A path planning method and system for an intelligent lawn mowing robot

Abstract

A path planning method and system for an intelligent lawn mowing robot, the method comprising: S1, generating a semantic map according to environmental information in a to-be-mowed area, the semantic map comprising boundary information, weather information, slope information, etc.; S2, positioning the robot in real time on the semantic map according to sensor information of the intelligent lawn mowing robot; S3, performing path planning on the semantic map using a preset algorithm to plan a safe and efficient movement route for the intelligent lawn mowing robot; S4, during the operation of the intelligent lawn mowing robot, repeating steps S2-S3 according to changes in the environment within a predetermined range until the robot returns to a charging station.

Description

Technical Field

[0001] The present invention belongs to the technical field of mobile robots, and in particular relates to a path planning method and system for an intelligent lawn mowing robot. Background Art

[0002] With the improvement of people's living standards, lawns have become a good place for urban residents to relax and have fun. People can camp, play golf, fly kites, etc. on the lawns. With the increase in the number and area of ​​urban lawns, the human resources consumption is getting bigger and bigger. A large number of public green spaces such as park lawns, football field lawns, and school lawns need to be maintained. Among them, lawn mowing is the most arduous task, and the lawn mowing robot designed to "free hands and reduce the burden on gardeners" was born. However, most lawn mowers on the market currently have problems such as low mowing efficiency, long path planning routes, and high missed mowing rates. Therefore, it is urgent to design a path planning method for intelligent lawn mowing robots so that the intelligent lawn mowing robots can efficiently mow lawns.

[0003] At present, the mainstream path planning methods of lawn mower robots include random, spiral and reciprocating. However, the random method has the disadvantages of missing a large area of ​​mowing and taking a long time; the spiral method has the disadvantage of many turns, which is also time-consuming; the reciprocating method will also miss a lot of mowing areas when turning, resulting in low mowing efficiency of the intelligent lawn mower robot. Not only that, the existing lawn mowers also have the problem of weak climbing ability. Therefore, in order to improve the mowing efficiency of the intelligent lawn mower robot, designing a path planning method and system for the intelligent lawn mower robot is an aspect worth considering at present. Summary of the invention

[0004] In order to solve the above problems, the present invention provides a path planning method and system for an intelligent lawn mowing robot, so as to realize autonomous and efficient operation of the intelligent lawn mowing robot, thereby freeing people's hands and reducing the burden on workers.

[0005] In order to achieve the above-mentioned purpose, in a first aspect, an embodiment of the present invention provides a path planning method for an intelligent lawn mowing robot, which is used to improve the mowing efficiency, coverage rate, and climbing ability of the intelligent lawn mowing robot and reduce the energy consumption of the intelligent lawn mowing robot during operation, and mainly includes the following steps:

[0006] S1. Generate a semantic map based on environmental information in the area to be mowed, wherein the semantic map includes boundary information, weather information, slope information, etc.;

[0007] S2. On the semantic map, positioning the robot in real time according to the sensor information of the intelligent lawn mowing robot;

[0008] S3, using a preset algorithm to perform path planning on the semantic map to plan a safe and efficient movement route for the intelligent mowing robot;

[0009] S4 During the operation of the intelligent lawn mowing robot, according to the changes in the environment within the predetermined range, steps S2-S3 are repeated until the robot returns to the charging station.

[0010] In a preferred embodiment, generating a semantic map based on environmental information in the area to be mowed includes the following steps:

[0011] S11, in the area to be mowed, controlling the intelligent mowing robot to move so that the intelligent mowing robot can completely collect real-time kinematic (RTK), inertial measurement unit (IMU), odometer data and environmental information;

[0012] S12, generating a semantic map according to the key data information obtained in S11, wherein the semantic map includes boundary information, weather information, slope information, etc.;

[0013] S13. Display the generated semantic map.

[0014] In a preferred embodiment, real-time positioning of the robot is performed according to the sensor information of the intelligent lawn mowing robot, which specifically includes the following steps:

[0015] S21, obtain key data such as RTK, IMU, odometer, etc. measured in S11;

[0016] S22, obtaining the semantic map generated by S12 according to the key data information in S11;

[0017] S23, establishing a coordinate system on the obtained semantic map, converting boundary information, slope information, odometer and other key data information into the coordinate system, and then obtaining the positioning information of the intelligent mowing robot according to the RTK and odometer and other key data information, and finally appropriately correcting the positioning information according to the adaptive Monte Carlo localization (AMCL) positioning information;

[0018] S24. Display the generated positioning information and semantic map.

[0019] In a preferred embodiment, the method of performing path planning on the semantic map using a preset algorithm to plan a safe and efficient movement route for the intelligent lawn mowing robot specifically includes the following steps:

[0020] S31, gridding the semantic map generated in S12 according to boundary information of obstacles and slopes;

[0021] Preferably, the specific steps of gridding the semantic map generated in S12 according to the boundary information of obstacles and slopes are:

[0022] S311, obtaining the boundary information, obstacle information, slope information obtained in S11 and the semantic map generated in S12;

[0023] S312, determining whether the slope of the area is greater than a threshold, if so, defining it as a dangerous slope area, if not, defining it as a gentle slope area, the threshold being determined by the developer;

[0024] S313, obtaining the dangerous slope area boundary information and the obstacle boundary information, and dividing the semantic map into a plurality of sub-areas according to the dangerous slope area boundary information and the obstacle boundary information, according to the first encounter with the obstacle boundary or the dangerous slope boundary and the last encounter with the obstacle boundary or the dangerous slope area boundary;

[0025] S314, according to the positioning result of S2, display the positioning information and position of the intelligent lawn mowing robot on the semantic map;

[0026] S315. According to the diameter of the cutting disk of the intelligent lawn mowing robot, the semantic map is divided into a plurality of squares whose side lengths are equal to the diameter of the cutting disk.

