CN114397893A - Path planning method, robot cleaning method and related equipment - Google Patents
Path planning method, robot cleaning method and related equipment Download PDFInfo
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- 238000000034 method Methods 0.000 title claims abstract description 81
- 238000004140 cleaning Methods 0.000 title claims abstract description 80
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- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
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Abstract
The invention relates to the technical field of robots, and provides a path planning method, a robot cleaning method and related equipment, which are used for solving the problems that a path area navigation mode planned along a wall mode cannot pass through in the existing path planning scheme, so that the finally planned path is too long or the planning fails. The method comprises the following steps: acquiring a grid map of an area where the intelligent equipment is located, the current position of the intelligent equipment and a target area; detecting whether a narrow area exists in a grid map between the current position and the target area when the intelligent device is in a navigation mode; if so, adjusting obstacles in the narrow area based on the structural elements corresponding to the intelligent equipment, and updating the grid map based on the adjustment result; and planning a path from the current position to the target area by using a jumping point search algorithm according to the updated grid map, and outputting a navigation path.
Description
Technical Field
The invention relates to the technical field of robots, in particular to a path planning method, a robot cleaning method and related equipment.
Background
The sweeping robot can realize sweeping through two modes in the sweeping process, firstly, the construction of a global map is realized through a wall-following mode, a sweeping area and a sweeping path can be planned according to self pose after the map construction is completed, the area of the map is swept by switching between the wall-following mode and a point-to-point navigation mode, and after the sweeping is completely completed, a recharging point is detected and the recharging path is planned.
Currently, in the cleaning process, if the cleaning robot needs to be cleaned from a certain cleaning area to the next cleaning area or needs to return to the charging position after the cleaning is completed, the path planning and navigation are implemented by using a point-to-point navigation mode. However, in the navigation process, due to the laser precision, when the path passing through the wall-following mode is sensed by the wall-following sensor unit and sometimes switched to the point-to-point navigation mode, the navigation mode cannot pass through the path area under the wall-following mode, which causes problems of navigation failure, too long navigated path and the like.
Disclosure of Invention
The invention provides a path planning method, a robot cleaning method and related equipment, which are used for solving the problems that a path area navigation mode planned along a wall mode cannot pass through in the conventional path planning scheme, so that the finally planned path is too long or the planning fails.
A first aspect of the present invention provides a path planning method, including:
acquiring a grid map of an area where the intelligent equipment is located, the current position of the intelligent equipment and a target area;
when the intelligent device is in a navigation mode, detecting whether a narrow area exists in a grid map between the current position and the target area, wherein the narrow area is an area which can pass along a wall and cannot pass in the navigation mode;
if so, adjusting obstacles in the narrow area based on the structural elements corresponding to the intelligent equipment, and updating the grid map based on the adjustment result;
and planning a path from the current position to the target area by using a preset path construction algorithm according to the updated grid map, and outputting a navigation path.
In a possible implementation, before the detecting whether there is a narrow area in the grid map between the current position and the target area, the method further includes:
judging whether the intelligent equipment finishes cleaning along the wall or not;
if the cleaning is finished, acquiring a cleaning path for cleaning along the wall;
and extracting a path area with obstacles around the position of the grid point in the cleaning path to obtain a narrow area set.
In a possible implementation, before the adjusting obstacles in the narrow area based on the corresponding structural elements of the smart device and updating the grid map based on the adjustment result, the method includes:
acquiring the size parameters of the intelligent equipment, and constructing corresponding original structural elements based on the size parameters;
and performing angle removal processing on the original structural elements to obtain structural elements.
In one possible embodiment, the adjusting obstacles in the narrow area based on the corresponding structural elements of the smart device and updating the grid map based on the adjustment result includes:
extracting a map of the stenosis region;
traversing each grid point in the map of the narrow area by taking the structural element as an operator, and extracting the grid points with obstacles;
and performing obstacle elimination processing on the extracted grid points, and updating the grid map based on the elimination result.
In a possible implementation, the traversing each grid point in the map of the narrow region with the structural element as an operator to extract the grid point where the obstacle exists includes:
filling and marking grid points in the map of the narrow area based on a wall-following mode according to the central position of the structural element to obtain a marked map;
identifying whether an obstacle exists in the structural element range of the grid point corresponding to the mark based on each mark in the mark map;
if the obstacle exists, the corresponding grid points are subjected to passing labeling until all the grid points with the obstacle are output after the narrow area is traversed.
In a possible implementation manner, after traversing each grid point in the map of the narrow area with the structural element as an operator and extracting a grid point where an obstacle exists, the method further includes:
extracting obstacles on the grid points, and performing expansion treatment on the obstacles according to the structural elements to obtain expanded obstacles;
and replacing the original obstacles in the grid map based on the expansion obstacles to obtain a new grid map.
In a possible embodiment, the planning a path from the current location to the target area according to the updated grid map by using a preset path construction algorithm and outputting a navigation path includes:
determining a heading of the smart device based on the current location and the coordinates of the target area;
searching all blank grid points meeting jumping point conditions in the advancing direction, the horizontal component direction and the vertical component direction in the advancing direction by using a jumping point search algorithm with the current position as a starting point;
and constructing a path based on the current position, the blank grid points and the target area, and outputting a navigation path.
