Method and system for controlling forbidden area by unmanned tower crane

Abstract

The invention discloses a method and a system for controlling a forbidden area by an unmanned tower crane. The method comprises the following steps of: defining a plurality of forbidden sub-areas according to a protection range of a plurality of forbidden characteristics and positions of the plurality of forbidden characteristics; the final forbidden area is defined based on the area optimization of the plurality of forbidden sub-areas, so that the integrity and accuracy of the final forbidden area are ensured. Further, an optimized moving track is defined according to the avoiding path, the safe moving range of the tower crane part and the moving track; the tower crane part detects a plurality of environment characteristics in real time in the moving process, and the dynamic avoiding logic of the tower crane part is defined according to the environment characteristics, the corresponding distances and the influence grades of the environment characteristics, so that the tower crane part can avoid the final forbidden area and the environment characteristics in the moving process in real time in the moving process. The moving stability of the tower crane part is ensured, and the final forbidden area and the overall consideration of the environmental characteristics in the moving process are compatible.

Description

Technical Field

[0001] The present invention relates to the technical field of unmanned tower cranes, and in particular to a control method and system for an unmanned tower crane to control a restricted area. Background Art

[0002] With the development of science and technology, unmanned tower cranes are applied to construction sites. The tower crane part is the main part of the unmanned tower crane and moves above the construction site. The tower crane part needs to move to the target position. In the existing technology, the tower crane part moves along a preset path, and the restricted area is manually set by the operator. The influence of the restricted features cannot be fully considered, which affects the accuracy of the restricted area. At the same time, the tower crane part cannot avoid the restricted area and the environmental features during the movement. Summary of the invention

[0003] The purpose of the present invention is to overcome the shortcomings of the prior art. The present invention provides a control method and system for a restricted area of ​​an unmanned tower crane, which defines the moving trajectory of the tower crane part according to the current position and target position of the tower crane part of the unmanned tower crane; triggers path detection based on the moving trajectory of the tower crane part, and collects multiple restricted features in the path detection; defines multiple restricted sub-areas according to the protection ranges of the multiple restricted features and the locations of the multiple restricted features; defines a final restricted area based on the regional optimization of the multiple restricted sub-areas, thereby controlling the multiple restricted sub-areas in multiple dimensions, and further defines the final restricted area through regional optimization of the multiple restricted sub-areas and further processing of the multiple restricted sub-areas, thereby ensuring the integrity and accuracy of the final restricted area.

[0004] Furthermore, a corresponding avoidance path is defined according to the final restricted area and the moving area corresponding to the moving trajectory, and an optimized moving trajectory is defined according to the avoidance path, the safe activity range of the tower crane part and the moving trajectory; the tower crane part detects multiple environmental features in real time during the movement, and the dynamic avoidance logic of the tower crane part is defined according to the multiple environmental features, the corresponding distances and the impact levels of the environmental features, so that the tower crane part can avoid the final restricted area and the environmental features during the movement in real time during the movement, thereby ensuring the movement stability of the tower crane part and being compatible with the overall consideration of the final restricted area and the environmental features during the movement.

[0005] The embodiment of the present invention provides a method for controlling a restricted area by an unmanned tower crane, which is applied to a scenario in which an unmanned tower crane controls a restricted area; The control method of the unmanned tower crane for the restricted area includes: Defining a moving trajectory of the tower crane part according to the current position and the target position of the tower crane part of the unmanned tower crane; Trigger path detection based on the moving trajectory of the tower crane, and collect multiple prohibited entry features during path detection; Defining multiple no-entry sub-areas according to the protection ranges of multiple no-entry features and the locations of multiple no-entry features; Defining a final keep-out area based on area optimization of multiple keep-out sub-areas; Define the corresponding avoidance path according to the final forbidden area and the moving area corresponding to the moving trajectory, and define the optimized moving trajectory according to the avoidance path, the safe activity range of the tower crane part and the moving trajectory; The tower crane detects multiple environmental features in real time during movement, and defines the dynamic avoidance logic of the tower crane according to the multiple environmental features, the corresponding distances and the impact levels of the environmental features.

[0006] Optionally, defining the moving trajectory of the tower crane part according to the current position and the target position of the tower crane part of the unmanned tower crane includes: Locate the crane part of the unmanned tower crane and collect the current position of the crane part of the unmanned tower crane; Associate the current position and target position of the crane part; defining a plurality of primary movement paths according to the current position and the target position of the tower crane part; Based on the multiple primary movement paths, the activity dimensions of the tower crane part and the preset movement time, multiple advanced movement paths are defined. At this time, the multiple advanced movement paths are further screened by the multiple primary movement paths; The moving trajectory of the tower crane part is defined based on the comparison of multiple high-level moving paths. At this time, each high-level moving path is divided into multiple moving spaces, and multiple optimal moving spaces are defined based on the comparison of the corresponding moving spaces. The moving trajectory of the tower crane part is defined based on the multiple optimal moving spaces.

[0007] Optionally, the moving trajectory of the tower crane part is used to trigger the path detection, and multiple forbidden-entry features are collected during the path detection, including: Freeze the moving trajectory of the tower crane part; Divide multiple path detection points based on the moving trajectory of the tower crane part, and perform path detection based on the multiple path monitoring points; Collecting corresponding obstacle data based on path detection at each path monitoring point; Defining obstacle types according to multiple obstacle data, and defining obstacle levels according to the obstacle types and corresponding volumes; A plurality of obstacles are collected, and a no-entry feature is defined according to a distance between two adjacent obstacles, an obstacle level of two adjacent obstacles, and a matching coefficient of two adjacent obstacles, so as to collect a plurality of no-entry features.

