Control method of storage tank cleaning robot and storage tank cleaning robot

Abstract

The invention provides a control method of a storage tank cleaning robot and the storage tank cleaning robot, and the control method of the storage tank cleaning robot comprises the steps: obtaining a storage tank internal map corresponding to a storage tank inner wall space to be cleaned by the storage tank cleaning robot; when it is detected that the obstacles exist in the inner wall space of the storage tank, the positions of the obstacles are marked in a map in the storage tank; based on the storage tank internal map marked with the positions of the obstacles, a first planned path of the storage tank cleaning robot is determined, and the first planned path bypasses the positions of the obstacles; and the storage tank cleaning robot is controlled to conduct displacement movement according to the first planning path, so that the storage tank cleaning robot cleans the storage tank area where the first planning path passes. Therefore, the storage tank cleaning robot can automatically recognize and position the obstacles in the inner wall of the storage tank, autonomous map navigation for bypassing the obstacles in the space of the inner wall of the storage tank is achieved, and high-automation cleaning operation of the inner wall of the storage tank is completed.

Description

Technical Field

[0001] The present invention relates to the technical field of petrochemical equipment, and in particular to a control method of a storage tank cleaning robot and the storage tank cleaning robot. Background Art

[0002] At present, in the field of petrochemicals, the cleaning process of oil storage tanks is mainly mechanical cleaning, assisted by manual cleaning. It has a series of problems such as long cleaning time, high safety risks and poor cleaning effect.

[0003] In the above context, intelligent cleaning robots have developed rapidly. Taking crude oil storage tanks as an example, heavy components such as paraffin and asphalt in the oil products, as well as impurities such as soil and heavy metal salts, will naturally settle and accumulate at the bottom of the oil tank due to the difference in specific gravity, forming sludge, which reduces the effective capacity of the oil tank and affects storage and transportation production. The high-pressure jet and strong suction function of the intelligent cleaning robot can safely and efficiently remove the sludge in the tank, ensure the safety of personnel, and reduce labor costs.

[0004] However, the operation path of the intelligent cleaning robot is generally relatively simple, such as a simple zigzag reciprocating movement. However, during the movement of the intelligent cleaning robot, it is easy to collide with obstacles, resulting in damage to the robot equipment and manual maintenance. It is also difficult to achieve autonomous cleaning operations on dirty areas on the inner wall of the tank.

[0005] The industry has not yet proposed a better solution to the above problems. Summary of the invention

[0006] The present invention provides a control method for a tank cleaning robot, a tank cleaning robot and a non-transitory computer-readable storage medium, which are used to at least solve the defects in the prior art that the tank cleaning robot is prone to hit obstacles when moving in the inner wall of the tank and cannot independently complete the cleaning of the inner wall of the tank.

[0007] The present invention provides a control method for a tank cleaning robot, the method comprising: obtaining a tank internal map corresponding to the tank inner wall space to be cleaned by the tank cleaning robot; marking the position of the obstacle in the tank internal map when an obstacle is detected in the tank inner wall space; determining a first planned path of the tank cleaning robot based on the tank internal map with the position of the obstacle marked, the first planned path bypassing the position of the obstacle; and controlling the tank cleaning robot to move according to the first planned path, so that the tank cleaning robot cleans the tank area passed by the first planned path.

[0008] According to a control method for a tank cleaning robot provided by the present invention, the first planned path of the tank cleaning robot is determined based on an internal map of the tank with the position of the obstacle marked, comprising: determining a map unit set corresponding to the internal map of the tank, each map unit in the map unit set having the same grid unit size; determining a target map unit corresponding to a moving start position and a moving end position of the tank cleaning robot based on a map unit in the map unit set corresponding to a manhole opening position of an inner wall space of the tank; determining an obstacle map unit in the map unit set corresponding to the position of the obstacle; and determining a first planned path of the tank cleaning robot based on the map unit set, the first planned path passing through the target map unit and bypassing the obstacle map unit.

[0009] According to a control method for a tank cleaning robot provided by the present invention, determining a first planned path of the tank cleaning robot based on the map unit set includes: processing the map unit set according to a preset longest path planning algorithm to determine the first planned path of the tank cleaning robot.

[0010] According to a control method for a tank cleaning robot provided by the present invention, the map unit set is processed according to a preset longest path planning algorithm to determine a first planned path of the tank cleaning robot, including: determining a first candidate planned path set of the tank cleaning robot according to the map unit set, each first candidate planned path in the first candidate planned path set passes through the target map unit and bypasses the obstacle map unit; determining the number of map units respectively corresponding to each of the first candidate planned paths in the first candidate planned path set, the number of map units being the number of map units passed by the first candidate planned path; determining the first planned path of the tank cleaning robot based on the first candidate planned path in the first candidate planned path set corresponding to the first candidate planned path with the largest number of map units.