A second aspect of the present invention provides a robot cleaning method, including:
the robot finishes cleaning along the wall in a wall-following mode, an initial grid map is constructed, and a cleaning path for cleaning along the wall is obtained;
the robot is switched to a navigation mode, whether a narrow area exists in a grid map between the current position of the robot and a target area to be cleaned or not is detected, and the narrow area is an area which can pass under a wall mode and cannot pass under the navigation mode;
if so, carrying out obstacle clearing treatment on the narrow area, and constructing a navigation path from the current position to the target area by using a preset path construction algorithm based on the narrow area after obstacle clearing;
and navigating the robot to reach the target area for cleaning based on the navigation path.
A third aspect of the present invention provides a path planning apparatus, including:
the data acquisition module is used for acquiring a grid map of an area where the intelligent equipment is located, the current position of the intelligent equipment and a target area;
the first detection module is used for detecting whether a narrow area exists in a grid map between the current position and the target area when the intelligent device is in a navigation mode, wherein the narrow area is a passable area in a wall mode and a non-passable area in the navigation mode;
the area adjusting module is used for adjusting obstacles in the narrow area based on the structural elements corresponding to the intelligent equipment when the narrow area is detected to exist, and updating the grid map based on the adjusting result;
and the path planning module is used for planning a path from the current position to the target area by utilizing a preset path construction algorithm according to the updated grid map and outputting a navigation path.
A fourth aspect of the present invention provides a robot comprising:
the system comprises a wall following construction module, a data acquisition module and a data processing module, wherein the wall following construction module is used for completing wall following cleaning in a wall following mode, constructing an initial grid map and obtaining a cleaning path for the wall following cleaning;
the second detection module is used for switching to a navigation mode and detecting whether a narrow area exists in a grid map between the current position of the robot and a target area to be cleaned, wherein the narrow area is an accessible area in a wall-following mode and an inaccessible area in the navigation mode;
the navigation construction module is used for carrying out obstacle clearing processing on the narrow area when the narrow area is detected, and constructing a navigation path from the current position to the target area by using a preset path construction algorithm based on the narrow area after obstacle clearing;
and the cleaning module is used for navigating the robot to reach the target area to clean based on the navigation path.
A fifth aspect of the present invention provides an intelligent device, including: a memory and at least one processor, the memory having instructions stored therein; the at least one processor invokes the instructions in the memory to cause the smart device to perform the steps of the path planning method or the steps of the robot cleaning method described above.
A sixth aspect of the present invention provides a computer-readable storage medium having stored therein a computer program which, when run on a computer, causes the computer to perform the steps of the path planning method described above or the steps of the robot cleaning method described above.
According to the technical scheme provided by the invention, the narrow area between the current position and the target area in the map is eliminated by defining the narrow area under the wall-following mode and eliminating the obstacle of the narrow area based on the structural element constructed by the intelligent equipment, so that the intelligent equipment can pass through the path area under the wall-following mode under the navigation mode, the defect that the narrow area passes under the wall-following mode but the navigation mode cannot pass through the area is overcome, the compatible mode of navigation and wall following is realized, meanwhile, the planning of the path is well optimized, and the optimal path is ensured.
Drawings
Fig. 1 is a schematic diagram of a first embodiment of a path planning method according to an embodiment of the present invention;
fig. 2 is a schematic diagram of a second embodiment of a path planning method according to an embodiment of the present invention;
FIG. 3 is a diagram of a third embodiment of a path planning method according to an embodiment of the present invention;
FIG. 4 is a schematic design diagram of a structural element in an embodiment of the present invention;
FIG. 5 is a schematic illustration of the treatment of a stenosis region in an embodiment of the present invention;
FIG. 6 is a schematic view of the barrier inflation process in an embodiment of the present invention;
FIG. 7 is a schematic view of a walking path along a wall mode in an embodiment of the present invention;
FIG. 8 is a schematic diagram of a grid map of an obstacle inflation process in an embodiment of the present invention;
FIG. 9 is a schematic diagram of a navigation path planning in the navigation mode according to an embodiment of the present invention;
FIG. 10 is a schematic diagram of a JPS algorithm planning navigation path in an embodiment of the present invention;
FIG. 11 is a schematic diagram of an embodiment of a robot cleaning method according to an embodiment of the present invention;
FIG. 12 is a schematic structural diagram of a path planning apparatus according to an embodiment of the present invention;
fig. 13 is another schematic structural diagram of a path planning apparatus according to an embodiment of the present invention;
FIG. 14 is a schematic diagram of a robot according to an embodiment of the present invention;
fig. 15 is a schematic diagram of an embodiment of an intelligent device in the embodiment of the present invention.
Detailed Description
The embodiment of the invention provides a path planning method, a robot cleaning method and related equipment, which are used for solving the problem that a path is too long because a navigation mode in intelligent equipment and a path planned in a wall-following mode cannot be superposed.
The terms "first," "second," "third," "fourth," and the like in the description and in the claims, as well as in the drawings, if any, are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It will be appreciated that the data so used may be interchanged under appropriate circumstances such that the embodiments described herein may be practiced otherwise than as specifically illustrated or described herein. Furthermore, the terms "comprises," "comprising," or "having," and any variations thereof, are intended to cover non-exclusive inclusions, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
It is understood that the present invention can be applied to a smart device, and the smart device can be a mobile robot by way of example and not limitation, and the mobile robot is exemplified in the present application. The mobile robot can be any one of a sweeping robot, a sweeping and mopping integrated robot, a floor cleaning robot or a floor washing robot and the like. The navigation type of the sweeping robot applied by the invention is not limited, and the sweeping robot can be a pure inertial navigation sweeping machine or other sweeping machines adopting navigation equipment. The invention can be applied to the control method and the equipment of the advancing direction with low requirement on the positioning precision. By way of example, and not limitation, the present invention is described in terms of a sweeping robot among mobile robots.
