data buffer area in the upper processor is responsible for receiving the data, and the data is forwarded according to data verification information; and buffering the data sent by the upper processor in advance into a data buffer area, after the data synchronization is finished, converting the output USB signal into a serial port signal through a CH340 module, and inputting the serial port signal into the bottom processor, wherein the bottom processor processes and forwards the data according to the data verification information.
A communication method of heterogeneous processors of an indoor unmanned vehicle, as shown in figure 2, comprises the following specific steps:
step 1, the communication method adopts a serial communication mode, and a bottom processor and an upper processor mutually start to send output data;
step 2, adding a synchronous character into serial communication data based on an external synchronous method, transmitting the synchronous character by a bottom layer processor and an upper layer processor before transmitting the data to the other side, and adjusting the time sequence of the processor by a receiver according to the transmission frequency of the synchronous character to finish rate synchronization;
step 3, judging whether the time sequence of the processor is consistent, if not, returning to the previous step to carry out time sequence adjustment again, and if so, sending a data packet;
step 4, adopting a heartbeat communication mechanism in ROS node communication of the upper layer processor, detecting whether a heartbeat packet exists in a transmitted data center in the communication process, if the existence of the heartbeat packet is not detected, adding the heartbeat packet, and if the existence of the heartbeat packet is detected, communicating and transmitting data between the lower layer processor and the upper layer processor;
step 5, adding check information into the serial communication data, and analyzing a check field;
and step 6, forwarding the data transmitted in the previous step, and finally completing the receiving between the bottom layer processor and the upper layer processor.
In the implementation, in order to ensure that the upper processor keeps long connection, as shown in fig. 2, a communication method adopts a heartbeat communication mechanism in ROS node communication of the upper processor, a heartbeat packet is added into an ROS node data packet in the upper processor, the heartbeat packet is detected, if the heartbeat packet is not detected, the heartbeat packet is added into the data packet, the detection is performed again, the data is formally transmitted until the heartbeat packet is detected, when the ROS master node does not receive data of a certain ROS node within 240 seconds, the node connection is automatically set to be disconnected, and the TCP connection is attempted to be reestablished with the ROS node data packet.
In a specific implementation, in order to ensure that data is forwarded and checked quickly, as shown in fig. 2, in the communication method, check information is added into serial communication data, and data check information sent by a bottom layer processor to an upper layer processor includes a data type field, a signaling rate field and a redundancy check field, and a data buffer area in the upper layer processor completes synchronization, forwarding and calibration of the data according to the information of each field; the data verification information sent to the bottom layer processor by the upper layer processor comprises a control type field, a signaling rate field and a redundancy verification field, and the bottom layer processor completes synchronization, preprocessing, forwarding and calibration of data according to the information of each field.
In a specific implementation, in order to provide a rapid heterogeneous communication process, as shown in fig. 2, a communication method adds a synchronous character into serial communication data based on an external synchronous method, a bottom layer processor and an upper layer processor send the synchronous character in advance before sending data to the other side, and a receiver adjusts the time sequence of the processor according to the sending frequency of the synchronous character to complete rate synchronization; when no data is transmitted between the processors, the synchronous character is replaced by the null character, the two sides keep the speed synchronous, and the synchronization is not needed when the data is transmitted between the processors.
In the specific implementation, in order to ensure the data transmission process of the flow, the control information issued by the upper layer processor in the communication method comprises motor speed regulation, steering angle, braking signals and the like, and the control data required by each indoor unmanned vehicle is expanded according to the motion control framework of the control data.
In the implementation, in order to reduce the calculation consumption of the sensing data in the upper processor, the communication method carries out filtering pretreatment on the sensing data in the upper processor, the sensors such as the laser radar and the camera are connected to the upper processor through the USB serial port, the data preprocessing module in the upper processor carries out filtering treatment on the laser sensor and the camera data, and the processed sensing data is sent to the upper processor to carry out relevant calculation on the real-time positioning and navigation unit.