[0027] S32, determining whether the current area of ​​the intelligent lawn mower is in a flat area, if so, executing S33, if not, executing S34;

[0028] S33, the intelligent lawn mower robot starts from the charging pile or the current position, generates path No. 1 and path No. 3, both of which are straight paths, parallel and opposite in direction, and the intelligent lawn mower robot first runs along path No. 1. When the intelligent lawn mower robot walks to the boundary point along path No. 1, it starts to generate path No. 2, which is a transition path for connecting path No. 1 and path No. 3, and corresponding to this transition path is path No. 4 connecting path No. 3 and path No. 1. The lawn mower robot walks along path No. 1 to the boundary point, turns right at an angle of θ, walks along path No. 2 to the midpoint of the adjacent grid on the right, turns right at an angle of θ, and continues to run along path No. 3. When the intelligent lawn mower robot walks to the boundary point along path No. 3, it starts to generate path No. 4, which is a transition path for connecting path No. 3 and path No. 1, and corresponds to path No. 2. The intelligent lawn mowing robot walks along path 3 to the boundary point, turns left at an angle θ, walks along path 4 to the midpoint of the adjacent grid on the right, turns left at an angle θ, and continues to move along path 1;

[0029] S34, the intelligent lawn mower robot generates path No. 1 and path No. 3 from the current position. Both path No. 1 and path No. 3 are straight paths with opposite directions, and path No. 1 is in the direction of going uphill, and path No. 3 is in the direction of going downhill. The intelligent lawn mower robot first runs along path No. 1. When the intelligent lawn mower robot walks to the boundary point along path No. 1, it starts to generate path No. 2. Path No. 2 is a transition path for connecting path No. 1 and path No. 3. Corresponding to this transition path is path No. 4 connecting path No. 3 and path No. 1. The lawn mower robot walks along path No. 1 to the boundary point, turns right at an angle of θ, walks along path No. 2 to the midpoint of the adjacent grid on the right, turns right at an angle of θ, and continues to run along path No. 3. When the intelligent lawn mower robot walks to the boundary point along path No. 3, it starts to generate path No. 4. Path No. 4 is a transition path for connecting path No. 3 and path No. 1, and corresponds to path No. 2. The intelligent lawn mowing robot walks along path 3 to the boundary point, turns left at an angle θ, walks along path 4 to the midpoint of the right adjacent grid, turns right at an angle θ, and then runs along path 1.

[0030] Wherein, θ is the steering angle of the intelligent lawn mowing robot when the intelligent lawn mowing robot runs to the boundary point, and the calculation formula of θ is:

[0031]

[0032] Where θ∈(0°, 180°), d represents the horizontal distance from the current position of the smart lawn mower to the next column of feasible paths (0≤d≤r), r represents the diameter of the cutting disk, and q represents the distance from the current position of the smart lawn mower to the next column of feasible paths.

[0033] Assume that the boundary coordinates are (O m ,O n ), the center coordinate of the current intelligent lawn mowing robot is marked as (x i ,y j ), m, n are any allowed values, the diameter of the blade of the intelligent mowing robot, that is, the distance between the center points of two adjacent columns is r (the unit of the following distance is uniformly expressed in m), the distance from the current position of the intelligent mowing robot to the center of the next feasible grid is q, and the horizontal distance from the current position of the intelligent mowing robot to the center of the next feasible grid is d (0≤d≤r), x i +d represents the horizontal coordinate of the center of the next feasible grid column of the current position of the intelligent mowing robot, p is the safe distance from the boundary point coordinate to the feasible path, and the formula of the minimum safe distance is:

[0034]

[0035] Wherein, f is the sum of the length from the edge of the blade disc to the edge of the intelligent lawn mowing robot and a safety margin, and the safety margin is determined by engineers according to actual conditions.

[0036] When the safety distance p≥minp, the intelligent mowing robot is allowed to move along a feasible path, assuming that the linear equation of the pre-planned path is ax+by+c=0, where the pre-planned path can be calculated based on the current position coordinates (x i ,y j ) and the next column of pre-feasible grid centers (x i +d,y k ) is determined, the coordinates of the point closest to the pre-planned path of the boundary point are (O g ,O h ), then the calculation formula of the safety distance p is:

[0037]

[0038] Optionally, in this embodiment, the connection curve between adjacent grid cells is turned only once, but the distance between adjacent grid cells can also be divided into several small segments, and then this idea is continuously iterated on each small segment to obtain an approximate curve connection path.

[0039] S35, when the intelligent lawn mowing robot has traversed one of the plurality of sub-areas, a path No. 5 is generated from the end point of the sub-area to the starting point of the next area, and the path No. 5 satisfies the intelligent lawn mowing robot to reach the starting point of the next area quickly and energy-savingly;

[0040] S36. If a dynamic obstacle, such as a pedestrian, is detected during the operation of the intelligent lawn mower robot, and if the dynamic obstacle detected within a limited time during the operation of the intelligent lawn mower robot is moving normally, the intelligent lawn mower robot generates path No. 6, and path No. 6 includes deceleration or even stopping on the spot. If the dynamic obstacle detected within a limited time during the operation of the intelligent lawn mower robot is moving abnormally, or even the dynamic obstacle stops on the robot's operation path, the intelligent lawn mower robot generates path No. 7, and path No. 7 will bypass the obstacle from one side of the obstacle. The abnormal movement of the dynamic obstacle includes spinning in place and radial movement from the movement route of the intelligent lawn mower robot, etc.;

[0041] S37. After the intelligent lawn mowing robot completes the lawn mowing operation or detects unsuitable weather conditions for work (such as rain or snow), a path No. 8 is generated. The path No. 8 is for the intelligent lawn mowing robot to return from the last sub-area end point or the current position to the charging pile.

[0042] In a second aspect, the present invention provides a system for path planning of an intelligent lawn mowing robot, comprising a mapping module, a positioning module and a path planning module.

[0043] The mapping module is used to generate a semantic map required for the robot to operate autonomously based on the environmental information in the area to be mowed, wherein the semantic map includes boundary information, weather information, slope information, etc.;

[0044] The positioning module is used to locate the robot in real time on the semantic map according to the sensor information of the intelligent lawn mowing robot;

[0045] The path planning module is used to perform path planning on the semantic map using a preset algorithm to plan a safe and efficient movement route for the intelligent lawn mowing robot.