For convenience of understanding, a specific flow of the embodiment of the present invention is described below, and referring to fig. 1, fig. 1 is a schematic diagram of a path planning method according to an embodiment of the present invention, where an embodiment of the path planning method according to the embodiment of the present invention includes:
s101, acquiring a grid map of an area where the intelligent device is located, the current position of the intelligent device and a target area.
In the step, the grid map is obtained through a perception module of the robot, and the opposite module is composed of different sensor units, such as a laser radar sensor unit, a collision sensor unit and a wall sensor unit.
When the robot starts to work, the robot is switched to a wall-following mode, the robot is controlled to clean in the wall-following mode according to the wall-following mode of the wall-following sensor unit, other environment information in the area where the robot is located is collected through the laser radar sensor unit and the collision sensor unit, a maxilla map is built, cleaning zones, obstacle information and the like are included on the grid map, and meanwhile the control module performs corresponding path planning control.
S102, detecting whether a narrow area exists in a grid map between the current position and the target area or not when the intelligent device is in a navigation mode.
In this embodiment, the narrow area is an area that can pass through in the wall-following mode and cannot pass through in the navigation mode; the narrow area processing in the path planning method is provided when the robot is in a navigation mode, and in the navigation mode, due to laser precision, when a path passing along the wall mode is sensed and generated by the wall sensor unit and is switched to a point-to-point navigation mode sometimes, the navigation mode cannot pass through the path areas along the wall mode, and the path areas are defined as narrow areas.
In this embodiment, the determining whether there is a stenosis region includes:
judging whether the current position is positioned beside a wall or at the edge position in a grid map;
if yes, planning a first path based on the wall-following mode and planning a second path based on the navigation mode respectively;
intercepting a path area which is different from a second path in the first path, and judging whether the intelligent equipment can pass through the path area in a navigation mode;
if the current position cannot pass through the target area, determining that a narrow area exists between the current position and the target area;
and if the current position of the intelligent device can pass through the target area, determining that no narrow area exists between the current position and the target area, and navigating the intelligent device to the target area by using the first path.
In practical application, a direction vector can be calculated through the current position and the target area, and whether a narrow area exists in the grid map in the direction of the direction vector is searched by taking the current position as a starting point; the search is specifically based on the marking of a previously marked narrow area in the grid map.
And S103, if the obstacle exists, adjusting the obstacle in the narrow area based on the structural element corresponding to the intelligent device, and updating the grid map based on the adjustment result.
In the step, the structural element is constructed based on the actual size of the intelligent device, and the construction mode is mainly edging processing, namely redundant grid points in the grid image corresponding to the intelligent device are deleted to obtain a grid image which is approximately circular.
Based on the structural element, the obstacle defined as the narrow area is adjusted, where the adjustment includes deleting a local part, moving, and the like.
In this embodiment, the narrow area in the map range from the current position to the target area may be selected to be adjusted, or all the narrow areas in the entire grid map may be adjusted.
In this embodiment, the structural element is used as an operator to traverse the narrow region, and after determining that the structural element does not traverse to a grid point, it is determined whether the structural element has an obstacle in the range of the structural element after the grid point, and if so, the obstacle at the position in the narrow region is eliminated, so that the structural element can pass through the obstacle. And replacing the corresponding narrow area in the grid map based on the adjusted narrow area to obtain a new grid map.
And S104, planning a path from the current position to the target area by using a preset path construction algorithm according to the updated grid map, and outputting a navigation path.
In the step, the path construction algorithm may be an a-star algorithm or a jump point search algorithm (JPS), preferably, the present application is implemented by using a JPS algorithm, the JPS is a path planning algorithm for constructing a path by searching for a jump point of a parent node or forcing a neighbor point, and the number of times of calculation of a navigation point can be reduced by planning the path through the algorithm.
In this embodiment, the current position is used as a start point, the start point is used as a parent node, a blank grid point meeting the requirement of the jumping point is searched in the direction of a direction vector from the current position to a target area to be used as the jumping point of the parent node, a path from the parent node to the jumping point is connected, then the jumping point is used as the parent node, the jumping point or the forced neighbor point is searched based on the same method, when the direct jumping point or the forced neighbor point is used as a point or an end point in the target area, the search is stopped, and the path from the current position to the target area is constructed based on all the searched points, so that the blank grid point in the narrow area can be also taken into consideration, and the method is not limited to the wall-following mode or the navigation mode.
In the embodiment of the invention, the narrow area is set based on the along-the-wall mode, and when the path is planned in the navigation mode, the obstacle in the narrow area is adjusted to meet the path planning requirement in the navigation mode, so that the compatibility of the along-the-wall mode and the navigation mode is realized, the path planning length can be optimal on the basis, and the problem of overlong path caused by excessive obstacle avoidance is avoided.
Referring to fig. 2, another embodiment of the path planning method according to the embodiment of the present invention includes path planning in a wall-following mode and path planning in a navigation mode, and is mainly applied to a sweeping robot, where the sweeping robot includes a control module, a sensing module, and a motion module, where the sensing module is composed of, for example, a laser radar sensor unit, a collision sensor unit, and a wall-following sensor unit, and the path planning method includes:
s201, the sweeping robot is electrified to start sweeping.
S202, constructing an initial map along the wall mode.