[0008] Optionally, the step of defining a plurality of no-entry sub-areas according to the protection ranges of the plurality of no-entry features and the locations of the plurality of no-entry features includes: Freeze each prohibited feature; Define corresponding forbidden levels based on the volume of each forbidden feature and the type corresponding to each forbidden feature; Associate each forbidden feature with the forbidden level table, and define the corresponding protection range according to the forbidden level corresponding to each forbidden feature and the position between two adjacent forbidden features; Collect the locations of multiple forbidden features; Associating the protection ranges of multiple no-entry features and the locations of multiple no-entry features; A plurality of no-entry sub-areas are defined based on protection ranges of the plurality of no-entry features, locations of the plurality of no-entry features, and no-entry levels corresponding to the plurality of no-entry features.

[0009] Optionally, the defining a final no-entry area based on area optimization of multiple no-entry sub-areas includes: Freeze multiple forbidden sub-areas; A plurality of forbidden spaces are formed according to the division of each forbidden sub-area; Define corresponding spatial images based on each forbidden space; Defining a corresponding object type according to the recognition of the spatial image, and defining a corresponding optimization coefficient according to the object type and the type matching table; In each forbidden sub-area, multiple optimization coefficients are collected, an optimization level is constructed based on the multiple optimization coefficients, and corresponding optimization is triggered according to the optimization level and the corresponding forbidden sub-area, and multiple optimized forbidden sub-areas are output, and the final forbidden area is defined based on the multiple optimized forbidden sub-areas.

[0010] Optionally, defining a corresponding avoidance path according to the final forbidden area and the moving area corresponding to the moving trajectory, and defining an optimized moving trajectory according to the avoidance path, the safe activity range of the tower crane part and the moving trajectory, includes: Freeze the final forbidden area; Associate the final forbidden area and movement trajectory; Define multiple avoidance spaces according to the final forbidden area and the moving area corresponding to the moving trajectory; Corresponding avoidance paths are defined according to multiple avoidance spaces and the activity dimensions of the tower crane.

[0011] Optionally, the method further includes defining an avoidance path according to the final forbidden area and the moving area corresponding to the moving trajectory, and defining an optimized moving trajectory according to the avoidance path, the safe activity range of the tower crane part and the moving trajectory: In each avoidance space, collect the safe range of movement of the tower crane; Associate avoidance paths, safe range of movement of crane parts, and movement trajectories; The optimized movement trajectory is defined based on the avoidance path, the safe activity range of the tower crane part and the movement trajectory.

[0012] Optionally, the tower crane part detects multiple environmental features in real time during the movement, and defines the dynamic avoidance logic of the tower crane part according to the multiple environmental features, the corresponding distances and the impact levels of the environmental features, including: The tower crane part moves along the optimized moving trajectory; The tower crane performs real-time detection during movement and collects multiple surrounding environment data; Defining multiple environmental features according to multiple surrounding environment data and characteristic logic of the tower crane part; The positions of the multiple environmental features are marked, and corresponding distances are defined according to the positions of the multiple environmental features.

[0013] Optionally, the tower crane part detects multiple environmental features in real time during the movement, and defines the dynamic avoidance logic of the tower crane part according to the multiple environmental features, the corresponding distances and the impact levels of the environmental features, further comprising: Associating a plurality of environmental features and corresponding distances, and defining an environmental impact area based on the plurality of environmental features and the corresponding distances; Freeze multiple environmental features and mark the impact levels of the corresponding environmental features; The environmental impact area and the impact level of the environmental characteristics are associated, and the dynamic avoidance logic of the tower crane part is defined based on the environmental impact area and the impact level of the environmental characteristics.

[0014] In addition, an embodiment of the present invention further provides a control system for a restricted area by an unmanned tower crane, and the control system for a restricted area by an unmanned tower crane includes: A moving trajectory module is used to define the moving trajectory of the tower crane part according to the current position and target position of the tower crane part of the unmanned tower crane; The forbidden entry feature module is used to trigger the path detection based on the moving trajectory of the tower crane part and collect multiple forbidden entry features in the path detection; A no-entry sub-area module, used to define multiple no-entry sub-areas according to the protection ranges of multiple no-entry features and the locations of multiple no-entry features; A keep-out area module, used to define a final keep-out area based on area optimization of multiple keep-out sub-areas; An optimization module is used to define a corresponding avoidance path according to the final forbidden area and the moving area corresponding to the moving trajectory, and to define an optimized moving trajectory according to the avoidance path, the safe activity range of the tower crane part and the moving trajectory; The dynamic avoidance module is used to detect multiple environmental features in real time during the movement of the tower crane, and define the dynamic avoidance logic of the tower crane according to the multiple environmental features, the corresponding distances and the impact levels of the environmental features.

[0015] In an embodiment of the present invention, through the method in the embodiment of the present invention, the moving trajectory of the tower crane part of the unmanned tower crane is defined according to the current position and the target position of the tower crane part; path detection is triggered based on the moving trajectory of the tower crane part, and multiple forbidden features are collected in the path detection; multiple forbidden sub-areas are defined according to the protection ranges of the multiple forbidden features and the locations of the multiple forbidden features; the final forbidden area is defined based on the regional optimization of the multiple forbidden sub-areas, so as to control the multiple forbidden sub-areas in multiple dimensions, and the final forbidden area is further defined through the regional optimization of the multiple forbidden sub-areas and further processing of the multiple forbidden sub-areas, thereby ensuring the integrity and accuracy of the final forbidden area.

