Auxiliary driving method for long roadway without obvious characteristics

Abstract

The invention discloses a long roadway auxiliary driving method without obvious characteristics, and relates to the technical field of coal mine underground long roadway moving wheel type dangerous gas unmanned automatic inspection. Comprising the steps that an upper computer selects an automatic inspection mode, and a robot is started and starts self-inspection; the upper computer provides setting parameters; the laser radar collects roadway wall information in real time to obtain data, calculates the distance and the included angle between the robot and the roadway wall surface, makes a difference with the given distance, calculates the deviation roadway wall angle to obtain an error, and obtains the angular velocity of the robot through a PID algorithm; according to the invention, path planning and polling positions are cooperatively applied through the upper computer, the RFID and the PLC, the advantages of robot long roadway polling monitoring are embodied, the RFID is added to assist the robot in positioning in a long-distance roadway, meanwhile, dual obstacle avoidance protection of radar obstacle avoidance and ultrasonic radar reduces the occurrence of safety accidents, and the working efficiency is improved.

Description

Technical Field

[0001] The invention relates to the technical field of unmanned automatic inspection of dangerous gases in long tunnels of coal mines, in particular to an auxiliary driving method for long tunnels without obvious features. Background Art

[0002] The detection of hazardous gases in coal mines mainly relies on manual labor, especially in the process of tunnel detection, sealing and unsealing, exposing old empty areas, and repairing old shafts and tunnels. Tile inspectors or rescue team members are required to conduct environmental detection in dangerous areas. Such manual detection has many problems such as high risk and low operating efficiency, which has become a bottleneck restricting coal mines from reducing staff, increasing safety, and improving efficiency. At this stage, a coal mine underground hazardous gas inspection robot has been developed, but it is still in the initial stage of exploration. There are still many problems in its maturity, intelligent application, and autonomous inspection methods.

[0003] The existing long tunnel hazardous gas robot inspection method has the following problems:

[0004] 1. Remote control inspection mode: The upper computer or remote controller is used on the ground to operate the underground robot inspection task. There is a problem of poor communication network. After the operation command is issued, the robot executes the action with a lag. Although the robot itself has obstacle avoidance protection, it is still dangerous and the operation experience is very poor. The delay effect of the communication system during long-distance remote operation increases the difficulty of robot walking control, and it is necessary to develop high-performance remote communication and control systems;

[0005] 2. Automatic inspection method: For conventional LiDAR SLAM mapping method, the SLAM algorithm also needs to have closed-loop detection capability. For example, in underground coal mines, there are many long tunnels and forks, and there are many similar scenes. It is difficult to form an effective global matching reference in the SLAM process, which can easily lead to the inability to clear the accumulated errors in the local area in time, and then cause loop closure problems.

[0006] 3. Inspection positioning problem: Due to similar scenes and background characteristics, the inspection robot’s map building is not accurate enough, resulting in inaccurate inspection paths and robot positioning. Summary of the invention

[0007] The purpose of the present invention is to solve the problems mentioned in the above background technology, and to propose a method for assisting driving in long lanes without obvious features. In view of the existing remote control inspection method, there are problems such as low efficiency, high intensity of operators, and high risks; the conventional laser radar SLAM mapping method has defects in the identification of long lane features, and the robot path planning is not accurate enough, resulting in the problem of inconsistent paths during the inspection process. The present invention combines laser radar, RFID, IMU and position encoder, takes the long lane wall as the reference, and feeds back the posture and inspection position of the inspection robot body in real time; sets the remote control inspection mode and autonomous navigation mode through the host computer; sets the inspection path of the inspection robot and the inspection monitoring position of dangerous gases through parameters such as the width and length of the long lane; through laser radar, RFID positioning and ultrasonic obstacle avoidance, ensure the control of driving speed during the inspection process and accurate obstacle avoidance when abnormal conditions occur; through real-time collection, analysis, processing and detection of lane wall information, the inspection robot can follow the set path and adjust the driving at any time along the long lane; by identifying the target RFID point to determine the position information, set the distance between the two target RFID points, and compare with the robot odometer information to obtain the robot position state.

[0008] The purpose of the present invention can be achieved by the following technical solution: A method for assisting driving in a long lane without obvious features, based on a robot and a control system, comprises the following steps:

[0009] The host computer selects the automatic inspection mode, and the robot starts and begins self-inspection;

[0010] The host computer provides setting parameters;

[0011] The laser radar collects tunnel wall information in real time to obtain data, calculates the distance and angle between the robot and the tunnel wall, and subtracts it from the given distance to calculate the angle of deviation from the tunnel wall, obtains the error, and uses the PID algorithm to obtain the robot's angular velocity;

[0012] The PLC controller makes real-time judgment and analysis based on the data information transmitted by the laser radar and the industrial computer. It corrects the position of the electric push rod in real time based on the deviation angle and vertical distance through the PID control algorithm, and adjusts the robot body posture in real time.