In specific implementation, in order to perform noise filtering optimization on input laser point cloud data, a data preprocessing module in a communication method adopts a statistical filtering algorithm on the laser point cloud data input by a laser sensor, calculates a distance set between a neighborhood of each point cloud and a k neighborhood thereof, calculates a mean value mu and a standard deviation sigma of distances from all points to the k neighborhood thereof, and then a distance threshold d max Can be expressed as d max =μ+α×σ, α is a scaling factor, all point clouds are processed, and the average distance between the comparison culling and k neighboring points is greater than d max And (3) completing the filtering process of the laser point cloud.
In specific implementation, in order to predict relevant state information of an indoor unmanned vehicle, a data preprocessing module in a communication method adopts Kalman filtering to image pixel points input by a visual sensor, and takes a pixel matrix of an image as an observed quantity Z of a system state k Calculating the state observation matrix H of the system according to the observed quantity attribute, and calculating the Kalman gain K of the system at the moment K k From this, a state estimator is calculatedIs>Estimating covariance matrix P k Finally, to make covariance matrix P k Minimum solving for the optimization objective the optimal state estimator at a certain moment K +.>And circulating the process, and outputting the state estimation value of the indoor unmanned vehicle to a calculation processing module in an upper layer processor in real time by a data preprocessing module according to the observed value of the image pixel input by the vision sensor.
In the implementation, in order to improve the operation efficiency of the upper processor, the communication method predicts the visual characteristics in the preprocessing module, the calculation processing module in the upper processor comprises a real-time positioning and mapping system and a motion planning system, the real-time positioning and mapping system completes the positioning of the unmanned vehicle and the reconstruction of the environment according to the processed visual pixel characteristics, and the motion planning system completes the path planning according to the positioning information of the unmanned vehicle.
It should be noted that the above-mentioned embodiments illustrate rather than limit the invention, and that those skilled in the art will be able to design alternative embodiments without departing from the scope of the appended claims.
Claims (9)
1. An indoor unmanned aerial vehicle's heterogeneous processor, its characterized in that: the system comprises a bottom layer processor responsible for motion control and an upper layer processor responsible for data processing, wherein the bottom layer processor comprises a processor adopting a core-M kernel architecture, and the upper layer processor comprises a processor adopting an ARMv8-a system architecture; the data of the bottom layer processor is output by a serial port, an output signal is converted into a USB signal through a CH340 module and is input to the upper layer processor, and a data buffer area in the upper layer processor is responsible for receiving the data and forwarding the data according to data verification information; the data pre-sent by the upper processor is cached to a data buffer area, after the data synchronization is finished, the output USB signal is converted into a serial port signal through a CH340 module and is input to the bottom processor, a data pre-processing module is further arranged in the upper processor and is responsible for carrying out filtering pre-processing on the sensor signal, and laser point clouds and image pixels are pre-processed through a data filtering algorithm so as to assist an indoor unmanned vehicle to complete state estimation; the bottom layer processor processes and forwards the data according to the data verification information, and the state data of the indoor unmanned vehicle is calculated by a motion processing module of the bottom layer processor, is output through a serial port and is received by a USB serial port of the upper layer processor; the control data of the indoor unmanned vehicle is calculated by a motion planning module of the upper processor, is output by a USB serial port of the upper processor, and is received by a serial port of the bottom processor.
2. A method of communicating with a heterogeneous processor of an indoor drone of claim 1, wherein: the method comprises the following specific steps:
step 1, the communication method adopts a serial communication mode, and a bottom processor and an upper processor mutually start to send output data;
step 2, adding a synchronous character into serial communication data based on an external synchronous method, transmitting the synchronous character by a bottom layer processor and an upper layer processor before transmitting the data to the other side, and adjusting the time sequence of the processor by a receiver according to the transmission frequency of the synchronous character to finish rate synchronization;
step 3, judging whether the time sequence of the processor is consistent, if not, returning to the previous step to carry out time sequence adjustment again, and if so, sending a data packet;
step 4, adopting a heartbeat communication mechanism in ROS node communication of the upper layer processor, detecting whether a heartbeat packet exists in a transmitted data center in the communication process, if the existence of the heartbeat packet is not detected, adding the heartbeat packet, and if the existence of the heartbeat packet is detected, communicating and transmitting data between the lower layer processor and the upper layer processor;
step 5, adding check information into the serial communication data, and analyzing a check field;
and step 6, forwarding the data transmitted in the previous step, and finally completing the receiving between the bottom layer processor and the upper layer processor.