Specifically, the control module controls the sweeping robot to work in a wall-following mode, then the robot is made to move along a wall or a boundary through the motion module, map data in the moving process and surrounding map data are collected through the sensing module, and a map is drawn based on the collected map data through a standard coordinate system to obtain an initial map.
S203, constructing a cleaning path along the wall mode, and acquiring raster data through a sensing module based on the cleaning path.
And S204, constructing a global grid map based on the acquired grid data.
Specifically, after the grid map is constructed, whether the sweeping robot completes the task of cleaning along the wall is judged, if yes, the next step is skipped, and if not, the cleaning along the wall is continued, grid data are collected, and the grid map is updated based on the grid data.
In this embodiment, a narrow area is defined based on the constructed grid map, specifically:
judging whether the intelligent equipment finishes cleaning along the wall or not;
if the cleaning is finished, acquiring a cleaning path for cleaning along the wall;
and extracting a path area with obstacles around the position of the grid point in the cleaning path to obtain a narrow area set. Further, marking in the grid map based on each narrow area in the narrow area set is further included.
And S205, switching to a navigation mode to clean or recharge.
S206, detecting whether a narrow area exists in the grid map between the current position and the target area.
Specifically, in the navigation mode, whether a narrow area exists around the route is judged based on a navigation route planned in advance, if yes, the next step is skipped, otherwise, the navigation route is output.
And S207, if the map exists, extracting the map of the narrow area.
And S208, traversing each grid point in the map of the narrow area by taking the structural element as an operator, and extracting the grid point with the obstacle.
In this embodiment, the structural element is a raster image of the sweeping robot, and the structural element is specifically constructed in the following manner:
acquiring the size parameters of the intelligent equipment, and constructing corresponding original structural elements based on the size parameters;
and performing angle removal processing on the original structural elements to obtain structural elements.
As shown in fig. 4, a matrix of the sweeping robot is constructed based on the size parameters to obtain an original structural element, as shown in fig. 4(a), and then the original structural element is chamfered in a chamfering manner, so that the length of a connecting diagonal line is √ 50 √ 7, thereby reducing the amount of calculation, and the designed structural element is as shown in fig. 4 (b).
S209, obstacle elimination processing is performed on the extracted grid points, and the grid map is updated based on the elimination result.
In this embodiment, specifically, each grid point in the map of the narrow area is filled and marked based on the wall-following mode at the center position of the structural element, so as to obtain a marked map;
identifying whether an obstacle exists in the structural element range of the grid point corresponding to the mark based on each mark in the mark map;
if the obstacle exists, the corresponding grid points are subjected to passing labeling until all the grid points with the obstacle are output after the narrow area is traversed.
And finally, carrying out obstacle elimination processing on all grid points to obtain a new grid map.
For example, the map is traversed based on the structural elements in fig. 4(b) in the following manner. Taking a narrow area as an example for explanation, fig. 5(a) is the narrow area defined based on the wall-following mode, and the center position of the structural element, that is, the coordinate position of the filling mark along the wall mode is taken as a reference in the traversal process, if an obstacle exists in the structural element in the coordinate range, the structural element is traversed as a pass, and the filling is "0", so as to eliminate the obstacle, and obtain the map shown in fig. 5(b), that is, the narrow area after the obstacle is eliminated.
S210, expanding the obstacles in the grid map and updating the grid map.
In this step, the expansion treatment is specifically performed on the obstacle in the narrow area after the obstacle is removed, specifically:
extracting obstacles on the grid points in a narrow area, and performing expansion treatment on the obstacles according to the structural elements to obtain expanded obstacles;
and replacing the original obstacles in the grid map based on the expansion obstacles to obtain a new grid map.
And S211, planning a path from the current position to a target area by using a preset path construction algorithm according to the updated grid map, and outputting a navigation path.
Specifically, the advancing direction of the intelligent device is determined based on the current position and the coordinates of the target area;
searching all blank grid points meeting jumping point conditions in the advancing direction, the horizontal component direction and the vertical component direction in the advancing direction by using a jumping point search algorithm with the current position as a starting point;
and constructing a path based on the current position, the blank grid points and the target area, and outputting a navigation path.
In practical application, the obstacles in the map processed in (b) of fig. 5 are traversed according to similar structural elements, the central element of the structural element is replaced with an obstacle mark "1", and if "1" exists in the structural element in the traversing process, the central element of the structural element is set as the obstacle, so that the expansion of the obstacles in the map is completed. Fig. 6(a) is a path through a narrow area along a wall-mode robot, fig. 6(b) is a map expanded through a structural element, and "J" is a navigation track generated through a JPS navigation algorithm.
Furthermore, the sweeping robot is regarded as a mass point, the size of the mass point is a map grid, and path planning is performed on the map processed in the step (b) of fig. 6. The path planning uses a JPS path navigation algorithm with a small calculation amount, and a specific algorithm implementation flow is shown in fig. 3, and specifically includes the following steps:
s301, acquiring a grid map;
s302, judging whether a wall-following mode exists or not;
s303, if so, acquiring a narrow area;
s304, eliminating obstacles in the narrow area according to a wall-following mode;
s305, expanding the obstacle by the radius of the robot, and performing navigation planning on the expanded grid map;
s306, judging whether the navigation is successful;
s307, if the navigation is successful, generating a navigation path by using a JPS algorithm;
s308, if the operation is unsuccessful, determining that the narrow area is not available;
and S309, ending.