[0013] The robot drives in a long-distance lane and determines whether it has identified the target RFID point. If yes, it continues to inspect. If not, it calculates the robot's odometer information and compares it with the given RFID target threshold distance. If it exceeds the threshold distance, it returns to the host computer for an alarm. If it is within the threshold range, it continues to identify the target RFID point.

[0014] The PLC controller makes real-time judgment and analysis based on the data information transmitted by the laser radar, RFID positioning chip, industrial computer and ultrasonic obstacle avoider. According to the distance between the vehicle body and the obstacle, the PLC controller judges and compares the driving state of the robot to accelerate, maintain a constant speed, decelerate and stop.

[0015] By comparing the position information collected by high-speed pulses with the position value set by the host computer, the collection position of each hazardous gas on the inspection route is determined, and the multi-parameter gas sensor performs hazardous gas detection;

[0016] After reaching the final position of the set long alley, the robot spins on the spot and returns to the original position along the original path, and the inspection process ends.

[0017] As a preferred implementation of the present invention, the parameters include the target RFID point distance, the target RFID threshold value, the distance from the robot to the wall, and the robot's travel speed.

[0018] As a preferred embodiment of the present invention, the robot is equipped with a laser radar, several RFID positioning chips, a lifting and lodging device, a multi-parameter gas sensor, a mining intrinsically safe vehicle-mounted ultrasonic radar, an incremental encoder, an IMU gyroscope and a visible light and thermal imaging gimbal; wherein the laser radar and the visible light and thermal imaging gimbal are installed on the upper end surface of the robot; the multi-parameter gas sensor is installed on the lifting and lodging device, the mining intrinsically safe vehicle-mounted ultrasonic radar is installed on the side of the robot, and the incremental encoder includes a left incremental encoder and a right incremental encoder, which are respectively installed on the wheel hubs on both sides of the robot.

[0019] As a preferred embodiment of the present invention, the control system includes a PLC controller, a switch, a wireless router, a host computer and an industrial computer; the PLC controller is connected to the switch via Ethernet, the switch is respectively connected to the visible light thermal imaging gimbal, the wireless router and the industrial computer via Ethernet, and the host computer interacts with and operates the robot data with the wireless router via wireless signals; the laser radar is connected to the industrial computer via Ethernet, and the collected tunnel wall model data is transmitted to the industrial computer in real time; the controller communicates with the right front ultrasonic obstacle avoider, the right middle front ultrasonic obstacle avoider, the right middle rear ultrasonic obstacle avoider, and the right rear ultrasonic obstacle avoider respectively via RS485 bus communication. , left front ultrasonic obstacle avoider, left middle front ultrasonic obstacle avoider, left middle rear ultrasonic obstacle avoider, left rear ultrasonic obstacle avoider, lifting and lodging device and multi-parameter gas sensor; the PLC controller is connected to the VCU controller through RS232 communication, and the VCU controller is connected to steering driver one, steering driver two, steering driver three and steering driver four respectively through RS485 bus communication, and each steering driver is connected to the left front push rod, right front push rod, left rear push rod and right rear push rod respectively through analog quantity; the VCU controller is connected to walking motor one, walking motor two, walking motor three and walking motor four respectively through CAN bus connection.

[0020] As a preferred embodiment of the present invention, the PLC controller receives the position information of the left and right incremental encoders via high-speed pulses; the PLC controller controls the left front light, right front light, left rear light and right rear light respectively in a digital manner.

[0021] As a preferred embodiment of the present invention, the control system is also used to analyze the stability of the communication signal established between the host computer and the robot, obtain the transmission time of the communication signal from the host computer to the robot, the proportion of data packets lost in a period of time to the total data packets, the strength of the communication signal and the degree of fluctuation of the communication delay, set an ideal value for each indicator, and assign weights to them, L0, P0, S0 and J0 are the ideal values ​​corresponding to each indicator respectively, aL, aP, aS and aJ are the weights of each indicator, and the sum of aL, aP, aS and aJ is 1, through the formula: The stability coefficient K is output, where L, P, S and J are the corresponding actual values ​​of each indicator. The upper computer sends an initialization instruction to the robot, and the robot feedbacks: if the stability coefficient is greater than the preset stability coefficient, the communication signal is judged to be normal, and the robot feedbacks that the communication signal connection is normal.