[0016] Furthermore, a corresponding avoidance path is defined according to the final restricted area and the moving area corresponding to the moving trajectory, and an optimized moving trajectory is defined according to the avoidance path, the safe activity range of the tower crane part and the moving trajectory; the tower crane part detects multiple environmental features in real time during the movement, and the dynamic avoidance logic of the tower crane part is defined according to the multiple environmental features, the corresponding distances and the impact levels of the environmental features, so that the tower crane part can avoid the final restricted area and the environmental features during the movement in real time during the movement, thereby ensuring the movement stability of the tower crane part and being compatible with the overall consideration of the final restricted area and the environmental features during the movement. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0018] Figure 1 It is a flow chart of a method for controlling a restricted area by an unmanned tower crane in an embodiment of the present invention; Figure 2 is a flow chart of S11 in the method for controlling a restricted area by an unmanned tower crane in an embodiment of the present invention; Figure 3is a flow chart of S12 in the method for controlling a restricted area by an unmanned tower crane in an embodiment of the present invention; Figure 4 1 is a flow chart of S13 in the method for controlling a restricted area by an unmanned tower crane in an embodiment of the present invention; Figure 5 is a flow chart of S14 in the method for controlling a restricted area by an unmanned tower crane in an embodiment of the present invention; Figure 6 is a flow chart of S15 in the method for controlling a restricted area by an unmanned tower crane in an embodiment of the present invention; Figure 7 is a flow chart of S16 in the method for controlling a restricted area by an unmanned tower crane in an embodiment of the present invention; Figure 8 It is a schematic diagram of the structure of the control system of the restricted area of ​​the unmanned tower crane in the embodiment of the present invention; Fig. 9 The figure is a hardware diagram of an electronic device according to an exemplary embodiment. DETAILED DESCRIPTION

[0019] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0020] See also Figures 1 to 9 , a control method for an unmanned tower crane to a restricted area, applied to a control scenario of an unmanned tower crane to a restricted area; the control method for an unmanned tower crane to a restricted area includes: Step S11: defining a moving trajectory of the tower crane part according to the current position of the tower crane part of the unmanned tower crane and the target position; Step S12: triggering path detection based on the moving trajectory of the tower crane part, and collecting multiple prohibited entry features in the path detection; Step S13: defining a plurality of no-entry sub-areas according to the protection ranges of the plurality of no-entry features and the locations of the plurality of no-entry features; Step S14: defining a final no-entry area based on area optimization of multiple no-entry sub-areas; Step S15: defining a corresponding avoidance path according to the final forbidden area and the moving area corresponding to the moving trajectory, and defining an optimized moving trajectory according to the avoidance path, the safe activity range of the tower crane part and the moving trajectory; Step S16: The tower crane detects multiple environmental features in real time during the movement, and defines the dynamic avoidance logic of the tower crane according to the multiple environmental features, the corresponding distances and the impact levels of the environmental features.

[0021] In an embodiment of the present invention, through the method in the embodiment of the present invention, the moving trajectory of the tower crane part of the unmanned tower crane is defined according to the current position and the target position of the tower crane part; path detection is triggered based on the moving trajectory of the tower crane part, and multiple forbidden features are collected in the path detection; multiple forbidden sub-areas are defined according to the protection ranges of the multiple forbidden features and the locations of the multiple forbidden features; the final forbidden area is defined based on the regional optimization of the multiple forbidden sub-areas, so as to control the multiple forbidden sub-areas in multiple dimensions, and the final forbidden area is further defined through the regional optimization of the multiple forbidden sub-areas and further processing of the multiple forbidden sub-areas, thereby ensuring the integrity and accuracy of the final forbidden area.

[0022] Furthermore, a corresponding avoidance path is defined according to the final restricted area and the moving area corresponding to the moving trajectory, and an optimized moving trajectory is defined according to the avoidance path, the safe activity range of the tower crane part and the moving trajectory; the tower crane part detects multiple environmental features in real time during the movement, and the dynamic avoidance logic of the tower crane part is defined according to the multiple environmental features, the corresponding distances and the impact levels of the environmental features, so that the tower crane part can avoid the final restricted area and the environmental features during the movement in real time during the movement, thereby ensuring the movement stability of the tower crane part and being compatible with the overall consideration of the final restricted area and the environmental features during the movement.

[0023] refer to Figure 2 , in step S11, a moving trajectory of the tower crane part is defined according to the current position of the tower crane part of the unmanned tower crane and the target position; In the specific implementation process of the present invention, the specific steps may be: S111: locating a tower crane part of the unmanned tower crane, and collecting a current position of the tower crane part of the unmanned tower crane; S112: Associating the current position and the target position of the tower crane; S113: defining a plurality of primary moving paths according to the current position and the target position of the tower crane; S114: defining a plurality of advanced movement paths based on the plurality of primary movement paths, the activity dimensions of the tower crane part, and the preset movement time, wherein the plurality of advanced movement paths are further screened from the plurality of primary movement paths; S115: The moving trajectory of the tower crane part is defined based on the comparison of multiple high-level moving paths. At this time, each high-level moving path is divided into multiple moving spaces, and multiple optimal moving spaces are defined based on the comparison of the corresponding moving spaces. The moving trajectory of the tower crane part is defined based on the multiple optimal moving spaces.