[0011] According to a control method for a tank cleaning robot provided by the present invention, after determining a first planned path of the tank cleaning robot according to the map unit set, the method includes: determining a legacy map unit set according to the map unit set and the first planned path, the legacy map unit set being a collection of map units in the map unit set except for each map unit passed by the first planned path and the obstacle map unit; determining a second planned path passing through each legacy map unit in the legacy map unit set; and controlling the tank cleaning robot to move according to the second planned path, so that the tank cleaning robot cleans the tank area passed by the second planned path.

[0012] According to a control method for a tank cleaning robot provided by the present invention, determining a second planned path passing through at least one legacy map unit in the legacy map unit set includes: processing the legacy map unit set according to a preset shortest path planning algorithm to determine the second planned path of the tank cleaning robot.

[0013] According to a control method for a tank cleaning robot provided by the present invention, the legacy map unit set is processed according to a preset shortest path planning algorithm to determine a second planned path for the tank cleaning robot, comprising: determining a second candidate planned path set for the tank cleaning robot according to the legacy map unit set, wherein each second candidate planned path in the second candidate planned path set passes through each legacy map unit in the legacy map unit set; for each second candidate planned path in the second candidate planned path set, based on the number of second map units corresponding to the second candidate planned path and the number of legacy map unit passes, determining a path cost value corresponding to the second candidate planned path; the number of legacy map unit passes is the number of legacy map units passed by the second candidate planned path; the path cost value is positively correlated with the number of second map units, and the path cost value is negatively correlated with the number of legacy map unit passes; and determining an additional planned path based on the second candidate planned path corresponding to the smallest path cost value in the second candidate planned path set.

[0014] According to a control method for a tank cleaning robot provided by the present invention, the method controls the tank cleaning robot to move according to the first planned path so that the tank cleaning robot cleans the tank area corresponding to the first planned path, comprising: when it is detected that the real-time map unit where the tank cleaning robot is located is adjacent to the obstacle map unit when moving, controlling and adjusting the posture of a nozzle flushing module of the tank cleaning robot according to the map unit relative orientation of the real-time map unit relative to the obstacle map unit; and starting the nozzle flushing module to flush the obstacle map unit.

[0015] According to a control method for a tank cleaning robot provided by the present invention, obtaining a tank internal map corresponding to the tank inner wall space to be cleaned by the tank cleaning robot includes: based on a depth camera, collecting depth information corresponding to the tank inner wall space to be cleaned by the tank cleaning robot; and constructing a tank internal map based on the collected depth information.

[0016] The present invention also provides a tank cleaning robot, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, a control method for the tank cleaning robot as described above is implemented.

[0017] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the control method of the tank cleaning robot as described in any one of the above is implemented.

[0018] The present invention provides a control method and a tank cleaning robot, which obtains a tank internal map of the tank inner wall space, detects obstacles in the tank inner wall space, and marks their positions in the tank internal map, thereby determining a planned path and controlling the tank cleaning robot to move according to the planned path. As a result, the tank cleaning robot can automatically identify and locate obstacles in the tank inner wall, realize autonomous map navigation of the tank inner wall space to bypass obstacles, and complete a highly automated tank inner wall cleaning operation. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions in the present invention or related technologies, the following briefly introduces the drawings required for use in the embodiments or related technical descriptions. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0020] Figure 1 A flowchart showing an example of a control method for a tank cleaning robot according to an embodiment of the present invention is shown;

[0021] Figure 2 Shown according to Figure 1 An exemplary operation flow chart of step S130 in FIG.

[0022] Figure 3 A structural block diagram showing an example of a control system of a tank cleaning robot according to an embodiment of the present invention;

[0023] Figure 4 A flowchart of an example of determining a first planning path by using a D* optimization algorithm according to an embodiment of the present invention is shown;

[0024] Figure 5 A schematic diagram showing an example of a tank cleaning robot locally planning and moving in a tank internal map;

[0025] Figure 6 A flowchart showing an example of a control method for a tank cleaning robot according to an embodiment of the present invention is shown;

[0026] Figure 7 It is a structural schematic diagram of the electronic device provided by the present invention. DETAILED DESCRIPTION

[0027] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are 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.

[0028] It should be noted that when the cleaning robot moves in the tank, it needs to avoid the protruding anode blocks, heating coils and other components at the bottom of the tank. Therefore, path planning to avoid collisions with obstacles in complex working spaces is one of the key technologies of the tank cleaning robot, which involves environmental map construction, obstacle monitoring, path planning and other issues.

[0029] Figure 1 A flowchart showing an example of a control method of a tank cleaning robot according to an embodiment of the present invention is shown.