[0022] Compared with the prior art, the beneficial effects of the present invention are as follows: the laser radar of the present invention is only used as a tool for collecting information on the tunnel wall, and does not participate in mapping and path planning. The path planning and inspection position are applied through the upper computer, RFID, and PLC, which reflects the advantages of robot inspection and monitoring of long tunnels, and solves the problem that in the automatic inspection mode, due to the large number of long tunnels and forks in the coal mine underground scene, there are many similar scenes, and it is difficult to form an effective global matching reference in the SLAM process, which easily leads to the inability to clear the accumulated errors in the local area in time, and then leads to problems such as inaccurate inspection paths. On this basis, RFID is added to assist the robot in positioning in long-distance tunnels, and the dual obstacle avoidance protection of radar obstacle avoidance and ultrasonic radar reduces the occurrence of safety accidents and improves work efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to facilitate understanding by those skilled in the art, the present invention is further described below with reference to the accompanying drawings.

[0024] Figure 1 The method flow of the present invention;

[0025] Figure 2 It is a schematic diagram of the robot structure of the present invention;

[0026] Figure 3 The control system of the present invention Figure 1 ;

[0027] Figure 4 The control system of the present invention Figure 2 . DETAILED DESCRIPTION

[0028] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0029] It should be understood that the terms "include" and "comprising" used in the specification and claims of the present disclosure indicate the presence of described features, integers, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or collections thereof.

[0030] It should also be understood that the terms used in this disclosure are only for the purpose of describing specific embodiments and are not intended to limit the disclosure. As used in this disclosure and claims, the singular forms of "a", "an", and "the" are intended to include the plural forms unless the context clearly indicates otherwise. It should also be further understood that the term "and / or" used in this disclosure and claims refers to any combination of one or more of the associated listed items and all possible combinations, including these combinations.

[0031] Example 1: Please refer to Figure 1-4 As shown, a method for assisted driving in a long tunnel without obvious features is implemented based on a robot and a control system, wherein the robot is a hazardous gas inspection robot, and is equipped with a laser radar 39, several RFID positioning chips, a lifting rod falling device 19, a multi-parameter gas sensor 20, a mining intrinsically safe vehicle-mounted ultrasonic radar 4, an incremental encoder 5, an IMU gyroscope 6 and a visible light and thermal imaging gimbal 35; the incremental encoder 5 includes a left incremental encoder 40 and a right incremental encoder 41, and the laser radar 39 is a 16-line laser radar.

[0032] like Figure 2As shown, the control system includes a PLC controller 10, a switch 29, a wireless router 36, a host computer 37 and an industrial computer 38; the PLC controller 10, as the control core of the robot, is connected to the switch 29 via Ethernet, and the switch 29 is respectively connected to the visible light thermal imaging gimbal 35, the wireless router 36, and the industrial computer 38 via Ethernet, wherein the host computer 37 interacts with the wireless router 36 through wireless signals to perform data exchange and operation of the robot; the laser radar 39 is connected to the industrial computer 38 via Ethernet to collect the tunnel wall model data in real time The controller 10 is respectively connected with the right front ultrasonic obstacle avoider 11, the right middle front ultrasonic obstacle avoider 12, the right middle rear ultrasonic obstacle avoider 13, the right rear ultrasonic obstacle avoider 14, the left front ultrasonic obstacle avoider 15, the left middle front ultrasonic obstacle avoider 16, the left middle rear ultrasonic obstacle avoider 17, the left rear ultrasonic obstacle avoider 18, the lifting and lodging device 19, and the multi-parameter gas sensor 20 through the RS485 bus communication method. The function of this part is to collect the robot's obstacle avoidance data and the multi-parameter dangerous gas collection. The multi-parameter gas sensor 20 is installed on the lifting and lodging device 1 9, the lifting and lodging device 19 measures the dangerous gas at high altitude in the long tunnel by lifting the multi-parameter gas sensor 20; the PLC controller 10 is connected to the VCU controller 30 through RS232 communication, and the VCU controller 30 is connected to the steering driver 1 21, the steering driver 22, the steering driver 3 23 and the steering driver 4 24 through RS485 bus communication. Each steering driver is connected to the left front push rod 25, the right front push rod 26, the left rear push rod 27 and the right rear push rod 28 through analog quantity. This part of the function is to control the robot Angle steering; VCU controller 30 is connected to walking motor 1 31, walking motor 2 32, walking motor 33, and walking motor 4 34 respectively through CAN bus connection. The function of this part is to control the forward and backward travel and travel speed of the robot; PLC controller 10 receives the position information of incremental encoder left 40 and incremental encoder right 41 through high-speed pulse, which is used to record the total mileage of the robot and locate the inspection position; PLC controller 10 controls the left front light 42, right front light 43, left rear light 44 and right rear light 45 respectively in digital quantity.