[0024] In an embodiment of the present application, the tower crane part of the unmanned tower crane is located, and the current position of the tower crane part of the unmanned tower crane is collected, the current position of the tower crane part of the unmanned tower crane is introduced, and the current position of the tower crane part of the unmanned tower crane is further controlled to facilitate subsequent processing of the tower crane part.

[0025] At this time, the current position and target position of the tower crane are associated, and overall control is performed on the current position and target position of the tower crane, so as to define multiple primary moving paths according to the current position and target position of the tower crane, thereby realizing multi-dimensional control of the current position and target position of the tower crane and ensuring the accuracy of multiple primary moving paths.

[0026] Therefore, multiple advanced moving paths are defined based on multiple primary moving paths, the activity dimensions of the tower crane part and the preset moving time. At this time, the multiple advanced moving paths are further screened by multiple primary moving paths, and are compatible with the overall consideration of multiple primary moving paths, the activity dimensions of the tower crane part and the preset moving time, thereby ensuring multi-dimensional control of the activity dimensions of the tower crane part and the preset moving time.

[0027] Furthermore, the moving trajectory of the tower crane part is defined based on the comparison of multiple high-level moving paths. At this time, each high-level moving path is divided into multiple moving spaces, and multiple optimal moving spaces are defined based on the comparison of the corresponding moving spaces. The moving trajectory of the tower crane part is defined based on the multiple optimal moving spaces, which ensures the accuracy of the moving trajectory of the tower crane part and deepens into the refined management and control of multiple moving spaces.

[0028] refer to Figure 3 , in step S12, path detection is triggered based on the moving trajectory of the tower crane part, and multiple forbidden-entry features are collected in the path detection; In the specific implementation process of the present invention, the specific steps may be: S121: freeze the moving trajectory of the tower crane; S122: dividing a plurality of path detection points based on the moving trajectory of the tower crane part, and performing path detection according to the plurality of path monitoring points; S123: collecting corresponding obstacle data based on the path detection of each path monitoring point; S124: defining an obstacle type according to the plurality of obstacle data, and defining an obstacle level according to the obstacle type and the corresponding volume; S125: Collect multiple obstacles, and define a no-entry feature according to the distance between two adjacent obstacles, the obstacle levels of two adjacent obstacles, and the matching coefficients of two adjacent obstacles, so as to collect multiple no-entry features.

[0029] In an embodiment of the present application, the moving trajectory of the tower crane part is frozen, and the moving trajectory of the tower crane part is further controlled, so as to divide a plurality of path detection points based on the moving trajectory of the tower crane part, and perform path detection according to the plurality of path monitoring points. At this time, a plurality of path monitoring points are formed by dividing the moving trajectory of the tower crane part, and the rationality of the plurality of path monitoring points is guaranteed.

[0030] At this time, the corresponding obstacle data is collected based on the path detection of each path monitoring point, and the corresponding obstacle data is introduced, so that the obstacle type is defined according to the multiple obstacle data, and the obstacle level is defined according to the obstacle type and the corresponding volume. The obstacle type and the corresponding volume are compatible, and the accuracy of the obstacle level is ensured.

[0031] Therefore, multiple obstacles are collected, and no-entry features are defined according to the distance between two adjacent obstacles, the obstacle levels of two adjacent obstacles, and the matching coefficient of two adjacent obstacles. In order to collect multiple no-entry features, the distance between two adjacent obstacles, the obstacle level of two adjacent obstacles, and the matching coefficient of two adjacent obstacles are introduced. The distance between two adjacent obstacles, the obstacle level of two adjacent obstacles, and the matching coefficient of two adjacent obstacles are controlled in multiple dimensions to ensure the accuracy of multiple no-entry features.

[0032] refer to Figure 4 , in step S13, a plurality of forbidden-entry sub-areas are defined according to the protection ranges of the plurality of forbidden-entry features and the locations of the plurality of forbidden-entry features; In the specific implementation process of the present invention, the specific steps may be: S131: freeze each prohibited feature; S132: defining corresponding forbidden levels based on the volumes of each forbidden feature and the types corresponding to each forbidden feature; S133: Associating each forbidden feature with the forbidden level table, and defining a corresponding protection range according to the forbidden level corresponding to each forbidden feature and the position between two adjacent forbidden features; S134: collecting locations of multiple forbidden features; S135: Associating the protection ranges of the multiple no-entry features and the locations of the multiple no-entry features; S136: defining a plurality of forbidden-entry sub-areas based on the protection ranges of the plurality of forbidden-entry features, the locations of the plurality of forbidden-entry features, and the forbidden-entry levels corresponding to the plurality of forbidden-entry features.

[0033] In an embodiment of the present application, each forbidden feature is frozen, and overall control is performed on each forbidden feature. At this time, the corresponding forbidden level is defined based on the volume of each forbidden feature and the type corresponding to each forbidden feature. The forbidden level is introduced, and is compatible with the overall consideration of the volume of each forbidden feature and the type corresponding to each forbidden feature, thereby ensuring multi-dimensional control of the volume of each forbidden feature and the type corresponding to each forbidden feature.

[0034] At this time, each forbidden feature and the forbidden level table are associated, and the corresponding protection range is defined according to the forbidden level corresponding to each forbidden feature and the position between two adjacent forbidden features. This achieves overall control of the forbidden level corresponding to each forbidden feature and the position between two adjacent forbidden features, introduces the protection range, and then controls the protection range.