3. The communication method of the heterogeneous processor of the indoor unmanned vehicle according to claim 2, wherein: in the step 4, a heartbeat packet added in an ROS node data packet in the upper-layer processor is kept in long connection with a main node server of the ROS, so that whether other nodes connected to the ROS main node are disconnected or not is detected at fixed time, and the orderly and normal receiving and transmitting of data are ensured; when the ROS master node does not receive data of a certain ROS node within 240 seconds, the node is automatically set to be disconnected and the TCP connection is attempted to be reestablished with the node.
4. The communication method of the heterogeneous processor of the indoor unmanned vehicle according to claim 2, wherein: in the step 4, the state information uploaded by the bottom layer processor at least comprises the linear speed, the angular speed, the mileage and the heading of the indoor unmanned vehicle.
5. The communication method of the heterogeneous processor of the indoor unmanned vehicle according to claim 2, wherein: in the step 4, the control information issued by the upper processor at least comprises motor speed regulation, steering angle and braking signals of the indoor unmanned vehicle.
6. The communication method of the heterogeneous processor of the indoor unmanned vehicle according to claim 2, wherein: in the step 5, the data verification information sent to the upper layer processor by the bottom layer processor includes a data type field, a signaling rate field and a redundancy check field; the data buffer area in the upper processor completes synchronization, forwarding and calibration of data according to the information of each field; the data verification information sent to the bottom layer processor by the upper layer processor comprises a control type field, a signaling rate field and a redundancy verification field, and the bottom layer processor completes synchronization, preprocessing, forwarding and calibration of data according to the information of each field.
7. The communication method of the heterogeneous processor of the indoor unmanned vehicle according to claim 2, wherein: the filtering pretreatment process comprises the following steps: external sensors such as a laser radar and a camera are connected to the upper layer processor through a USB serial port, a data preprocessing module in the upper layer processor filters the laser sensor and the camera data, and the processed sensing data is transmitted to a real-time positioning and navigation unit of the upper layer processor for relevant calculation.
8. The method for communicating with a heterogeneous processor of an indoor drone of claim 7, wherein: the data preprocessing module adopts a statistical filtering algorithm to the laser point cloud data input by the laser sensor, calculates a distance set between the neighborhood of each point cloud and the k neighborhood thereof, calculates the average value mu and the standard deviation sigma of the distances from all points to the k neighborhood thereof, and then calculates a distance threshold d max Can be expressed as d max =μ+α×σ, where α is a scaling factor, processing all point clouds, and comparing the average distance between the culling and k neighboring points is greater than d max Finishing the filtering treatment of the laser point cloud;
the data preprocessing module adopts Kalman filtering to image pixel points input by the visual sensor, and takes a pixel matrix of the image as a observed quantity Z of a system state k Calculating the state observation matrix H of the system according to the observed quantity attribute, and calculating the Kalman gain K of the system at the moment K k From this, a state estimator is calculatedIs>Estimating covariance matrix P k Finally, to make covariance matrix P k Minimum solving for the optimization objective the optimal state estimator at a certain moment K +.>And circulating the process, and outputting the state estimation value of the indoor unmanned vehicle to a calculation processing module in an upper layer processor in real time by a data preprocessing module according to the observed value of the image pixel input by the vision sensor.
9. The method for communicating with a heterogeneous processor of an indoor drone of claim 7, wherein: the data preprocessing module is used for predicting visual characteristics, the calculation processing module in the upper processor comprises a real-time positioning and mapping system and a motion planning system, the real-time positioning and mapping system is used for completing positioning of the unmanned vehicles and reconstruction of the environment according to the processed visual pixel characteristics, and the motion planning system is used for completing path planning according to the positioning information of the unmanned vehicles.
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