[0046] In a preferred embodiment, the mapping module specifically includes:

[0047] Information acquisition unit: used to control the movement of the intelligent mowing robot in the area to be mowed, so that the intelligent mowing robot can fully collect RTK, IMU, odometer data and environmental information;

[0048] A map generating unit: used to generate a semantic map according to the key data information obtained in S11, wherein the semantic map includes boundary information, weather information, slope information, etc.;

[0049] Display unit: used to display the collected sensor information and the generated semantic map.

[0050] In a preferred embodiment, the positioning module specifically includes:

[0051] Information reading unit: used to read key data such as RTK, IMU, odometer, etc. measured in S11 and the semantic map generated by S12;

[0052] Positioning unit: used to establish a coordinate system on the semantic map of the information reading unit, convert boundary information, slope information, odometer and other key data information into the coordinate system, and then obtain the positioning information of the intelligent mowing robot according to the RTK and odometer and other key data information, and finally perform appropriate correction on the positioning information according to the adaptive Monte Carlo positioning information;

[0053] Display unit: used to display positioning information and semantic maps.

[0054] In a preferred embodiment, the path planning module specifically includes:

[0055] A map gridding unit: used to grid the semantic map generated by S12 according to the boundary information of obstacles and slopes;

[0056] In a preferred embodiment, the map gridding unit specifically includes the following subunits:

[0057] The second judgment subunit is used to judge whether the slope of the area is greater than a threshold value according to the information of the information reading unit in the positioning module. If so, it is defined as a dangerous slope area; if not, it is defined as a gentle area. The threshold value is determined by the developer;

[0058] A map segmentation subunit is used to segment the semantic map into a plurality of sub-areas according to the dangerous slope area boundary information and the obstacle boundary information, and according to the first encounter with the obstacle boundary or the dangerous slope boundary and the last encounter with the obstacle boundary or the dangerous slope area boundary;

[0059] Gridding subunit: used for dividing the semantic map into a number of squares with a side length equal to the diameter of the cutting disk according to the diameter of the cutting disk of the intelligent lawn mowing robot.

[0060] The first judgment unit is used to judge whether the current area of ​​the intelligent lawn mower is in a flat area, if so, execute S33, if not, execute S34;

[0061] Path generation unit: used to perform path planning on the semantic map using a preset algorithm to plan a safe and efficient movement route for the intelligent mowing robot. For the specific process of path generation, please refer to S33-S37.

[0062] Calculation unit: used to calculate the steering angle θ of the intelligent robot when the intelligent mowing robot encounters a boundary point in the path generation unit.

[0063] The calculation formula of θ is:

[0064]

[0065] Where θ∈(0°, 180°), d represents the horizontal distance from the current position of the smart lawn mower to the next column of feasible paths (0≤d≤r), r represents the diameter of the cutting disk, and q represents the distance from the current position of the smart lawn mower to the next column of feasible paths.

[0066] Assume that the boundary coordinates are (O m ,O n ), the center coordinate of the current intelligent lawn mowing robot is marked as (x i ,y j), m, n are any allowed values, the diameter of the blade of the intelligent mowing robot, that is, the distance between the center points of two adjacent columns is r (the unit of the following distance is uniformly expressed in m), the distance from the current position of the intelligent mowing robot to the center of the next feasible grid is q, and the horizontal distance from the current position of the intelligent mowing robot to the center of the next feasible grid is d (0≤d≤r), x i +d represents the horizontal coordinate of the center of the next feasible grid column of the current position of the intelligent mowing robot, p is the safe distance from the boundary point coordinate to the feasible path, and the formula of the minimum safe distance is:

[0067]

[0068] Wherein, f is the sum of the length from the edge of the blade disc to the edge of the intelligent lawn mowing robot and a safety margin, and the safety margin is determined by engineers according to actual conditions.

[0069] When the safety distance p≥minp, the intelligent mowing robot is allowed to move along a feasible path, assuming that the linear equation of the pre-planned path is ax+by+c=0, where the pre-planned path can be calculated based on the current position coordinates (x i ,y j ) and the next column of pre-feasible grid centers (x i +d,y k ) is determined, the coordinates of the point closest to the pre-planned path are (O g ,O h ), then the calculation formula of the safety distance p is:

[0070]

[0071] Compared with the existing technology, the beneficial effects achieved by the present invention are: a path planning method and system for an intelligent lawn mowing robot is designed, and weather, boundary, slope and other information are integrated into a semantic map according to the sensor data of the intelligent lawn mowing robot. According to the slope and weather information, the intelligent lawn mowing robot can plan the robot's running route more quickly and effectively. Compared with the existing map generation method, this new semantic map can provide a basis for the better and safer operation of the intelligent lawn mowing robot. In addition, the existing lawn mowing robot path planning methods mainly include random, spiral and reciprocating types, but the random type has the disadvantages of missing a large area of ​​mowing and a long time; the spiral type has the disadvantage of many turns, which is also relatively time-consuming; the reciprocating type will also have more missed areas when turning, resulting in low mowing efficiency of the intelligent lawn mowing robot. Not only that, the existing lawn mowers also have the problem of weak climbing ability. However, the path planning method provided by the present invention can generate several sub-areas based on the slope information and boundary information. According to the characteristics of each area, for example, a path more suitable for the intelligent mowing robot to climb can be planned in the steep slope area, thereby improving the climbing ability of the intelligent mowing robot, and then planning a more energy-saving and efficient operation route in each sub-area. The path planning method provided by the present invention can also make indeterminate angle turns at the edge of an irregular mowing area according to the edge characteristics, so that the area missed by the intelligent mowing robot is smaller. In addition, the path planning method provided by the present invention can also plan a safe avoidance path according to the operating conditions of dynamic obstacles. BRIEF DESCRIPTION OF THE DRAWINGS

[0072] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0073] Attached Figure 1 This is a schematic diagram of a method for path planning of an intelligent lawn mowing robot provided by the first embodiment of the present invention;

[0074] Attached Figure 2 This is a flow chart of a mapping method provided by the present invention for Embodiment 1;