The above method will be described in detail in the following actual scenarios. In actual scene testing, the size of the map collected was 78 × 89, where the lidar resolution was 0.05. The map is a map loaded by sensing the surrounding environment through a laser radar carried by the sweeping robot, and meanwhile, the sweeping process in a wall-following mode is completed, wherein a black area is an obstacle, and an X line represents a wall-following path in the sweeping process of the robot, as shown in fig. 7.
At the time of cleaning, the robot needs to navigate from one point along the wall to another cleaning point and through the narrow area shown in the map. First, the map is cleared of obstacles along the wall path according to the robot, as shown in fig. 8(a), and then the obstacles are expanded according to the radius of the robot, as shown in fig. 8 (b).
Finally, the robot navigates from one point to another during the course of the wall while following the optimal path through the narrow area. As shown in fig. 9, 9(a) is a route for which no narrow area navigation is performed, and 9(b) is a route generated for which narrow area navigation is performed. The black point is a starting point of the robot, the star point is a target point of the robot, the solid line track is a motion track of the navigation of the robot, and a narrow area in the middle section can pass through the solid line track.
The following illustrates a route finding process of planning a navigation route by the JPS algorithm. As shown in fig. 10, in the 5 × 5 grid, the diagonal filled portions represent the blocking regions, S is the starting point, and E is the ending point. To find the shortest path from S to E, JPS first initializes to add the starting point S to the openset. Taking out the point S with the minimum F value from the openset, deleting the point S from the openset, adding closed set, wherein the current direction of S is null, searching for a jump point in eight directions, wherein only three directions of lower, right and lower right (relative to the absolute reference system of the screen: upper, lower, left and right, relative to the reference system of the player: front, back, left and right, herein for the convenience of description, the absolute reference system and the relative reference system are switched) are available from S, but searching downwards until D meets a boundary, searching rightwards until F meets a block, and therefore no jump point is found, then searching for a jump point in the lower right direction, at G point, parent (G) is S according to the definition of the jump point, praent (G) until S is diagonal movement, and G can reach a jump point I through vertical direction movement (downward movement), therefore G is the jump point, and G is added to the openset. And (3) taking a point G with the minimum F value from the openset, deleting the point G from the openset, adding closed set, searching for a jump point in three directions of right (horizontal component of the current direction), lower (vertical component of the current direction) and right-lower (current direction) because the current direction of G is a diagonal direction (direction from S to G), only walking downwards from G in the figure, searching for the jump point downwards, finding a jump point I according to the jump point definition, and adding I into the openset. Taking the point I with the minimum F value from the openset, deleting the point I from the openset, adding closed set, searching jumping points along the left, the left front and the front because the current direction of the I is a straight line direction (the direction from G to I), the left rear of the I is not available at the point I, and the left front is available at the point I, but the left front and the front meet the boundary, only searching jumping point Q (defined according to the jumping points) to the left, and adding Q into the openset. And (3) taking a point Q with the minimum F value from the openset, deleting the point Q from the openset, adding closed set, searching for a jumping point along the left, the left front and the front because the current direction of the Q is a straight line direction, the left rear of the Q cannot be moved and the left front and the front can be moved, but meeting a boundary at the left front and the front, and only searching for a jumping point E (defined according to the jumping point) to the left, so that adding E into the openset. The point E with the smallest F value is taken from openset, and since E is the destination point, the way finding ends and the path is S, G, I, Q, E. Note that the case of walking from H to K is not considered herein, because the diagonal has a block, if H to K can be directly reached, the path is S, G, H, K, M, P, E, and the calculation method of the jumping point is modified, but if H to K can be directly reached in the game, the block on the right side of H is crossed.
In the embodiment of the invention, through the visualization of the method and the actual operation module, the defect that the navigation mode can not pass through a narrow area under the wall-following mode is overcome, so that the compatible mode of navigation and wall-following is realized, and meanwhile, the planning of the path is well optimized, and the optimal path is ensured.
Referring to fig. 11, a robot cleaning method provided in an embodiment of the present application includes the following steps:
s401, the robot completes the cleaning along the wall in the mode of along the wall, an initial grid map is built, and a cleaning path for cleaning along the wall is obtained.
In this step, the robot detects a wall or a boundary by a laser sensor or a wall sensor unit while in a wall-following mode, and controls the robot to scan map data along the wall or the boundary and construct a wall-following cleaning path for cleaning based on a start point and a destination, and in the cleaning process, environment data outside the wall or the boundary is acquired by the laser sensor, an initial grid map is constructed based on the environment data and the wall-following cleaning path, and a narrow area is defined based on the wall-following cleaning path, the narrow area being a path area that is passable along the wall mode and impassable in a navigation mode in the wall-following cleaning path, and the path area is defined as a narrow area.
S402, the robot is switched to a navigation mode, and whether a narrow area exists in a grid map between the current position of the robot and a target area to be cleaned or not is detected.
In this embodiment, the narrow area is an area that can pass through in the wall-following mode and cannot pass through in the navigation mode; specifically, a structural element is constructed based on the floor space of the robot, wherein the structural element is constructed by acquiring the size parameter of the intelligent device and constructing a corresponding original structural element based on the size parameter; and performing angle removal processing on the original structural elements to obtain structural elements.
And traversing each grid point in the narrow area under the wall mode in the grid map based on the structural element, judging the position of the grid point, judging whether an obstacle exists in the range of the structural element, and if so, determining that the narrow area exists.
And S403, if the target area exists, carrying out obstacle clearing treatment on the narrow area, and constructing a navigation path from the current position to the target area by using a preset path construction algorithm based on the narrow area after obstacle clearing.