[0035] Therefore, the locations of multiple forbidden features are collected; the protection ranges of multiple forbidden features and the locations of multiple forbidden features are associated; and multiple forbidden sub-areas are defined based on the protection ranges of multiple forbidden features, the locations of multiple forbidden features and the forbidden levels corresponding to the multiple forbidden features, thereby achieving overall control of the protection ranges of multiple forbidden features, the locations of multiple forbidden features and the forbidden levels corresponding to the multiple forbidden features, and performing multi-dimensional management based on the protection ranges of multiple forbidden features, the locations of multiple forbidden features and the forbidden levels corresponding to the multiple forbidden features, thereby ensuring the accuracy of the multiple forbidden sub-areas and fully considering the protection ranges of multiple forbidden features, the locations of multiple forbidden features and the forbidden levels corresponding to the multiple forbidden features.

[0036] refer to Figure 5 , S14: defining a final no-entry area based on area optimization of multiple no-entry sub-areas; In the specific implementation process of the present invention, the specific steps may be: S141: freeze multiple forbidden sub-areas; S142: forming a plurality of forbidden spaces according to the division of each forbidden sub-area; S143: defining corresponding spatial images based on each forbidden space; S144: defining a corresponding object type according to the recognition of the spatial image, and defining a corresponding optimization coefficient according to the object type and the type matching table; S145: In each forbidden sub-area, multiple optimization coefficients are collected, and an optimization level is constructed based on the multiple optimization coefficients. The corresponding optimization is triggered according to the optimization level and the corresponding forbidden sub-area, and multiple optimized forbidden sub-areas are output. The final forbidden area is defined based on the multiple optimized forbidden sub-areas.

[0037] In an embodiment of the present application, a moving trajectory of a tower crane part is defined according to a current position and a target position of the tower crane part of an unmanned tower crane; path detection is triggered based on the moving trajectory of the tower crane part, and a plurality of forbidden-entry features are collected in the path detection; a plurality of forbidden-entry sub-areas are defined according to protection ranges of the plurality of forbidden-entry features and locations of the plurality of forbidden-entry features; a final forbidden-entry area is defined based on area optimization of the plurality of forbidden-entry sub-areas, thereby performing multi-dimensional control over the plurality of forbidden-entry sub-areas, and further defining the final forbidden-entry area through area optimization of the plurality of forbidden-entry sub-areas and further processing of the plurality of forbidden-entry sub-areas, thereby ensuring the integrity and accuracy of the final forbidden-entry area.

[0038] At this time, multiple restricted-entry sub-areas are frozen, and overall control is performed on the multiple restricted-entry sub-areas, so that multiple restricted-entry spaces are formed according to the division of each restricted-entry sub-area, so as to introduce multiple restricted-entry spaces and further manage the multiple restricted-entry spaces.

[0039] Furthermore, a corresponding spatial image is defined based on each forbidden space, so as to define the corresponding object type according to the recognition of the spatial image, and the corresponding optimization coefficient is defined according to the object type and the type matching table, thereby introducing the object type and fully considering the matching between the object type and the type matching table to define the corresponding optimization coefficient.

[0040] Therefore, in each forbidden sub-area, multiple optimization coefficients are collected, and an optimization level is constructed based on the multiple optimization coefficients. The corresponding optimization is triggered according to the optimization level and the corresponding forbidden sub-area, and multiple optimized forbidden sub-areas are output, thereby ensuring the accuracy of the multiple optimized forbidden sub-areas and realizing the optimized processing of the forbidden sub-areas. At the same time, the final forbidden area is defined based on the multiple optimized forbidden sub-areas, thereby performing multi-dimensional control of the multiple forbidden sub-areas, and further defining the final forbidden area through regional optimization of multiple forbidden sub-areas and further processing of multiple forbidden sub-areas, thereby ensuring the integrity and accuracy of the final forbidden area.

[0041] refer to Figure 6 , S15: defining a corresponding avoidance path according to the final forbidden area and the moving area corresponding to the moving trajectory, and defining an optimized moving trajectory according to the avoidance path, the safe activity range of the tower crane part and the moving trajectory; In the specific implementation process of the present invention, the specific steps may be: S151: freeze the final forbidden area; S152: Associating the final forbidden area and movement trajectory; S153: defining a plurality of avoidance spaces according to the final forbidden area and the moving area corresponding to the moving trajectory; S154: defining corresponding avoidance paths according to the plurality of avoidance spaces and the activity dimensions of the tower crane; S155: Collect the safe activity range of the tower crane in each avoidance space; S156: Associating the avoidance path, the safe range of movement of the tower crane, and the moving trajectory; defining an optimized moving trajectory based on the avoidance path, the safe range of movement of the tower crane, and the moving trajectory.

[0042] In an embodiment of the present application, the final forbidden area is frozen, the final forbidden area and the moving trajectory are introduced, and the final forbidden area and the moving trajectory are controlled. At this time, the final forbidden area and the moving trajectory are associated; multiple avoidance spaces are defined according to the moving areas corresponding to the final forbidden area and the moving trajectory, thereby realizing multi-dimensional control of the moving areas corresponding to the final forbidden area and the moving trajectory, and ensuring the accuracy of multiple avoidance spaces.

[0043] Therefore, corresponding avoidance paths are defined according to multiple avoidance spaces and the activity dimensions of the tower crane, and overall control is carried out based on multiple avoidance spaces and the activity dimensions of the tower crane. Further in-depth control is carried out on each avoidance space to ensure the accuracy of the avoidance space.