[0075] Attached Figure 3 This is a flow chart of a positioning method provided by the present invention for Embodiment 1;

[0076] Attached Figure 4 This is a flow chart of a path planning method provided by the present invention for Embodiment 1;

[0077] Attached Figure 5 A map gridding flow chart of a path planning method provided by the present invention in Embodiment 1;

[0078] Attached Figure 6A schematic diagram of a decomposition method for dividing a semantic map into several sub-areas provided by the first embodiment of the present invention;

[0079] Attached Figure 7 This is a schematic diagram of calculating the steering angle θ when generating a feasible path for an intelligent lawn mowing robot in a path planning method provided by the first embodiment of the present invention;

[0080] Attached Figure 8 A schematic diagram of a gridded semantic map and a result schematic diagram of a feasible path generated by an intelligent lawn mowing robot provided by the present invention in Embodiment 1;

[0081] Attached Fig. 9 This is a block diagram of a path planning system for an intelligent lawn mowing robot provided by the second embodiment of the present invention; DETAILED DESCRIPTION

[0082] In order to make the technical solution of the present invention clearer, the technical solution provided by the present invention will be described in detail in conjunction with specific embodiments, and the present invention will be further described in conjunction with the accompanying drawings. It is understood that the drawings and embodiments provided herein are only part of the present invention and are used to explain the present invention, rather than to limit the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0083] Embodiment 1

[0084] In order to improve the mowing efficiency, coverage rate, and climbing ability of the intelligent lawn mowing robot and reduce the energy consumption of the intelligent lawn mowing robot during operation, an embodiment of the present invention provides a path planning method for the intelligent lawn mowing robot, please refer to the attached Figure 1 , attached Figure 1 This is a schematic diagram of a method for path planning of an intelligent lawn mowing robot provided by the present invention in Embodiment 1, such as Figure 1 As shown, the method mainly includes the following steps:

[0085] S1. Generate a semantic map based on environmental information in the area to be mowed, wherein the semantic map includes boundary information, weather information, slope information, etc.;

[0086] S2. On the semantic map, positioning the robot in real time according to the sensor information of the intelligent lawn mowing robot;

[0087] S3, using a preset algorithm to perform path planning on the semantic map to plan a safe and efficient movement route for the intelligent mowing robot;

[0088] S4 During the operation of the intelligent lawn mowing robot, according to the changes in the environment within the predetermined range, steps S2-S3 are repeated until the robot returns to the charging station.

[0089] In a preferred embodiment, a semantic map is generated based on the environmental information of the area to be mowed. Figure 2 , attached Figure 2 This is a flowchart of a mapping method provided by the present invention for Embodiment 1, which specifically includes the following steps:

[0090] S11. In the area to be mowed, control the movement of the intelligent mowing robot so that the intelligent mowing robot can completely collect RTK, IMU, odometer data and environmental information;

[0091] S12, generating a semantic map according to the key data information obtained in S11, wherein the semantic map includes boundary information, weather information, slope information, etc.;

[0092] S13. Display the generated semantic map.

[0093] In a preferred embodiment, the robot is positioned in real time according to the sensor information of the intelligent lawn mowing robot. Figure 3 , attached Figure 3 The present invention provides a flow chart of a positioning method for Embodiment 1, which specifically includes the following steps:

[0094] S21, obtain key data such as RTK, IMU, odometer, etc. measured in S11;

[0095] S22, obtaining the semantic map generated by S12 according to the key data information in S11;

[0096] S23, establishing a coordinate system on the obtained semantic map, converting boundary information, slope information, odometer and other key data information into the coordinate system, and then obtaining the positioning information of the intelligent lawn mowing robot according to the RTK and odometer and other key data information, and finally appropriately correcting the positioning information according to the AMCL positioning information;

[0097] S24. Display the generated positioning information and semantic map.

[0098] In a preferred embodiment, the preset algorithm is used to perform path planning on the semantic map to plan a safe and efficient movement route for the intelligent lawn mowing robot. Figure 4 , attached Figure 4 The present invention provides a flow chart of a path planning method for Embodiment 1, which specifically includes the following steps:

[0099] S31, gridding the semantic map generated in S12 according to boundary information of obstacles and slopes;

[0100] S311, obtaining the boundary information, obstacle information, slope information obtained in S11 and the semantic map generated in S12;

[0101] S312, determining whether the slope of the area is greater than a threshold, if so, defining it as a dangerous slope area, if not, defining it as a gentle slope area, the threshold being determined by the developer;

[0102] S313, obtaining the dangerous slope area boundary information and the obstacle boundary information, and dividing the semantic map into a plurality of sub-areas according to the dangerous slope area boundary information and the obstacle boundary information, according to the first encounter with the obstacle boundary or the dangerous slope boundary and the last encounter with the obstacle boundary or the dangerous slope area boundary;

[0103] S314, according to the positioning result of S2, display the positioning information and position of the intelligent lawn mowing robot on the semantic map;

[0104] S315. According to the diameter of the cutting disk of the intelligent lawn mowing robot, the semantic map is divided into a plurality of squares whose side lengths are equal to the diameter of the cutting disk.

[0105] Please see attached Figure 5 and Annex 6, Figure 5 This is a map gridding flow chart of a path planning method provided by the present invention in Embodiment 1, Figure 6 This is a schematic diagram of a decomposition method for dividing a semantic map into several sub-areas provided in Embodiment 1 of the present invention.