[0033] The specific process is:

[0034] The host computer 37 selects the automatic inspection mode, the robot starts to start and starts self-inspection, the host computer 37 provides the setting parameters, including the target RFID point distance, the target RFID threshold size, the robot to the wall distance, the robot travel speed, the laser radar 39 collects the lane wall information in real time, obtains the data to calculate the distance and angle between the robot and the lane wall, and makes a difference with the given distance to calculate the angle of deviation from the lane wall, and obtains the error. The PID algorithm is used to obtain the robot angular velocity, which provides effective data for the robot to adjust its posture. The PLC controller 10 makes real-time judgment and analysis based on the data information transmitted by the laser radar 39 and the industrial computer 38, and corrects the electric push rod position in real time through the PID control algorithm according to the information such as the deviation angle and vertical distance, and adjusts the robot body posture in real time to ensure that the robot travels along the long lane. When the robot travels in the long-distance lane, it determines whether the target RFID point is identified. If yes, it continues to inspect; if not, it calculates the robot odometer information and compares it with the given RFID target threshold distance. If it exceeds the threshold distance, it returns to the host computer 37 for alarm. If it is within the threshold range, it continues to identify the target RFID point to ensure that the robot travels along the long lane. The PLC controller 10 makes real-time judgment and analysis based on the data information transmitted by the laser radar 39, RFID positioning chip, industrial computer 38 and ultrasonic obstacle avoider. According to the distance between the vehicle body and the obstacle, the PLC controller 10 judges and compares the driving state of the robot to accelerate, keep a constant speed, decelerate and stop. The inspection position of the robot is determined by two incremental encoders 5. The position information is collected by high-speed pulses and compared with the position value set by the host computer 37 to determine each hazardous gas collection position on the inspection route. The multi-parameter gas sensor 20 performs hazardous gas detection. After reaching the final position of the set long lane, the robot spins in place and returns to the original position along the original path, and the inspection process ends.

[0035] Embodiment 2: Based on Embodiment 1, the control system is also used to analyze the stability of the communication signal established between the host computer 37 and the robot, obtain the transmission time of the communication signal from the host computer 37 to the robot, the proportion of data packets lost in a period of time to the total data packets, the strength of the communication signal and the degree of fluctuation of the communication delay, set an ideal value for each indicator, and assign weights to them. L0, P0, S0 and J0 are the ideal values ​​corresponding to each indicator respectively, aL, aP, aS and aJ are the weights of each indicator, and the sum of aL, aP, aS and aJ is 1. By formula:

[0036] S and J are the corresponding actual values ​​of each indicator, and the upper computer 37 will send an initialization instruction to the robot, and the robot will feedback: if the stability coefficient is greater than the preset stability coefficient, the communication signal is determined to be normal, and the robot will feedback that the communication signal connection is normal.

[0037] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. A method for assisting driving in long lanes without obvious features, based on a robot and a control system, characterized in that: The following steps are involved: The host computer (37) selects the automatic inspection mode, and the robot starts and begins self-inspection; The host computer (37) provides setting parameters; The laser radar (39) collects tunnel wall information in real time to obtain data, calculates the distance and angle between the robot and the tunnel wall, and makes a difference with the given distance to calculate the angle of deviation from the tunnel wall to obtain the error, and uses the PID algorithm to obtain the robot angular velocity; The PLC controller (10) performs real-time judgment and analysis based on the data information transmitted by the laser radar (39) and the industrial computer (38), and corrects the position of the electric push rod in real time through the PID control algorithm according to the deviation angle and the vertical distance, and adjusts the robot body posture in real time; The robot travels in a long-distance lane and determines whether it has identified the target RFID point. If so, it continues the inspection; If not, the robot odometer information is calculated and compared with the given RFID target threshold distance. If the threshold distance is exceeded, it is returned to the host computer (37) for alarm. If it is within the threshold range, the target RFID point is continuously identified; The PLC controller (10) performs real-time judgment and analysis based on the data information transmitted by the laser radar (39), the RFID positioning chip, the industrial computer (38) and the ultrasonic obstacle avoider, and judges and compares the driving state of the robot, such as acceleration, constant speed, deceleration and parking, through the PLC controller (10) according to the distance between the vehicle body and the obstacle; By comparing the position information collected by high-speed pulses with the position value set by the host computer (37), each hazardous gas collection position on the inspection route is determined, and the multi-parameter gas sensor (20) performs hazardous gas detection; After reaching the final position of the set long alley, the robot spins on the spot and returns to the original position along the original path, and the inspection process ends.