Specifically, by extracting a map of the narrow area; traversing each grid point in the map of the narrow area by taking the structural element as an operator, and extracting the grid points with obstacles; extracting obstacles on the grid points, and performing expansion treatment on the obstacles according to the structural elements to obtain expanded obstacles; and replacing the original obstacles in the grid map based on the expansion obstacles to obtain a new grid map.
Further, determining the advancing direction of the intelligent device based on the current position and the coordinates of the target area;
searching all blank grid points meeting jumping point conditions in the advancing direction, the horizontal component direction and the vertical component direction in the advancing direction by using a jumping point search algorithm with the current position as a starting point;
and constructing a path based on the current position, the blank grid points and the target area, and outputting a navigation path.
And S404, navigating the robot to reach the target area based on the navigation path to clean.
In this step, when the robot is controlled to move to the target area based on the navigation path, the method further includes controlling the robot to detect whether a new obstacle exists after the robot moves to each navigation point in the navigation path, if so, selecting the nearest navigation point by using an a-x algorithm to reconstruct the navigation path, and then entering the target area based on the new navigation path to clean the target area.
In this embodiment, by defining a narrow area in the wall-following mode, the obstacle in the map between the current position and the target area is eliminated based on the structural element constructed by the intelligent device, so that the intelligent device can also pass through a path area in the wall-following mode in the navigation mode, thereby making up for the defect that the narrow area passes through in the wall-following mode but the navigation mode cannot pass through the area, and realizing a compatible mode of navigation and wall-following.
With reference to fig. 12, the path planning method in the embodiment of the present invention is described above, and a path building apparatus in the embodiment of the present invention is described below, where an embodiment of the path building apparatus in the embodiment of the present invention includes:
a data obtaining module 901, configured to obtain a grid map of an area where the intelligent device is located, a current position of the intelligent device, and a target area;
a first detecting module 902, configured to detect whether a narrow area exists in a grid map between the current location and the target area when the smart device is in a navigation mode;
an area adjusting module 903, configured to, when a narrow area is detected to exist, adjust an obstacle in the narrow area based on a structural element corresponding to the smart device, and update the grid map based on an adjustment result;
and a path planning module 904, configured to plan a path from the current position to the target area according to the updated grid map by using a skip point search algorithm, and output a navigation path.
The function implementation of each module in the path construction apparatus corresponds to each step in the embodiment of the path planning method, and the function and implementation process thereof are not described in detail herein.
In the embodiment of the invention, the narrow area between the current position and the target area in the map is eliminated by defining the narrow area under the wall-following mode and eliminating the obstacle of the narrow area based on the structural element constructed by the intelligent equipment, so that the intelligent equipment can pass through the path area under the wall-following mode under the navigation mode, the defect that the narrow area passes under the wall-following mode but the navigation mode cannot pass through the area is overcome, the compatible mode of navigation and wall-following is realized, meanwhile, the planning of the path is well optimized, and the optimal path is ensured.
Referring to fig. 13, another embodiment of the path building apparatus according to the embodiment of the present invention includes:
a data obtaining module 901, configured to obtain a grid map of an area where the intelligent device is located, a current position of the intelligent device, and a target area;
a judging module 905, configured to judge whether the intelligent device has completed cleaning along a wall;
a path obtaining module 906, configured to obtain a cleaning path for cleaning along the wall when it is determined that the cleaning along the wall is completed;
a defining module 907 for extracting a path area where an obstacle exists around a position where a grid point is located in the cleaning path to obtain a narrow area set;
a first detecting module 902, configured to detect whether a narrow area exists in a grid map between the current location and the target area when the smart device is in a navigation mode;
an area adjusting module 903, configured to, when a narrow area is detected to exist, adjust an obstacle in the narrow area based on a structural element corresponding to the smart device, and update the grid map based on an adjustment result;
and a path planning module 904, configured to plan a path from the current position to the target area according to the updated grid map by using a skip point search algorithm, and output a navigation path.
Optionally, the robot further comprises: a building block 908 for
Acquiring the size parameters of the intelligent equipment, and constructing corresponding original structural elements based on the size parameters;
and performing angle removal processing on the original structural elements to obtain structural elements.
Optionally, the area adjusting module 903 includes:
an extracting unit 9031, configured to extract a map of the narrow area;
a traversal unit 9032, configured to traverse each grid point in the map of the narrow area by using the structural element as an operator, and extract a grid point where an obstacle exists;
an elimination unit 9033 is configured to perform obstacle elimination processing on the extracted grid points, and update the grid map based on a result of elimination.
Optionally, the traversal unit 9032 is specifically configured to:
filling and marking grid points in the map of the narrow area based on a wall-following mode according to the central position of the structural element to obtain a marked map;
identifying whether an obstacle exists in the structural element range of the grid point corresponding to the mark based on each mark in the mark map;
if the obstacle exists, the corresponding grid points are subjected to passing labeling until all the grid points with the obstacle are output after the narrow area is traversed.
Optionally, the traversal unit 9032 may further be specifically configured to:
extracting obstacles on the grid points, and performing expansion treatment on the obstacles according to the structural elements to obtain expanded obstacles;
and replacing the original obstacles in the grid map based on the expansion obstacles to obtain a new grid map.