[0106] S32, determining whether the current area of ​​the intelligent lawn mower is in a flat area, if so, executing S33, if not, executing S34;

[0107] S33, the intelligent lawn mower robot starts from the charging pile or the current position, generates path No. 1 and path No. 3, both of which are straight paths, parallel and opposite in direction, and the intelligent lawn mower robot first runs along path No. 1. When the intelligent lawn mower robot walks to the boundary point along path No. 1, it starts to generate path No. 2, which is a transition path for connecting path No. 1 and path No. 3, and corresponding to this transition path is path No. 4 connecting path No. 3 and path No. 1. The lawn mower robot walks along path No. 1 to the boundary point, turns right at an angle of θ, walks along path No. 2 to the midpoint of the adjacent grid on the right, turns right at an angle of θ, and continues to run along path No. 3. When the intelligent lawn mower robot walks to the boundary point along path No. 3, it starts to generate path No. 4, which is a transition path for connecting path No. 3 and path No. 1, and corresponds to path No. 2. The intelligent lawn mowing robot walks along path 3 to the boundary point, turns left at an angle θ, walks along path 4 to the midpoint of the adjacent grid on the right, turns left at an angle θ, and continues to move along path 1;

[0108] S34, the intelligent lawn mower robot generates path No. 1 and path No. 3 from the current position. Both path No. 1 and path No. 3 are straight paths with opposite directions, and path No. 1 is in the direction of going uphill, and path No. 3 is in the direction of going downhill. The intelligent lawn mower robot first runs along path No. 1. When the intelligent lawn mower robot walks to the boundary point along path No. 1, it starts to generate path No. 2. Path No. 2 is a transition path for connecting path No. 1 and path No. 3. Corresponding to this transition path is path No. 4 connecting path No. 3 and path No. 1. The lawn mower robot walks along path No. 1 to the boundary point, turns right at an angle of θ, walks along path No. 2 to the midpoint of the adjacent grid on the right, turns right at an angle of θ, and continues to run along path No. 3. When the intelligent lawn mower robot walks to the boundary point along path No. 3, it starts to generate path No. 4. Path No. 4 is a transition path for connecting path No. 3 and path No. 1, and corresponds to path No. 2. The intelligent lawn mowing robot walks along path 3 to the boundary point, turns left at an angle θ, walks along path 4 to the midpoint of the adjacent grid on the right, turns right at an angle θ, and then runs along path 1;

[0109] Wherein, θ is the steering angle of the intelligent lawn mowing robot when the intelligent lawn mowing robot runs to the boundary point. Please refer to the attached Figure 7 , attached Figure 7 This is a schematic diagram of calculating the steering angle θ when generating a feasible path for an intelligent lawn mowing robot in a path planning method provided by the present invention in Embodiment 1. The calculation formula of θ is:

[0110]

[0111] Where θ∈(0°, 180°), d represents the horizontal distance from the current position of the smart lawn mower to the next column of feasible paths (0≤d≤r), r represents the diameter of the cutting disk, and q represents the distance from the current position of the smart lawn mower to the next column of feasible paths.

[0112] Assume that the boundary coordinates are (O m ,O n ), the center coordinate of the current intelligent lawn mowing robot is marked as (x i ,y j ), m, n are any allowed values, the diameter of the blade of the intelligent mowing robot, that is, the distance between the center points of two adjacent columns is r (the unit of the following distance is uniformly expressed in m), the distance from the current position of the intelligent mowing robot to the center of the next feasible grid is q, and the horizontal distance from the current position of the intelligent mowing robot to the center of the next feasible grid is d (0≤d≤r), x i +d represents the horizontal coordinate of the center of the next feasible grid column of the current position of the intelligent mowing robot, p is the safe distance from the boundary point coordinate to the feasible path, and the formula of the minimum safe distance is:

[0113]

[0114] Wherein, f is the sum of the length from the edge of the blade disc to the edge of the intelligent lawn mowing robot and a safety margin, and the safety margin is determined by engineers according to actual conditions.

[0115] When the safety distance p≥minp, the intelligent mowing robot is allowed to move along a feasible path, assuming that the linear equation of the pre-planned path is ax+by+c=0, where the pre-planned path can be calculated based on the current position coordinates (x i ,y j ) and the next column of pre-feasible grid centers (x i +d,y k ) is determined, the coordinates of the point closest to the pre-planned path are (O g ,O h ), then the calculation formula of the safety distance p is:

[0116]

[0117] Optionally, in this embodiment, the connection curve between adjacent grid cells is turned only once, but the distance between adjacent grid cells can also be divided into several small segments, and then this idea is continuously iterated on each small segment to obtain an approximate curve connection path.

[0118] S35, when the intelligent lawn mowing robot has traversed one of the plurality of sub-areas, a path No. 5 is generated from the end point of the sub-area to the starting point of the next area, and the path No. 5 satisfies the intelligent lawn mowing robot to reach the starting point of the next area quickly and energy-savingly;

[0119] S36. If a dynamic obstacle, such as a pedestrian, is detected during the operation of the intelligent lawn mower robot, and if the dynamic obstacle detected within a limited time during the operation of the intelligent lawn mower robot is moving normally, the intelligent lawn mower robot generates path No. 6, and path No. 6 includes deceleration or even stopping on the spot. If the dynamic obstacle detected within a limited time during the operation of the intelligent lawn mower robot is moving abnormally, or even the dynamic obstacle stops on the robot's operation path, the intelligent lawn mower robot generates path No. 7, and path No. 7 will bypass the obstacle from one side. The abnormal movement of the dynamic obstacle includes spinning in place and moving radially from the movement route of the intelligent lawn mower robot, etc.;

[0120] S37. After the intelligent lawn mowing robot completes the lawn mowing operation or detects unsuitable weather conditions for work (such as rain or snow), a path No. 8 is generated. The path No. 8 is for the intelligent lawn mowing robot to return from the last sub-area end point or the current position to the charging pile.

[0121] Please see attached Figure 8 , attached Figure 8 The present invention provides a schematic diagram of a gridded semantic map and a schematic diagram of a feasible path generated by an intelligent lawn mowing robot in Example 1.

[0122] Embodiment 2

[0123] In order to realize the autonomous and efficient work of the intelligent lawn mowing robot and reduce the burden on workers, the present invention provides a path planning system for the intelligent lawn mowing robot, including a mapping module, a positioning module and a path planning module. Fig. 9 , attached Fig. 9 This is a system block diagram for path planning of an intelligent lawn mowing robot provided in Embodiment 2 of the present invention.