[0030] Regarding the execution subject of the method of the embodiment of the present invention, it can be any controller or processor with computing or processing capabilities to achieve the goal of controlling the tank cleaning robot to clean the dirty area of ​​the inner wall of the tank. In some examples, it can be integrated and configured in the tank cleaning robot by software, hardware, or a combination of software and hardware, which should not be limited here.

[0031] The following will take the tank cleaning robot as an exemplary implementation subject to introduce the details of the technical solution involved in the present invention. However, it should be understood that one or more steps involved in the following process can be implemented by one or more controllers or software installed and deployed in the tank cleaning robot.

[0032] like Figure 1 As shown, in step S110, a tank internal map corresponding to the tank inner wall space to be cleaned by the tank cleaning robot is obtained.

[0033] In one example of the embodiment of the present invention, the environment of the inner wall of the tank to be inspected can be simulated in advance by modeling software, and a corresponding tank internal map can be generated, which can then be preset in the tank cleaning robot. In another example of the embodiment of the present invention, the tank cleaning robot can model the environment of the inner wall of the tank in real time while moving on the inner wall of the tank to determine the corresponding tank internal map.

[0034] In step S120, when it is detected that there is an obstacle in the inner wall space of the tank, the position of the obstacle is marked in the internal map of the tank.

[0035] Here, the tank cleaning robot can detect obstacles in the inner wall space of the tank through various obstacle recognition technologies. For example, the tank cleaning robot can actively sense obstacles in the environment (e.g., anode blocks, heating coils, etc.) and inaccessible locations such as tank walls through a two-dimensional laser radar ranging sensor, and mark them.

[0036] In step S130, based on the internal map of the tank on which the positions of obstacles are marked, a first planned path of the tank cleaning robot is determined, and the first planned path bypasses the positions of the obstacles.

[0037] It should be understood that the tank cleaning robot can use various types of path planning algorithms to plan a path that can bypass the position of the obstacle, which should not be limited here. In addition, the coverage of the first planned path can also be diversified. In one example of an embodiment of the present invention, the first planned path can cover all areas except the position of the obstacle in the internal map of the tank to achieve comprehensive cleaning of the inner wall of the tank. In another example of an embodiment of the present invention, the first planned path is a local or most area in the internal map of the tank except the position of the obstacle.

[0038] In step S140, the tank cleaning robot is controlled to move according to the first planned path, so that the tank cleaning robot cleans the tank area passed by the first planned path.

[0039] In some embodiments, the tank cleaning robot is equipped with a high-pressure jet module and a strong suction module, which can complete deep cleaning of the inner wall area it passes through.

[0040] In the embodiment of the present invention, the tank cleaning robot identifies obstacles in the inner wall space of the tank, and marks the location of the obstacles in the internal map of the tank, and then uses the internal map of the tank to complete the autonomous mobile navigation operation. As a result, the tank cleaning robot can automatically identify and locate obstacles in the inner wall of the tank, navigate the tank cleaning robot through map path planning, and realize autonomous navigation of the tank cleaning robot to complete the cleaning operation of the inner wall of the tank, and can also prevent the tank cleaning robot from colliding with obstacles during movement, which can avoid damage to the tank cleaning robot or damage to the internal structure of the tank by the tank cleaning robot.

[0041] Regarding the above step S110, in some embodiments, the tank cleaning robot can collect depth information corresponding to the inner wall space of the tank to be cleaned by the tank cleaning robot based on the depth camera, and then build an internal map of the tank based on the collected depth information. Therefore, the tank cleaning robot solves the problem of being sensitive to ambient light during visual map construction by using the depth camera without relying on external light sources, and realizes the automated map construction operation of the inner wall space of the tank with dark ambient light.

[0042] Preferably, the depth camera can adopt an active ranging structured light RGB-D camera, which has high measurement accuracy (can reach mm level) and long measurement distance (can reach 10m, covering the inner wall space depth of a general storage tank).

[0043] Through the embodiments of the present invention, the tank cleaning robot is able to quickly identify obstacles in a complex tank environment with poor lighting conditions and static obstacles, and automatically plan a reasonable travel path, so that the cleaning robot can achieve the highest coverage and lowest repetition rate during operation, and has more efficient and stable autonomous navigation capabilities.

[0044] Figure 2 Shown according to Figure 1 An example operation flow chart of step S130 in FIG.

[0045] like Figure 2 As shown, in step S210, a map unit set corresponding to the internal map of the storage tank is determined, and each map unit in the map unit set has the same grid unit size.

[0046] In some implementations, the internal map of the storage tank is segmented using two-dimensional space units having a preset grid unit size to determine a map unit set corresponding to the internal map of the storage tank.