Optionally, the path planning module 904 includes;
a direction determining unit 9041, configured to determine, based on the current position and the coordinates of the target area, a heading direction of the smart device;
a searching unit 9042, configured to search, with the current position as a starting point, all blank grid points that meet a skip point condition in the forward direction, and in a horizontal component direction and a vertical component direction in the forward direction, respectively, by using a skip point search algorithm;
a planning unit 9043, configured to construct a path based on the current position, the blank grid point, and the target region, and output a navigation path.
In the embodiment of the invention, the way of the narrow area is defined, the barrier in the narrow area is adjusted, so that the path in the wall-following mode can be used under the navigation mode, the defect that the narrow area passes through in the wall-following mode but the navigation mode cannot pass through the narrow area is overcome, the compatible mode of navigation and wall-following is realized, meanwhile, the planning of the path is well optimized, and the optimal path is ensured.
In the above description of the robot cleaning method in the embodiment of the present invention, referring to fig. 14, the road robot in the embodiment of the present invention is described below, and an embodiment of the robot in the embodiment of the present invention includes:
an along-wall construction module 1401, configured to complete the along-wall cleaning in the along-wall mode, construct an initial grid map, and obtain a cleaning path for the along-wall cleaning;
a second detecting module 1402, configured to switch to a navigation mode, and detect whether a narrow area exists in a grid map between a current position of the robot and a target area to be cleaned, where the narrow area is a passable area in a wall-following mode and a passable area in the navigation mode;
a navigation building module 1403, configured to perform obstacle clearing processing on a narrow area when the narrow area is detected, and build a navigation path from the current position to the target area by using a preset path building algorithm based on the narrow area after obstacle clearing;
a cleaning module 1404 configured to navigate the robot to the target area for cleaning based on the navigation path.
The function implementation of each module in the robot corresponds to each step in the robot cleaning method embodiment, and the robot is implemented by using the path planning method when implementing the construction of the navigation path, and the function and implementation process are not described in detail herein.
In the embodiment of the invention, the narrow area between the current position and the target area in the map is eliminated by defining the narrow area under the wall-following mode and eliminating the obstacle of the narrow area based on the structural element constructed by the intelligent equipment, so that the intelligent equipment can pass through the path area under the wall-following mode under the navigation mode, the defect that the narrow area passes under the wall-following mode but the navigation mode cannot pass through the area is overcome, the compatible mode of navigation and wall-following is realized, meanwhile, the planning of the path is well optimized, and the optimal path is ensured.
Fig. 12 to 14 describe the path building apparatus and the robot in the embodiment of the present invention in detail from the perspective of the modular functional entity, and the intelligent device based on the unit decomposition in the embodiment of the present invention is described in detail from the perspective of the hardware processing.
Fig. 15 is a schematic structural diagram of an intelligent device 1100 according to an embodiment of the present invention, where the intelligent device 1100 may have a relatively large difference due to different configurations or performances, and may include one or more processors (CPUs) 1110 (e.g., one or more processors) and a memory 1120, and one or more storage media 1130 (e.g., one or more mass storage devices) for storing applications 1133 or data 1132. Memory 1120 and storage medium 1130 may be, among other things, transient or persistent storage. The program stored on the storage medium 1130 may include one or more modules (not shown), each of which may include a sequence of instructions for operating on the smart device 1100. Still further, the processor 1110 may be configured to communicate with the storage medium 1130 to execute a series of instruction operations in the storage medium 1130 on the smart device 1100.
The smart based device 1100 may also include one or more power supplies 1140, one or more wired or wireless network interfaces 1150, one or more input-output interfaces 1160, and/or one or more operating systems 1131, such as Windows Server, Mac OS X, Unix, Linux, FreeBSD, etc. Those skilled in the art will appreciate that the smart device architecture illustrated in FIG. 13 does not constitute a limitation of smart devices and may include more or fewer components than those illustrated, or some components may be combined, or a different arrangement of components.
The present invention also provides a computer-readable storage medium, which may be a non-volatile computer-readable storage medium, and which may also be a volatile computer-readable storage medium, in which a computer program is stored, which, when run on a computer, causes the computer to perform the steps of the path planning method or the robot cleaning method.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes several computer programs to enable a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a removable hard disk, a read-only memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.
The above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (12)
1. A path planning method is characterized by comprising the following steps:
acquiring a grid map of an area where the intelligent equipment is located, the current position of the intelligent equipment and a target area;
when the intelligent device is in a navigation mode, detecting whether a narrow area exists in a grid map between the current position and the target area, wherein the narrow area is an area which can pass along a wall and cannot pass in the navigation mode;
if so, adjusting obstacles in the narrow area based on the structural elements corresponding to the intelligent equipment, and updating the grid map based on the adjustment result;
and planning a path from the current position to the target area by using a preset path construction algorithm according to the updated grid map, and outputting a navigation path.
2. The path planning method according to claim 1, further comprising, before the detecting whether there is a narrow area in the grid map between the current position to the target area:
judging whether the intelligent equipment finishes cleaning along the wall or not;
if the cleaning is finished, acquiring a cleaning path for cleaning along the wall;
and extracting a path area with obstacles around the position of the grid point in the cleaning path to obtain a narrow area set.
3. The path planning method according to claim 1, wherein before the adjusting obstacles in the narrow area based on the corresponding structural elements of the smart device and updating the grid map based on the adjustment result, the method comprises:
acquiring the size parameters of the intelligent equipment, and constructing corresponding original structural elements based on the size parameters;
and performing angle removal processing on the original structural elements to obtain structural elements.