[0044] At this time, in each avoidance space, the safe movement range of the tower crane part is collected; the avoidance path, the safe movement range of the tower crane part and the moving trajectory are associated; the optimized moving trajectory is defined based on the avoidance path, the safe movement range of the tower crane part and the moving trajectory, which is compatible with the overall consideration of the avoidance path, the safe movement range of the tower crane part and the moving trajectory, realizes the multi-dimensional control of the avoidance path, the safe movement range of the tower crane part and the moving trajectory, and ensures the accuracy of the optimized moving trajectory.

[0045] refer to Figure 7 , S16: The tower crane part detects multiple environmental features in real time during the movement, and defines the dynamic avoidance logic of the tower crane part according to the multiple environmental features, the corresponding distances and the impact levels of the environmental features; In the specific implementation process of the present invention, the specific steps may be: S161: The tower crane moves along the optimized moving trajectory; S162: The tower crane performs real-time detection during movement and collects multiple surrounding environment data; S163: defining a plurality of environmental features according to a plurality of surrounding environment data and a characteristic logic of the tower crane; marking locations of the plurality of environmental features, and defining corresponding distances according to the locations of the plurality of environmental features; S164: Associating multiple environmental features and corresponding distances, and defining an environmental impact area according to the multiple environmental features and the corresponding distances; S165: freeze multiple environmental features and mark the impact levels of the corresponding environmental features; S166: Associate the environmental impact area with the impact level of the environmental characteristics, and define the dynamic avoidance logic of the tower crane part based on the environmental impact area and the impact level of the environmental characteristics.

[0046] In the specific implementation process of the present invention, a corresponding avoidance path is defined according to the final forbidden area and the moving area corresponding to the moving trajectory, and an optimized moving trajectory is defined according to the avoidance path, the safe activity range of the tower crane part and the moving trajectory; the tower crane part detects multiple environmental features in real time during the movement, and the dynamic avoidance logic of the tower crane part is defined according to the multiple environmental features, the corresponding distances and the influence levels of the environmental features, so that the tower crane part can avoid the final forbidden area and the environmental features during the movement in real time during the movement, thereby ensuring the movement stability of the tower crane part and being compatible with the overall consideration of the final forbidden area and the environmental features during the movement.

[0047] At this time, the tower crane part moves along the optimized moving trajectory. At the same time, the tower crane part performs real-time detection during the movement and collects multiple surrounding environment data. Multiple surrounding environment data are introduced, and overall control is performed on the multiple surrounding environment data, so as to define multiple environmental features according to the multiple surrounding environment data and the characteristic logic of the tower crane part, thereby realizing the precise construction of multiple environmental features. At the same time, the locations of multiple environmental features are marked, and the corresponding distances are defined according to the locations of the multiple environmental features.

[0048] Furthermore, multiple environmental features and corresponding distances are introduced, multiple environmental features and corresponding distances are associated, and environmental impact areas are defined based on the multiple environmental features and corresponding distances. The environmental impact areas are controlled, and the overall impact of the multiple environmental features and corresponding distances is fully considered.

[0049] Therefore, multiple environmental features are frozen and the impact levels of the corresponding environmental features are marked; the environmental impact areas and the impact levels of the environmental features are associated, and the dynamic avoidance logic of the tower crane is defined based on the environmental impact areas and the impact levels of the environmental features, so that the tower crane can avoid the final restricted area and the environmental features during the movement in real time during the movement, thereby ensuring the movement stability of the tower crane and being compatible with the overall consideration of the final restricted area and the environmental features during the movement.

[0050] In an unmanned tower crane, the main thing during the operation of the tower crane is to restrict the trolley on the arm from entering the restricted area, and the movement of the trolley on the arm should switch directions as little as possible. The movement of the trolley on the arm is actually a polar coordinate motion composed of the boom angle and the amplitude value of the trolley on the boom, so this abstracts the movement of the trolley into a polar coordinate motion in a two-dimensional space, and its range of motion is a circle with the length of the boom as the radius.

[0051] First, the motion space of the trolley on the arm is divided into circular grids as shown in the figure below according to a certain angle resolution (1°) and distance resolution (0.2m). Then the forbidden area is divided into grids, and the grids in the forbidden area are calculated. As shown in the figure below, the red grid represents the forbidden area; this grid map is called costmap.

[0052] Finally, a traversal path planning algorithm is designed to calculate the optimal path that meets the conditions. The specific steps are as follows: Calculate and determine the starting position grid and the target position grid; Assuming that n turns are required from the starting position to the target position, an optimal path planning is performed; Traverse n from 0 to 8 and calculate the optimal path until a path that can reach the end point from the starting point is obtained; The following describes the single optimal path planning algorithm in step 2 above: Starting from the starting point, expand to 4 grids in its area, add these 4 grids to the seed set, and increase the path cost by 1 for each grid expanded outward. If a forbidden area is encountered, the cost is set to infinity, which means it is impassable. Select the point with the minimum cost among the seed points and continue to expand outward. If the outward movement is in the direction of the corner, and the seed point and its parent node are moving in the amplitude direction, the number of direction changes is +1. If the number of direction changes is greater than the number of direction changes n, the cost is set to infinity, which means it is impassable. Continue to expand outward according to the above method until there are no seed points or the end point is reached. If the end point is reached, it is considered that this path planning is successful and the final motion path is obtained; if there is no seed point set and it is empty, it means that this path planning has failed, then the reversal number threshold +1, and a single optimal path planning is performed again; According to the above algorithm, it can be ensured that the motion path does not pass through the forbidden area, and the number of movement reversals of the car is minimized, thus obtaining the optimal motion path.