[0047] It should be understood that the size and / or shape of the grid unit corresponding to the map unit can be diverse and should not be limited here. Exemplarily, the size of the grid unit corresponding to the map unit is greater than or equal to the outer dimensions of the tank cleaning robot, so that the tank cleaning robot can successfully pass through each map unit.

[0048] In step S220, based on the map unit corresponding to the manhole opening position of the inner wall space of the tank in the map unit set, the target map unit corresponding to the moving start position and the moving end position of the tank cleaning robot is determined.

[0049] It should be noted that the manhole opening position of the tank is the position for manually taking and placing the tank cleaning robot into the inner wall space of the tank. It can be used as the starting point and end point of the moving planning path of the tank cleaning robot to facilitate the operator to take and place the tank cleaning robot, and is conducive to improving the efficiency of cleaning multiple tanks in turn.

[0050] In step S230, an obstacle map unit corresponding to the position of the obstacle in the map unit set is determined. Specifically, the position of the obstacle is matched with each map unit in the map unit set to determine the corresponding obstacle map unit.

[0051] In step S240, a first planned path of the tank cleaning robot is determined according to the map unit set, and the first planned path passes through the target map unit and bypasses the obstacle map unit. Thus, the first planned path can pass through the target map unit and bypass the obstacle map unit, so that the tank cleaning robot can automatically navigate around the obstacle and can also ensure that the tank cleaning robot can return to the manhole position, which is convenient for the operator to recover the tank cleaning robot.

[0052] In some examples of the embodiments of the present invention, when controlling the tank cleaning robot to move according to the first planned path, the tank cleaning robot can locate the current real-time map unit in real time and identify and detect the types of adjacent map units. Furthermore, when the tank cleaning robot detects that the real-time map unit where the tank cleaning robot is located when it moves is adjacent to the obstacle map unit, the tank cleaning robot controls and adjusts the posture of the nozzle flushing module of the tank cleaning robot according to the relative orientation of the map unit of the real-time map unit relative to the obstacle map unit, and then starts the nozzle flushing module to flush the obstacle map unit. As a result, the tank cleaning robot can use the nozzle flushing module to complete the cleaning of obstacles that cannot be passed (for example, anode blocks, heating coils, etc.), and achieve comprehensive cleaning of the inner wall of the tank.

[0053] Figure 3 A structural block diagram of an example of a control system of a tank cleaning robot according to an embodiment of the present invention is shown.

[0054] like Figure 3 As shown, the control system 300 of the tank cleaning robot includes a map construction module 310, a positioning module 320, a target detection module 330, a path planning module 340 and a control storage module 350. Among them, the control system 300 of the tank cleaning robot can be set inside the tank cleaning robot to realize autonomous planning of the path of the tank cleaning robot.

[0055] Specifically, the positioning module 310 can adopt a visual inertial navigation SLAM positioning and navigation device, receive visual image signals through the RGB-D camera in the device, build a global map of the tank, output visual navigation SLAM positioning data, calculate the robot's speed / acceleration, rotation / tilt angle and displacement data through the IMU sensor, obtain the motion trajectory information of the robot's path through the solution, output inertial navigation SLAM positioning data, realize real-time positioning of the robot, and transmit it to the control storage module 350.

[0056] The map construction module 320 is based on the planning method of the environmental model to establish the internal environmental model of the tank. Specifically, the positioning module receives the visual image signal based on the RGB-D camera in the visual inertial navigation SLAM positioning device, constructs the global map of the tank, and outputs the visual navigation SLAM positioning data; the IMU sensor calculates the speed / acceleration, rotation / tilt angle and displacement data of the robot, and obtains the motion trajectory information of the robot through the path through the solution, outputs the inertial navigation SLAM positioning data, and realizes the real-time positioning of the robot. The map construction module automatically generates the internal map model of the tank through the known global map and the computer environment modeling software, and transmits it to the control storage module 350.

[0057] The target detection module 330 is also called the obstacle detection module. It uses a two-dimensional laser radar ranging sensor to actively sense obstacles (anode blocks, heating coils, etc.) and impassable locations such as tank walls to obtain a local map and mark them, thereby making up for the shortcomings of visual SLAM in constructing a global map of the tank, that is, obstacles that are not marked in the global map are supplemented with marks, and the above obstacle marks are synchronized and transmitted to the map construction module. The map construction module integrates the global map and the partial map data, and uses computer environment modeling software to automatically generate an internal map model of the tank and transmit it to the control storage module 350.

[0058] Furthermore, the lidar ranging sensor can be installed in the middle position directly in front of the robot, which can sense obstacles within a 120° fan-shaped section at a distance of 5 to 10 meters in front of the robot, and mark them and record them in the internal map of the tank.