4. The path planning method according to claim 3, wherein the adjusting obstacles in the narrow area based on the corresponding structural elements of the smart device and updating the grid map based on the adjustment result comprises:
extracting a map of the stenosis region;
traversing each grid point in the map of the narrow area by taking the structural element as an operator, and extracting the grid points with obstacles;
and performing obstacle elimination processing on the extracted grid points, and updating the grid map based on the elimination result.
5. The path planning method according to claim 4, wherein traversing each grid point in the map of the narrow area with the structural element as an operator to extract grid points with obstacles comprises:
filling and marking grid points in the map of the narrow area based on a wall-following mode according to the central position of the structural element to obtain a marked map;
identifying whether an obstacle exists in the structural element range of the grid point corresponding to the mark based on each mark in the mark map;
if the obstacle exists, the corresponding grid points are subjected to passing labeling until all the grid points with the obstacle are output after the narrow area is traversed.
6. The path planning method according to claim 4, wherein after traversing each grid point in the map of the narrow area with the structural element as an operator and extracting the grid point where the obstacle exists, the method further comprises:
extracting obstacles on the grid points, and performing expansion treatment on the obstacles according to the structural elements to obtain expanded obstacles;
and replacing the original obstacles in the grid map based on the expansion obstacles to obtain a new grid map.
7. The path planning method according to any one of claims 1 to 6, wherein the planning a path from the current position to the target area according to the updated grid map by using a preset path construction algorithm and outputting a navigation path comprises:
determining a heading of the smart device based on the current location and the coordinates of the target area;
searching all blank grid points meeting jumping point conditions in the advancing direction, the horizontal component direction and the vertical component direction in the advancing direction by using a jumping point search algorithm with the current position as a starting point;
and constructing a path based on the current position, the blank grid points and the target area, and outputting a navigation path.
8. A robot cleaning method, characterized by comprising:
the robot finishes cleaning along the wall in a wall-following mode, an initial grid map is constructed, and a cleaning path for cleaning along the wall is obtained;
the robot is switched to a navigation mode, whether a narrow area exists in a grid map between the current position of the robot and a target area to be cleaned or not is detected, wherein the narrow area is an area which can pass under a wall mode and cannot pass under the navigation mode;
if so, carrying out obstacle clearing treatment on the narrow area, and constructing a navigation path from the current position to the target area by using a preset path construction algorithm based on the narrow area after obstacle clearing;
and navigating the robot to reach the target area for cleaning based on the navigation path.
9. A path planning apparatus, characterized in that the path planning apparatus comprises:
the data acquisition module is used for acquiring a grid map of an area where the intelligent equipment is located, the current position of the intelligent equipment and a target area;
the first detection module is used for detecting whether a narrow area exists in a grid map between the current position and the target area when the intelligent device is in a navigation mode, wherein the narrow area is a passable area in a wall mode and a non-passable area in the navigation mode;
the area adjusting module is used for adjusting obstacles in the narrow area based on the structural elements corresponding to the intelligent equipment when the narrow area is detected to exist, and updating the grid map based on the adjusting result;
and the path planning module is used for planning a path from the current position to the target area by utilizing a preset path construction algorithm according to the updated grid map and outputting a navigation path.
10. A robot, characterized in that the robot comprises:
the system comprises a wall following construction module, a data acquisition module and a data processing module, wherein the wall following construction module is used for completing wall following cleaning in a wall following mode, constructing an initial grid map and obtaining a cleaning path for the wall following cleaning;
the second detection module is used for switching to a navigation mode and detecting whether a narrow area exists in a grid map between the current position of the robot and a target area to be cleaned, wherein the narrow area is a passable area in a wall-following mode and a passable area in the navigation mode;
the navigation construction module is used for carrying out obstacle clearing processing on the narrow area when the narrow area is detected, and constructing a navigation path from the current position to the target area by using a preset path construction algorithm based on the narrow area after obstacle clearing;
and the cleaning module is used for navigating the robot to reach the target area to clean based on the navigation path.
11. A smart device, the smart device comprising: a memory and at least one processor, the memory having stored therein a computer program;
the at least one processor invokes the computer program in the memory to cause the smart device to perform the steps of the path planning method according to any of claims 1-7 or the steps of the robot cleaning method according to claim 8.
12. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the path planning method according to any one of claims 1-7 or the steps of the robot cleaning method according to claim 8.
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| CN112180924A (en) * | 2020-09-28 | 2021-01-05 | 珠海市一微半导体有限公司 | Movement control method for navigating to dense obstacles |
| CN112180931A (en) * | 2020-09-30 | 2021-01-05 | 小狗电器互联网科技（北京）股份有限公司 | Sweeping path planning method and device of sweeper and readable storage medium |
| CN113693493A (en) * | 2021-02-10 | 2021-11-26 | 北京石头世纪科技股份有限公司 | Regional map drawing method and device, medium and electronic equipment |
| CN113156970A (en) * | 2021-05-08 | 2021-07-23 | 珠海市一微半导体有限公司 | Path fusion planning method for passing area, robot and chip |
| CN113219975A (en) * | 2021-05-08 | 2021-08-06 | 珠海市一微半导体有限公司 | Route optimization method, route planning method, chip and robot |
| CN113791617A (en) * | 2021-08-31 | 2021-12-14 | 金华市浙工大创新联合研究院 | Global path planning method based on physical dimension of fire-fighting robot |
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| CN117472067A (en) * | 2023-12-27 | 2024-01-30 | 江苏中科重德智能科技有限公司 | Robot narrow channel passing method and system based on multilayer grid map |
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