[0124] The mapping module is used to generate a semantic map required for the robot to operate autonomously based on the environmental information in the area to be mowed, wherein the semantic map includes boundary information, weather information, slope information, etc.;

[0125] The positioning module is used to locate the robot in real time on the semantic map according to the sensor information of the intelligent lawn mowing robot;

[0126] The path planning module is used to perform path planning on the semantic map using a preset algorithm to plan a safe and efficient movement route for the intelligent lawn mowing robot.

[0127] In a preferred embodiment, the mapping module specifically includes:

[0128] Information acquisition unit: used to control the movement of the intelligent mowing robot in the area to be mowed, so that the intelligent mowing robot can fully collect RTK, IMU, odometer data and environmental information;

[0129] A map generation unit: used to generate a semantic map according to the key data information obtained in S11, wherein the semantic map includes boundary information, weather information, slope information, etc.;

[0130] Display unit: used to display the collected sensor information and the generated semantic map.

[0131] In a preferred embodiment, the positioning module specifically includes:

[0132] Information reading unit: used to read key data such as RTK, IMU, odometer, etc. measured in S11 and the semantic map generated by S12;

[0133] Positioning unit: used to establish a coordinate system on the semantic map of the information reading unit, convert boundary information, slope information, odometer and other key data information into the coordinate system, and then obtain the positioning information of the intelligent mowing robot according to the RTK and odometer and other key data information, and finally perform appropriate correction on the positioning information according to the adaptive Monte Carlo positioning information;

[0134] Display unit: used to display positioning information and semantic maps.

[0135] In a preferred embodiment, the path planning module specifically includes:

[0136] A map gridding unit: used to grid the semantic map generated by S12 according to the boundary information of obstacles and slopes;

[0137] In a preferred embodiment, the map gridding unit specifically includes the following subunits:

[0138] The second judgment subunit is used to judge whether the slope of the area is greater than a threshold value according to the information of the information reading unit in the positioning module. If so, it is defined as a dangerous slope area; if not, it is defined as a gentle area. The threshold value is determined by the developer;

[0139] A map segmentation subunit is used to segment the semantic map into a plurality of sub-areas according to the dangerous slope area boundary information and the obstacle boundary information, and according to the first encounter with the obstacle boundary or the dangerous slope boundary and the last encounter with the obstacle boundary or the dangerous slope area boundary;

[0140] Gridding subunit: used for dividing the semantic map into a number of squares with a side length equal to the diameter of the cutting disk according to the diameter of the cutting disk of the intelligent lawn mowing robot.

[0141] The first judgment unit is used to judge whether the current area of ​​the intelligent lawn mower is in a flat area, if so, execute S33, if not, execute S34;

[0142] Path generation unit: used to perform path planning on the semantic map using a preset algorithm to plan a safe and efficient movement route for the intelligent mowing robot. For the specific process of path generation, please refer to S33-S37.

[0143] Calculation unit: used to calculate the steering angle θ of the intelligent robot when the intelligent mowing robot encounters a boundary point in the path generation unit.

[0144] The calculation formula of θ is:

[0145]

[0146] Where θ∈(0°, 180°), d represents the horizontal distance from the current position of the smart lawn mower to the next column of feasible paths (0≤d≤r), r represents the diameter of the cutting disk, and q represents the distance from the current position of the smart lawn mower to the next column of feasible paths.

[0147] Assume that the boundary coordinates are (O m ,O n ), the center coordinate of the current intelligent lawn mowing robot is marked as (x i ,y j ), m, n are any allowed values, the diameter of the blade of the intelligent mowing robot, that is, the distance between the center points of two adjacent columns is r (the unit of the following distance is uniformly expressed in m), the distance from the current position of the intelligent mowing robot to the center of the next feasible grid is q, and the horizontal distance from the current position of the intelligent mowing robot to the center of the next feasible grid is d (0≤d≤r), x i +d represents the horizontal coordinate of the center of the next feasible grid column of the current position of the intelligent mowing robot, p is the safe distance from the boundary point coordinate to the feasible path, and the formula of the minimum safe distance is:

[0148]

[0149] Wherein, f is the sum of the length from the edge of the blade disc to the edge of the intelligent lawn mowing robot and a safety margin, and the safety margin is determined by engineers according to actual conditions.

[0150] When the safety distance p≥minp, the intelligent mowing robot is allowed to move along a feasible path, assuming that the linear equation of the pre-planned path is ax+by+c=0, where the pre-planned path can be calculated based on the current position coordinates (x i ,y j ) and the next column of pre-feasible grid centers (x i +d,y k ) is determined, the coordinates of the point closest to the pre-planned path are (O g ,O h ), then the calculation formula of the safety distance p is:

[0151]

[0152] It should be noted that the serial numbers such as “No. 1” and “No. 2” appearing in the present invention are only for the convenience of distinction and are not used to limit the protection scope of the present invention.

[0153] It should be noted that in the above-mentioned embodiment of the path planning system, the various modules included are only divided according to functional logic and are not limited to the above-mentioned division, as long as the corresponding functions can be achieved; in addition, the specific names of the functional units are only for the convenience of distinguishing each other and are not used to limit the scope of protection of the present invention.

[0154] Finally, the above are only preferred embodiments of the present invention and the technical principles used. Those skilled in the art will understand that the present invention is not limited to the specific embodiments described herein, and that various obvious changes, readjustments and substitutions can be made by those skilled in the art without departing from the scope of protection of the present invention. Therefore, although the present invention is described in more detail through the above embodiments, the present invention is not limited to the above embodiments, and may include more other equivalent embodiments without departing from the concept of the present invention, and the scope of the present invention is determined by the scope of the appended claims.