[0059] Furthermore, the robot's displacement wheel system adopts omnidirectional four-wheel drive, and all four wheels are Mecanum wheels, which are powered by explosion-proof motors, giving the robot omnidirectional movement capabilities of forward, backward, mobile steering and on-the-spot steering.

[0060] In some embodiments, the map model established by the map construction module 310 is a method of modeling a map based on the grid method using computer VB software. The process is to simulate the global map and the local map after the tank fusion as a collection of small grids, including obstacles and tank boundaries, and use the D* algorithm to perform binary simulation replacement on all targets in the map model in the scene. For example, the position where there is an obstacle and cannot be passed is assigned to 1, and the position that can be passed normally is assigned to 0.

[0061] The path planning module 340 is to achieve the following goals: determine the starting and ending positions of the robot, reasonably avoid obstacles, and optimize the moving path with as little repetition as possible and a large coverage area. In order to achieve the above goals, the map model established by the map construction module is first divided into grids. For example, the internal map of the tank contains a total of m×n grids, and the robot can only be in one of the grids. Obstacles or boundaries can occupy multiple grid positions; when the robot is in a grid that is not adjacent to an obstacle or boundary, there are a total of 8 movable grids around it (grids 1 to 8); at the same time, it is stipulated that each command action can only allow the robot to move to one of the 8 grids (including oblique grids); the distance between two adjacent grids is 1 unit (for ease of understanding, the distance between the grids at two oblique angles is also regarded as 1 unit);

[0062] Furthermore, the current coordinate position of the robot in the map model can be determined by the positioning module 320. The present invention stipulates that the starting and ending positions of the robot are the same point A (i.e., the manhole position of the tank); the path planning module uses the D* algorithm to assign values ​​to each grid in the tank map model and perform path planning for it, wherein the inaccessible grids are assigned a value of 1 (such as the tank boundary, obstacles), the grids that can be moved normally are assigned a value of 0, and at the same time, the grids that the robot has moved are also assigned a value of 1.

[0063] Figure 4 A flowchart of an example of determining a first planned path by using a D* optimization algorithm according to an embodiment of the present invention is shown.

[0064] like Figure 4As shown, the following calculations are completed by the D* optimization algorithm. First, the starting point of the tank cleaning robot is set to point A at the manhole opening. Because its ultimate goal is to clean the entire tank and recycle it, the end point of the robot's moving path is also A. Then, create an open list to save all generated but unchecked grids, that is, grids waiting to be checked; at the same time, create a closed list to save all checked grids, and add the starting point (end point) A to the open list. Then, check the open list to find the grid with the maximum value of the K(X) (cost estimation function), where the K value is the basis for the priority queue open list, and its maximum value Kmax data is ranked first. At the same time, add the grid to the open list to wait for inspection.

[0065] Furthermore, K(X, Y) represents the estimated cost of the path between X and Y, which is called a cost estimation function. For the present invention, K(A, A) represents the estimated cost from the starting point A to the end point A.

[0066] K(X, Y)=G(X, Y)+H(X, Y) Formula (1)

[0067] Among them, G(X,Y) represents the estimated cost of moving from the starting point X grid to the Y grid, and H(X,Y) represents the estimated cost of moving from the starting point Y grid back to the X grid. The physical meaning of the G function and the H function represent the corresponding displacement functions, and only 1 unit can be moved each time (the movement between two oblique angles is also considered as 1 unit).

[0068] It should be noted that compared with the traditional D* algorithm for finding the shortest optimal path, in order to enable the tank cleaning robot to maximize the cleaning of the tank bottom plate, the inverse solution method of the D* algorithm is adopted in the present invention, that is, to find the longest optimal path for the robot's movement route, allowing the starting point A to move in an oblique direction.

[0069] Figure 5 A schematic diagram showing an example of a tank cleaning robot locally planning and moving in a tank interior map.

[0070] like Figure 5 As shown, the tank cleaning robot can check the 8 adjacent grids (subgrids) around the current grid. If there is an unreachable tank boundary or obstacle in the subgrid (i.e., a grid with a value of 1), it will be added to the closed list and will no longer be checked. The following operations are only for subgrids that can move normally (i.e., grids with a value of 0).

[0071] Specifically, if the adjacent subgrid is not in the open list, it is added to the open list, and the subgrid is set as the current processing grid, and then the values ​​of the K function, G function and H function are recalculated. If the adjacent grid grid already exists in the open list, and after calculation, as long as the new K function value is larger than the original K function value (that is, the estimated cost becomes larger), the subgrid of the adjacent subgrid is set as the current processing grid, and the K function value is recalculated.

[0072] Furthermore, when the tank cleaning robot moves to the next grid unit, the above steps are repeated to determine the displacement of the next step until the tank cleaning robot reaches the end point, thereby finding the longest path of the robot's movement route through the D* algorithm, that is, the tank cleaning robot starts from the starting point A and moves along the sub-nodes of each grid until it returns to the end point A after spending the maximum cost.