2. The method for assisting driving in a long lane without obvious features according to claim 1, characterized in that: The parameters include the target RFID point distance, the target RFID threshold value, the robot-to-wall distance and the robot travel speed.

3. The method for assisting driving in a long lane without obvious features according to claim 1, characterized in that: The robot is equipped with a laser radar (39), a plurality of RFID positioning chips, a lifting and lowering device (19), a multi-parameter gas sensor (20), a mining intrinsically safe vehicle-mounted ultrasonic radar (4), an incremental encoder (5), an IMU gyroscope (6) and a visible light and thermal imaging gimbal (35); wherein the laser radar (39) and the visible light and thermal imaging gimbal (35) are installed on the upper end surface of the robot; the multi-parameter gas sensor (20) is installed on the lifting and lowering device (19), the mining intrinsically safe vehicle-mounted ultrasonic radar (4) is installed on the side of the robot, and the incremental encoder (5) includes a left incremental encoder (40) and a right incremental encoder (41), which are respectively installed on the wheel hubs on both sides of the robot.

4. The method for assisting driving in a long lane without obvious features according to claim 3, characterized in that: The control system comprises a PLC controller (10), a switch (29), a wireless router (36), a host computer (37) and an industrial computer (38); the PLC controller (10) is connected to the switch (29) via Ethernet, the switch (29) is respectively connected to the visible light thermal imaging gimbal (35), the wireless router (36) and the industrial computer (38) via Ethernet, and the host computer (37) performs data exchange and operation of the robot with the wireless router (36) via wireless signals; the laser radar (39) is connected to the industrial computer (38) via Ethernet, and the collected lane wall model data is transmitted to the industrial computer (38) in real time; the controller (10) is respectively connected to the right front ultrasonic obstacle avoider (11), the right middle front ultrasonic obstacle avoider (12), the right middle rear ultrasonic obstacle avoider (13), the right rear ultrasonic obstacle avoider (14), the left front ultrasonic obstacle avoider (15), the left rear ultrasonic obstacle avoider (16) and the right front ultrasonic obstacle avoider (17) via RS485 bus communication. 15), a left middle front ultrasonic obstacle avoider (16), a left middle rear ultrasonic obstacle avoider (17), a left rear ultrasonic obstacle avoider (18), a lifting and lowering device (19) and a multi-parameter gas sensor (20); the PLC controller (10) is connected to the VCU controller (30) through RS232 communication mode, the VCU controller (30) is respectively connected to a steering driver 1 (21), a steering driver 2 (22), a steering driver 3 (23) and a steering driver 4 (24) through RS485 bus communication mode, each steering driver is respectively connected to a left front push rod (25), a right front push rod (26), a left rear push rod (27) and a right rear push rod (28) through analog quantity mode; the VCU controller (30) is respectively connected to a travel motor 1 (31), a travel motor 2 (32), a travel motor 3 (33) and a travel motor 4 (34) through CAN bus connection mode.

5. The method for assisting driving in a long lane without obvious features according to claim 4, characterized in that: The PLC controller (10) receives position information of a left incremental encoder (40) and a right incremental encoder (41) in a high-speed pulse manner; the PLC controller (10) controls the left front light (42), the right front light (43), the left rear light (44) and the right rear light (45) in a digital quantity manner.

6. The method for assisting driving in a long lane without obvious features according to claim 4, characterized in that: The control system is also used to analyze the stability of the communication signal established between the host computer (37) and the robot, obtain the transmission time of the communication signal from the host computer (37) to the robot, the proportion of the data packets lost in a period of time to the total data packets, the strength of the communication signal and the degree of fluctuation of the communication delay, set an ideal value for each indicator, and assign a weight to it, L0, P0, S0 and J0 are the ideal values ​​corresponding to each indicator respectively, aL, aP, aS and aJ are the weights of each indicator, through the formula: Output a stability coefficient K, where L, P, S and J are the corresponding actual values ​​of each indicator, and the upper computer (37) sends an initialization instruction to the robot, and the robot feedbacks: if the stability coefficient is greater than the preset stability coefficient, the communication signal is determined to be normal, and the robot feedbacks that the communication signal connection is normal.

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