Claims

1. A path planning method for an intelligent lawn mowing robot, comprising the following steps: S1. Generate a semantic map according to environmental information in the area to be mowed, wherein the semantic map includes boundary information, weather information and slope information; S2. On the semantic map, positioning the robot in real time according to the sensor information of the intelligent lawn mowing robot; S3, using a preset algorithm to perform path planning on the semantic map to plan a safe and efficient movement route for the intelligent mowing robot; S4 During the operation of the intelligent lawn mowing robot, according to the changes in the environment within the predetermined range, steps S2-S3 are repeated until the robot returns to the charging station; The step S1 of generating a semantic map according to the environmental information of the area to be mowed specifically includes the following steps: S11, in the area to be mowed, controlling the intelligent mowing robot to move so that the intelligent mowing robot can completely collect real-time kinematic (RTK), inertial measurement unit (IMU), odometer data and environmental information; S12, generating a semantic map according to the key data information obtained in S11, wherein the semantic map includes boundary information, weather information, and slope information; S13, displaying the generated semantic map; The step S3 of using a preset algorithm to perform path planning on the semantic map specifically includes: S31, gridding the semantic map generated in S12 according to boundary information of obstacles and slopes; S32, determining whether the current area of ​​the intelligent lawn mower is in a flat area, if so, executing S33, if not, executing S34; S33, the intelligent lawn mowing robot starts from the charging pile or the current position, generates path No. 1 and path No. 3, both of which are straight paths with parallel and opposite directions, and the intelligent lawn mowing robot first runs along path No. 1; when the intelligent lawn mowing robot reaches the boundary point along path No. 1, it starts to generate path No. 2, which is a transition path connecting path No. 1 and path 3, and corresponding to this transition path is path No. 4 connecting path No. 3 and path 1; the lawn mowing robot runs along path No. 1 Walk to the boundary point, turn right at an angle of θ, walk along the No. 2 path to the midpoint of the adjacent grid on the right, turn right at an angle of θ, and continue to run along the No. 3 path; when the intelligent lawn mowing robot walks to the boundary point along the No. 3 path, it starts to generate the No. 4 path, which is a transition path for connecting the No. 3 path and the No. 1 path, and corresponds to the No. 2 path; the intelligent lawn mowing robot walks along the No. 3 path to the boundary point, turns left at an angle of θ, walks along the No. 4 path to the midpoint of the adjacent grid on the right, turns left at an angle of θ, and continues to run along the No. 1 path; S34, the intelligent lawn mowing robot generates path No. 1 and path No. 3 from the current position, wherein both path No. 1 and path No. 3 are straight paths with opposite directions, and path No. 1 is along the uphill direction, and path No. 3 is along the downhill direction. The intelligent lawn mowing robot first runs along path No. 1; when the intelligent lawn mowing robot reaches the boundary point along path No. 1, it starts to generate path No. 2, which is a transition path connecting path No. 1 and path No. 3, and corresponding to this transition path is path No. 4 connecting path No. 3 and path 1 ; The lawn mowing robot walks along path No. 1 to the boundary point, turns right at an angle of θ, walks along path No. 2 to the midpoint of the adjacent grid on the right, turns right at an angle of θ, and continues to run along path No. 3; When the intelligent lawn mowing robot walks along path No. 3 to the boundary point, it starts to generate path No. 4, which is a transition path connecting path No. 3 and path No. 1, and corresponds to path No. 2; The intelligent lawn mowing robot walks along path No. 3 to the boundary point, turns left at an angle of θ, walks along path No. 4 to the midpoint of the adjacent grid on the right, turns right at an angle of θ, and runs along path No. 1; Wherein, θ is the steering angle of the intelligent lawn mowing robot when the intelligent lawn mowing robot runs to the boundary point, and the calculation formula of θ is: Where θ∈(0°, 180°), d represents the horizontal distance from the current position of the intelligent lawn mower to the next column of feasible paths, 0≤d≤r, r represents the diameter of the cutting disk, and q represents the distance from the current position of the intelligent lawn mower to the next column of feasible paths; Assume that the boundary coordinates are (O m , O n ), the center coordinate of the current intelligent lawn mowing robot is marked as (x i ,y j ), m, n are any allowed values, the diameter of the blade of the intelligent mowing robot, that is, the distance between the center points of two adjacent columns is r, the distance from the current position of the intelligent mowing robot to the next column of feasible paths is q, the horizontal distance from the current position of the intelligent mowing robot to the next column of feasible paths is d, x i +d represents the horizontal coordinate of the center of the next feasible grid column of the current position of the intelligent mowing robot, p is the safe distance from the boundary point coordinate to the feasible path, and the formula for the minimum safe distance is: Wherein, f is the sum of the length from the edge of the blade to the edge of the intelligent lawn mowing robot and the safety margin, and the safety margin is determined by the engineer according to the actual situation; When the safety distance p≥minp, the intelligent mowing robot is allowed to move along a feasible path, assuming that the linear equation of the pre-planned path is ax+by+c=0, where the pre-planned path can be calculated based on the current position coordinates (x i ,y j ) and the next column of pre-feasible grid centers (x i +d,y k ) is determined, the coordinates of the point closest to the pre-planned path are (O g , O h ), then the calculation formula of the safety distance p is: S35, when the intelligent lawn mowing robot has traversed one of the plurality of sub-areas, a path No. 5 is generated from the end point of the sub-area to the starting point of the next area, and the path No. 5 satisfies the intelligent lawn mowing robot to reach the starting point of the next area quickly and energy-savingly; S36. If a dynamic obstacle is detected during the operation of the intelligent lawn mower robot, and if the dynamic obstacle detected within a limited time during the operation of the intelligent lawn mower robot is in normal motion, the intelligent lawn mower robot generates a path No. 6, and the path No. 6 includes deceleration or even stopping on the spot; if the dynamic obstacle detected within a limited time during the operation of the intelligent lawn mower robot is in abnormal motion, or even the dynamic obstacle stops on the robot's operation path, the intelligent lawn mower robot generates a path No. 7, and the path No. 7 will bypass the obstacle from one side of the obstacle; the abnormal motion of the dynamic obstacle includes spinning in place and radial motion from the motion path of the intelligent lawn mower robot; S37. After the intelligent lawn mowing robot completes the lawn mowing operation or detects that the weather is not suitable for work, a path No. 8 is generated. The path No. 8 is for the intelligent lawn mowing robot to return from the last sub-area end point or the current position to the charging pile.