[0073] Furthermore, the path planning information is transmitted to the control storage module 350 to execute the movement control command of the robot. Specifically, the control storage module 350 is used to receive the global map information and robot positioning information provided by the visual inertial navigation SLAM positioning device transmitted by the positioning module 320, the map construction module 310 and the target detection module 330, as well as the local map information and obstacle position information provided by the laser radar ranging sensor. The control storage module 350 further processes the above information and transmits it to the path planning module 340. After the built-in algorithm of the path planning module 340 calculates the optimal route of the robot, the information is fed back to the control storage module 350 to control the robot's mobile operation.

[0074] In the embodiment of the present invention, a map model in an unfamiliar and complex environment is accurately established through a visual inertial navigation SLAM positioning device and a laser radar ranging sensor, and the tank boundaries, obstacles and robots therein are accurately positioned. In addition, a local path planning method based on the grid method is adopted to simulate the map model as binary information, and the inverse algorithm of the D* local path planning algorithm is applied to plan the maximum path inside the tank according to the operation requirements of the tank cleaning robot, which can effectively improve the robot cleaning operation efficiency and expand the robot's cleaning range.

[0075] Figure 6 A flowchart showing an example of a control method of a tank cleaning robot according to an embodiment of the present invention is shown.

[0076] like Figure 6 As shown, in step S610, a tank internal map corresponding to the tank inner wall space to be cleaned by the tank cleaning robot is obtained.

[0077] In step S620, when it is detected that there is an obstacle in the inner wall space of the tank, the position of the obstacle is marked in the internal map of the tank.

[0078] In step S630, a map unit set corresponding to the internal map of the storage tank is determined, and each map unit in the map unit set has the same grid unit size.

[0079] In step S640, based on the map unit corresponding to the manhole opening position of the inner wall space of the tank in the map unit set, the target map unit corresponding to the moving start position and the moving end position of the tank cleaning robot is determined.

[0080] In step S650, an obstacle map unit corresponding to the position of the obstacle in the map unit set is determined.

[0081] In step S660, the map unit set is processed according to a preset longest path planning algorithm to determine a first planned path of the tank cleaning robot, where the first planned path passes through the target map unit and bypasses the obstacle map unit.

[0082] In some embodiments, the tank cleaning robot processes the map unit set according to a preset longest path planning algorithm to determine a first planned path of the tank cleaning robot.

[0083] It should be noted that according to the tank cleaning robot's degree of mastery of the environment of the inner wall space of the tank, path planning can be divided into two categories, namely, global path planning that fully masters the map information in the workspace, and local path planning that does not fully master the map information in the workspace.

[0084] In one example of an embodiment of the present invention, the tank cleaning robot can use the inverse solution model of the D* algorithm to solve the map unit set to determine the longest path for the tank cleaning robot to start moving from the manhole opening position and return to the manhole opening position, for example, the planned path corresponds to the maximum number of map units. Thus, through the first planned path, the tank cleaning robot moves the maximum path distance in the inner wall of the tank, realizing the single maximum range cleaning process of the inner wall of the tank.

[0085] Therefore, through local path planning design, the focus is on considering the current local environmental information of the tank cleaning robot, the internal environment of the tank is monitored, and the dynamic update of the environmental model can be corrected at any time. It has high robustness to environmental errors and noise, and can provide real-time feedback and correction of the planning results.

[0086] In another example of the embodiment of the present invention, the tank cleaning robot can also perform global path planning based on the internal map of the tank. It should be noted that the accuracy of global path planning depends on the accuracy of environmental acquisition, and does not require high real-time computing capabilities of the robot system.

[0087] Specifically, the tank cleaning robot determines the first candidate planning path set of the tank cleaning robot according to the map unit set, and each first candidate planning path in the first candidate planning path set passes through the target map unit and bypasses the obstacle map unit. In some embodiments, the tank cleaning robot can calculate the first candidate planning path corresponding to the tank cleaning robot through a variety of different path planning algorithms, and obtain the first candidate planning path set by summarizing. Furthermore, the tank cleaning robot determines the number of map units corresponding to each first candidate planning path in the first candidate planning path set, and the number of map units is the number of map units passed by the first candidate planning path. Based on the first candidate planning path corresponding to the largest number of map units in the first candidate planning path set, the first planning path of the tank cleaning robot is determined. Exemplarily, the first candidate planning paths determined by each path planning algorithm are compared to find the first candidate planning path corresponding to the largest number of map units passed, and use it as the first planning path.

[0088] In step S670, the tank cleaning robot is controlled to move according to the first planned path, so that the tank cleaning robot cleans the tank area along the first planned path. Thus, the tank cleaning robot can clean the maximum range of the tank inner wall in a single cleaning process.