[0053] In an embodiment of the present invention, through the method in the embodiment of the present invention, the moving trajectory of the tower crane part of the unmanned tower crane is defined according to the current position and the target position of the tower crane part; path detection is triggered based on the moving trajectory of the tower crane part, and multiple forbidden features are collected in the path detection; multiple forbidden sub-areas are defined according to the protection ranges of the multiple forbidden features and the locations of the multiple forbidden features; the final forbidden area is defined based on the regional optimization of the multiple forbidden sub-areas, so as to control the multiple forbidden sub-areas in multiple dimensions, and the final forbidden area is further defined through the regional optimization of the multiple forbidden sub-areas and further processing of the multiple forbidden sub-areas, thereby ensuring the integrity and accuracy of the final forbidden area.

[0054] Furthermore, a corresponding avoidance path is defined according to the final restricted area and the moving area corresponding to the moving trajectory, and an optimized moving trajectory is defined according to the avoidance path, the safe activity range of the tower crane part and the moving trajectory; the tower crane part detects multiple environmental features in real time during the movement, and the dynamic avoidance logic of the tower crane part is defined according to the multiple environmental features, the corresponding distances and the impact levels of the environmental features, so that the tower crane part can avoid the final restricted area and the environmental features during the movement in real time during the movement, thereby ensuring the movement stability of the tower crane part and being compatible with the overall consideration of the final restricted area and the environmental features during the movement.

[0055] See also Figure 8 , Figure 8 It is a schematic diagram of the structure of the control system of the restricted area of ​​the unmanned tower crane in the embodiment of the present invention.

[0056] like Figure 8 As shown, a control system for a restricted area by an unmanned tower crane, the control system for a restricted area by an unmanned tower crane comprises: A moving track module 21 is used to define a moving track of the tower crane part according to the current position and the target position of the tower crane part of the unmanned tower crane; A forbidden entry feature module 22, used for triggering path detection based on the moving trajectory of the tower crane part, and collecting multiple forbidden entry features in the path detection; A forbidden sub-area module 23, used to define a plurality of forbidden sub-areas according to the protection ranges of the plurality of forbidden features and the positions of the plurality of forbidden features; A no-entry area module 24, configured to define a final no-entry area based on area optimization of multiple no-entry sub-areas; The optimization module 25 is used to define a corresponding avoidance path according to the final forbidden area and the moving area corresponding to the moving trajectory, and define an optimized moving trajectory according to the avoidance path, the safe activity range of the tower crane part and the moving trajectory; The dynamic avoidance module 26 is used for the tower crane to detect multiple environmental features in real time during movement, and to define the dynamic avoidance logic of the tower crane according to the multiple environmental features, the corresponding distances and the impact levels of the environmental features.

[0057] See also Fig. 9 , refer to the following Fig. 9 The electronic intelligent device 40 according to this embodiment of the present invention is described. Fig. 9 The electronic intelligent device 40 shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.

[0058] like Fig. 9 As shown, the electronic intelligent device 40 is in the form of a general computing intelligent device. The components of the electronic intelligent device 40 may include but are not limited to: at least one processing unit 41, at least one storage unit 42, and a bus 43 connecting different system components (including the storage unit 42 and the processing unit 41).

[0059] The storage unit stores program codes, which can be executed by the processing unit 41, so that the processing unit 41 executes the steps according to various exemplary embodiments of the present invention described in the above “Embodiment Method” section of this specification.

[0060] The storage unit 42 may include a readable medium in the form of a volatile storage unit, such as a random access memory unit (RAM) 421 and / or a cache memory unit 422 , and may further include a read-only memory unit (ROM) 423 .

[0061] The storage unit 42 may also include a program / utility 424 having a set (at least one) of program modules 425, such program modules 425 including but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment.

[0062] Bus 43 may represent one or more of several types of bus structures, including a memory unit bus or memory unit controller, a peripheral bus, an accelerated graphics port, a processing unit, or a local bus using any of a variety of bus architectures.

[0063] The electronic smart device 40 may also communicate with one or more external smart devices (e.g., keyboards, pointing smart devices, Bluetooth smart devices, etc.), one or more smart devices that enable a user to interact with the electronic smart device 40, and / or any smart device that enables the electronic smart device 40 to communicate with one or more other computing smart devices (e.g., routers, modems, etc.). Such communication may be performed via an input / output (I / O) interface 44. Furthermore, the electronic smart device 40 may also communicate with one or more networks (e.g., a local area network (LAN), a wide area network (WAN), and / or a public network, such as the Internet) via a network adapter 45. Fig. 9 As shown, the network adapter 45 communicates with other modules of the electronic intelligent device 40 via the bus 43. It should be understood that although Fig. 9 Not shown, other hardware and / or software modules may be used in conjunction with the electronic intelligent device 40, including but not limited to: microcode, intelligent device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup planning systems.

[0064] Through the description of the above implementation, it is easy for those skilled in the art to understand that the example implementation described here can be implemented by software, or by software combined with necessary hardware. Therefore, the technical solution according to the implementation of the present disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, and includes several instructions to enable a computing intelligent device (which can be a personal computer, a server, a terminal device, or a network intelligent device, etc.) to execute the method according to the implementation of the present disclosure.

[0065] Those skilled in the art can understand that all or part of the steps in the various methods of the above embodiments can be completed by instructing related hardware through a program, and the program can be stored in a computer-readable storage medium, and the storage medium can include: a read-only memory (ROM), a random access memory (RAM), a disk or an optical disk, etc. In addition, it stores computer program instructions, and when the computer program instructions are executed by a computer, the computer executes the above method.