2. A path planning method for an intelligent lawn mowing robot as claimed in claim 1, characterized in that: The real-time positioning of the robot according to the sensor information of the intelligent lawn mowing robot described in step S2 specifically includes the following steps: S21, obtain the RTK, IMU, and odometer key data measured in S11; S22, obtaining the semantic map generated by S12 according to the key data information in S11; S23, establishing a coordinate system on the obtained semantic map, converting the boundary information, slope information and odometer key data information into the coordinate system, then obtaining the positioning information of the intelligent lawn mowing robot according to the RTK and odometer key data information, and finally appropriately correcting the positioning information according to the adaptive Monte Carlo localization (AMCL) positioning information; S24. Display the generated positioning information and semantic map.

3. A path planning method for an intelligent lawn mowing robot as claimed in claim 1, characterized in that: Step S31 specifically includes: S311, obtaining the boundary information, obstacle information, slope information obtained in S11 and the semantic map generated in S12; S312, determining whether the slope of the area is greater than a threshold, if so, defining it as a dangerous slope area, if not, defining it as a gentle slope area, the threshold being determined by the developer; S313, obtaining the dangerous slope area boundary information and the obstacle boundary information, and dividing the semantic map into a plurality of sub-areas according to the dangerous slope area boundary information and the obstacle boundary information, according to the first encounter with the obstacle boundary or the dangerous slope boundary and the last encounter with the obstacle boundary or the dangerous slope area boundary; S314, according to the positioning result of step S2, the positioning information and posture of the intelligent lawn mowing robot are displayed on the semantic map; S315. According to the diameter of the cutting disk of the intelligent lawn mowing robot, the semantic map is divided into a plurality of squares whose side lengths are equal to the diameter of the cutting disk.

4. A system for path planning of an intelligent lawn mowing robot that implements the path planning method for an intelligent lawn mowing robot as claimed in claim 1, characterized in that: Includes mapping module, positioning module and path planning module; The mapping module is used to generate a semantic map required for the robot to operate autonomously according to the environmental information in the area to be mowed, wherein the semantic map includes boundary information, weather information and slope information; The positioning module is used to locate the robot in real time based on the sensor information of the intelligent lawn mowing robot on the semantic map; The path planning module is used to perform path planning on the semantic map using a preset algorithm to plan a safe and efficient movement route for the intelligent mowing robot.

5. The path planning system for an intelligent lawn mowing robot according to claim 4, characterized in that: The mapping module specifically includes: Information acquisition unit: used to control the movement of the intelligent mowing robot in the area to be mowed, so that the intelligent mowing robot can fully collect RTK, IMU, odometer data and environmental information; A map generating unit: used to generate a semantic map according to the key data information obtained in S11, wherein the semantic map includes boundary information, weather information and slope information; Display unit: used to display the collected sensor information and the generated semantic map.

6. The path planning system for an intelligent lawn mowing robot according to claim 4, characterized in that: The positioning module specifically includes: Information reading unit: used to read the RTK, IMU, odometer key data measured in S11 and the semantic map generated by S12; Positioning unit: used to establish a coordinate system on the semantic map of the information reading unit, convert the boundary information, slope information and odometer key data information into the coordinate system, and then obtain the positioning information of the intelligent mowing robot according to the RTK and odometer key data information, and finally perform appropriate correction on the positioning information according to the adaptive Monte Carlo positioning information; Display unit: used to display positioning information and semantic maps.

7. The path planning system for an intelligent lawn mowing robot according to claim 4, characterized in that: The path planning module specifically includes: Map gridding unit: used to grid the semantic map generated by S12 according to the boundary information of obstacles and slopes; the map gridding unit specifically includes the following subunits: The second judgment subunit is used to judge whether the slope of the area is greater than a threshold value according to the information of the information reading unit in the positioning module. If so, it is defined as a dangerous slope area; if not, it is defined as a gentle area. The threshold value is determined by the developer; A map segmentation subunit is used to segment the semantic map into a plurality of sub-areas according to the dangerous slope area boundary information and the obstacle boundary information, and according to the first encounter with the obstacle boundary or the dangerous slope boundary and the last encounter with the obstacle boundary or the dangerous slope area boundary; A gridding subunit: used for dividing the semantic map into a number of squares with a side length equal to the diameter of the cutting disk according to the diameter of the cutting disk of the intelligent lawn mowing robot; The first judgment unit is used to judge whether the current area where the intelligent lawn mower is located is a flat area, if so, execute S33, if not, execute S34; Path generation unit: used for performing path planning on the semantic map using a preset algorithm to plan a movement route for the intelligent lawn mowing robot; Calculation unit: used to calculate the steering angle θ of the intelligent robot when the intelligent mowing robot encounters a boundary point in the path generation unit; The calculation formula of θ is: Where θ∈(0°, 180°), d represents the horizontal distance from the current position of the intelligent lawn mower to the next column of feasible paths 0≤d≤r, r represents the diameter of the cutting disk, and q represents the distance from the current position of the intelligent lawn mower to the next column of feasible paths; Assume that the boundary coordinates are (O m , O n ), the center coordinate of the current intelligent lawn mowing robot is marked as (x i ,y j ), m, n are any allowed values, the diameter of the blade of the intelligent mowing robot, that is, the distance between the center points of two adjacent columns is r, the distance from the current position of the intelligent mowing robot to the next column of feasible paths is q, the horizontal distance from the current position of the intelligent mowing robot to the next column of feasible paths is d, x i +d represents the horizontal coordinate of the center of the next feasible grid column of the current position of the intelligent mowing robot, p is the safe distance from the boundary point coordinate to the feasible path, and the formula of the minimum safe distance is: Wherein, f is the sum of the length from the edge of the blade to the edge of the intelligent lawn mowing robot and the safety margin, and the safety margin is determined by the engineer according to the actual situation; When the safety distance p≥minp, the intelligent mowing robot is allowed to move along a feasible path, assuming that the linear equation of the pre-planned path is ax+by+c=0, where the pre-planned path can be calculated based on the current position coordinates (x i ,y j ) and the next column of pre-feasible grid centers (x i +d,y k ) is determined, the coordinates of the point closest to the pre-planned path are (O g , O h ), then the calculation formula of the safety distance p is:

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