[0089] In step S680, a legacy map unit set is determined according to the map unit set and the first planned path, where the legacy map unit set is a collection of map units in the map unit set except for the map units and obstacle map units passed by the first planned path.

[0090] In step S690, a second planned path passing through each legacy map unit in the legacy map unit set is determined.

[0091] In some embodiments, the set of legacy map units is processed according to a preset shortest path planning algorithm to determine a second planned path for the tank cleaning robot. It should be understood that the second planned path can be a single path or contain multiple sub-paths, for example, composed of multiple sub-paths for different legacy map units. As a result, the tank robot can perform targeted cleaning on the map units that were omitted from cleaning in the first planned path, thereby improving cleaning efficiency.

[0092] Specifically, according to the legacy map unit set, a second candidate planning path set of the tank cleaning robot is determined, and each second candidate planning path in the second candidate planning path set passes through each legacy map unit in the legacy map unit set. Then, for each second candidate planning path in the second candidate planning path set, based on the number of second map units corresponding to the second candidate planning path and the number of legacy map unit passes, the path cost value corresponding to the second candidate planning path is determined. Here, the number of legacy map unit passes is the number of legacy map units passed by the second candidate planning path.

[0093] It should be noted that the path cost value is positively correlated with the number of second map units, that is, the higher the number of map units passed by the second candidate planning path, the higher the corresponding path cost value. In addition, the path cost value is negatively correlated with the number of legacy map units passed, that is, the higher the number of legacy map units passed by the second candidate planning path, the lower the corresponding path cost value.

[0094] Exemplarily, the path cost value R may be determined by:

[0095] R = N1*w1 - N2*w2 Formula (2)

[0096] Wherein, N1 represents the number of second map units, N2 represents the number of legacy map units passed, and w1 and w2 represent preset weight values ​​respectively.

[0097] In step S6110, the tank cleaning robot is controlled to move according to the second planned path, so that the tank cleaning robot cleans the tank area along the second planned path. Thus, through the second planned path, the tank cleaning robot can efficiently and quickly perform secondary supplementary cleaning on the area of ​​the tank inner wall that is not covered by the first planned path, expand the range of the tank inner wall that is autonomously cleaned by the robot, and achieve comprehensive cleaning of the tank inner wall.

[0098] Figure 7 The following is a schematic diagram of the physical structure of a tank cleaning robot. Figure 7As shown, the electronic device may include: a processor 710, a communication interface 720, a memory 730 and a communication bus 740, wherein the processor 710, the communication interface 720 and the memory 730 communicate with each other through the communication bus 740. The processor 710 may call the logic instructions in the memory 730 to execute the control method of the tank cleaning robot, the method comprising: obtaining a tank internal map corresponding to the tank inner wall space to be cleaned by the tank cleaning robot; in the case where an obstacle is detected in the tank inner wall space, marking the position of the obstacle in the tank internal map; based on the tank internal map with the position of the obstacle marked, determining a first planned path of the tank cleaning robot, the first planned path bypassing the position of the obstacle; controlling the tank cleaning robot to move according to the first planned path, so that the tank cleaning robot cleans the tank area passed by the first planned path.

[0099] In addition, the logic instructions in the above-mentioned memory 730 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

[0100] On the other hand, the present invention also provides a computer program product, which includes a computer program. The computer program can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the control method of the tank cleaning robot provided by the above-mentioned methods, the method including: obtaining an internal tank map corresponding to the inner wall space of the tank to be cleaned by the tank cleaning robot; when an obstacle is detected in the inner wall space of the tank, marking the position of the obstacle in the internal tank map; based on the internal tank map with the position of the obstacle marked, determining a first planned path of the tank cleaning robot, the first planned path bypassing the position of the obstacle; controlling the tank cleaning robot to move according to the first planned path, so that the tank cleaning robot cleans the tank area passed by the first planned path.

[0101] On the other hand, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, is implemented to execute the control method of the tank cleaning robot provided by the above-mentioned methods, the method comprising: obtaining an internal tank map corresponding to the inner wall space of the tank to be cleaned by the tank cleaning robot; when an obstacle is detected in the inner wall space of the tank, marking the position of the obstacle in the internal tank map; determining a first planned path of the tank cleaning robot based on the internal tank map with the position of the obstacle marked, the first planned path bypassing the position of the obstacle; controlling the tank cleaning robot to move according to the first planned path, so that the tank cleaning robot cleans the tank area passed by the first planned path.

[0102] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0103] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0104] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A control method for a tank cleaning robot, characterized in that: The method comprises: Acquire a tank internal map corresponding to the tank inner wall space to be cleaned by the tank cleaning robot; When an obstacle is detected in the inner wall space of the storage tank, marking the position of the obstacle in the internal map of the storage tank; Determining a first planned path of the tank cleaning robot based on an internal map of the tank on which the location of the obstacle is marked, wherein the first planned path bypasses the location of the obstacle; The tank cleaning robot is controlled to move according to the first planned path, so that the tank cleaning robot cleans the tank area passed by the first planned path.

2. The control method of the tank cleaning robot according to claim 1, characterized in that: The determining of a first planned path of the tank cleaning robot based on the internal map of the tank on which the position of the obstacle is marked includes: Determine a map unit set corresponding to the internal map of the storage tank, wherein each map unit in the map unit set has the same grid unit size; Determine a target map unit corresponding to a moving start position and a moving end position of the tank cleaning robot based on a map unit corresponding to a manhole opening position of the inner wall space of the tank in the map unit set; Determining an obstacle map unit in the map unit set corresponding to the position of the obstacle; A first planned path of the tank cleaning robot is determined according to the map unit set, wherein the first planned path passes through the target map unit and bypasses the obstacle map unit.

3. The control method of the tank cleaning robot according to claim 2, characterized in that: Determining a first planned path of the tank cleaning robot according to the map unit set includes: The map unit set is processed according to a preset longest path planning algorithm to determine a first planned path of the tank cleaning robot.

4. The control method of the tank cleaning robot according to claim 3, characterized in that: The processing of the map unit set according to a preset longest path planning algorithm to determine a first planned path of the tank cleaning robot includes: Determine a first candidate planning path set for the tank cleaning robot according to the map unit set, wherein each first candidate planning path in the first candidate planning path set passes through the target map unit and bypasses the obstacle map unit; Determine the number of map units respectively corresponding to each of the first candidate planning paths in the first candidate planning path set, where the number of map units is the number of map units passed by the first candidate planning path; Based on the first candidate planned path in the first candidate planned path set corresponding to the first candidate planned path with the largest number of map units, a first planned path for the tank cleaning robot is determined.

5. The control method of the tank cleaning robot according to claim 2, characterized in that: After determining a first planned path of the tank cleaning robot according to the map unit set, the method includes: Determine a legacy map unit set according to the map unit set and the first planned path, wherein the legacy map unit set is a collection of map units in the map unit set except for each map unit passed by the first planned path and the obstacle map unit; determining a second planned path passing through each legacy map unit in the set of legacy map units; The tank cleaning robot is controlled to move according to the second planned path, so that the tank cleaning robot cleans the tank area passed by the second planned path.

6. The control method of the tank cleaning robot according to claim 5, characterized in that: The determining a second planned path passing through at least one legacy map unit in the set of legacy map units comprises: The legacy map unit set is processed according to a preset shortest path planning algorithm to determine a second planned path for the tank cleaning robot.

7. The control method of the tank cleaning robot according to claim 6, characterized in that: The step of processing the legacy map unit set according to a preset shortest path planning algorithm to determine a second planned path for the tank cleaning robot includes: Determine a second candidate planning path set for the tank cleaning robot according to the legacy map unit set, each second candidate planning path in the second candidate planning path set passes through each legacy map unit in the legacy map unit set; For each of the second candidate planning paths in the second candidate planning path set, based on the number of second map units corresponding to the second candidate planning path and the number of legacy map units passed, determining a path cost value corresponding to the second candidate planning path; the number of legacy map units passed is the number of legacy map units passed by the second candidate planning path; the path cost value is positively correlated with the number of second map units, and the path cost value is negatively correlated with the number of legacy map units passed; An additional planned path is determined based on the second candidate planned path corresponding to the minimum path cost value in the second candidate planned path set.

8. The control method of the tank cleaning robot according to claim 2, characterized in that: The step of controlling the tank cleaning robot to move according to the first planned path so that the tank cleaning robot cleans the tank area corresponding to the first planned path includes: When it is detected that the real-time map unit where the tank cleaning robot is located when it moves is adjacent to the obstacle map unit, according to the map unit relative orientation of the real-time map unit relative to the obstacle map unit, controlling and adjusting the posture of the nozzle flushing module of the tank cleaning robot; The nozzle flushing module is started to flush the obstacle map unit.

9. The control method of the tank cleaning robot according to claim 1, characterized in that: The step of obtaining the internal map of the storage tank corresponding to the inner wall space of the storage tank to be cleaned by the storage tank cleaning robot includes: Based on the depth camera, the depth information corresponding to the inner wall space of the tank to be cleaned by the tank cleaning robot is collected; Based on the acquired depth information, a map of the interior of the tank is constructed.

10. A tank cleaning robot, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the control method of the tank cleaning robot according to any one of claims 1 to 9 is implemented.

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