[0066] In addition, the control method and system for the restricted area of ​​the unmanned tower crane provided in the embodiment of the present invention are introduced in detail above. Specific examples are used in this article to illustrate the principle and implementation mode of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea; at the same time, for general technical personnel in this field, according to the idea of ​​the present invention, there will be changes in the specific implementation mode and application scope. In summary, the content of this specification should not be understood as a limitation on the present invention.

Claims

1. A method for controlling a restricted area by an unmanned tower crane, characterized in that: Applicable to the control scenario of unmanned tower crane in restricted areas; The control method of the unmanned tower crane for the restricted area includes: Defining a moving trajectory of the tower crane part according to the current position and the target position of the tower crane part of the unmanned tower crane; Trigger path detection based on the moving trajectory of the tower crane, and collect multiple prohibited entry features during path detection; Defining multiple no-entry sub-areas according to the protection ranges of multiple no-entry features and the locations of multiple no-entry features; Defining a final keep-out area based on area optimization of multiple keep-out sub-areas; Define the corresponding avoidance path according to the final forbidden area and the moving area corresponding to the moving trajectory, and define the optimized moving trajectory according to the avoidance path, the safe activity range of the tower crane part and the moving trajectory; The tower crane detects multiple environmental features in real time during movement, and defines the dynamic avoidance logic of the tower crane according to the multiple environmental features, the corresponding distances and the impact levels of the environmental features.

2. The method for controlling a restricted area by an unmanned tower crane according to claim 1, characterized in that: Defining the moving trajectory of the tower crane part according to the current position and the target position of the tower crane part of the unmanned tower crane includes: Locate the crane part of the unmanned tower crane and collect the current position of the crane part of the unmanned tower crane; Associate the current position and target position of the crane part; defining a plurality of primary movement paths according to the current position and the target position of the tower crane part; Based on the multiple primary movement paths, the activity dimensions of the tower crane part and the preset movement time, multiple advanced movement paths are defined. At this time, the multiple advanced movement paths are further screened by the multiple primary movement paths; The moving trajectory of the tower crane part is defined based on the comparison of multiple high-level moving paths. At this time, each high-level moving path is divided into multiple moving spaces, and multiple optimal moving spaces are defined based on the comparison of the corresponding moving spaces. The moving trajectory of the tower crane part is defined based on the multiple optimal moving spaces.

3. The method for controlling a restricted area by an unmanned tower crane according to claim 2, characterized in that: The moving trajectory of the tower crane triggers the path detection, and collects multiple forbidden features during the path detection, including: Freeze the moving trajectory of the tower crane part; Divide multiple path detection points based on the moving trajectory of the tower crane part, and perform path detection based on the multiple path monitoring points; Collecting corresponding obstacle data based on path detection at each path monitoring point; Defining obstacle types according to multiple obstacle data, and defining obstacle levels according to the obstacle types and corresponding volumes; A plurality of obstacles are collected, and a no-entry feature is defined according to a distance between two adjacent obstacles, an obstacle level of two adjacent obstacles, and a matching coefficient of two adjacent obstacles, so as to collect a plurality of no-entry features.

4. The method for controlling a restricted area by an unmanned tower crane according to claim 3, characterized in that: Defining a plurality of forbidden sub-areas according to the protection ranges of the plurality of forbidden features and the locations of the plurality of forbidden features includes: Freeze each prohibited feature; Define corresponding forbidden levels based on the volume of each forbidden feature and the type corresponding to each forbidden feature; Associate each forbidden feature with the forbidden level table, and define the corresponding protection range according to the forbidden level corresponding to each forbidden feature and the position between two adjacent forbidden features; Collect the locations of multiple forbidden features; Associating the protection ranges of multiple no-entry features and the locations of multiple no-entry features; A plurality of no-entry sub-areas are defined based on protection ranges of the plurality of no-entry features, locations of the plurality of no-entry features, and no-entry levels corresponding to the plurality of no-entry features.

5. The method for controlling a restricted area by an unmanned tower crane according to claim 4, characterized in that: The final no-entry area is defined based on the area optimization of the multiple no-entry sub-areas, including: Freeze multiple forbidden sub-areas; A plurality of forbidden spaces are formed according to the division of each forbidden sub-area; Define corresponding spatial images based on each forbidden space; Defining a corresponding object type according to the recognition of the spatial image, and defining a corresponding optimization coefficient according to the object type and the type matching table; In each forbidden sub-area, multiple optimization coefficients are collected, an optimization level is constructed based on the multiple optimization coefficients, and corresponding optimization is triggered according to the optimization level and the corresponding forbidden sub-area, and multiple optimized forbidden sub-areas are output, and the final forbidden area is defined based on the multiple optimized forbidden sub-areas.

6. The method for controlling a restricted area by an unmanned tower crane according to claim 5, characterized in that: The method of defining a corresponding avoidance path according to the final forbidden area and the moving area corresponding to the moving trajectory, and defining an optimized moving trajectory according to the avoidance path, the safe activity range of the tower crane part and the moving trajectory, includes: Freeze the final forbidden area; Associate the final forbidden area and movement trajectory; Define multiple avoidance spaces according to the final forbidden area and the moving area corresponding to the moving trajectory; Corresponding avoidance paths are defined according to multiple avoidance spaces and the activity dimensions of the tower crane.

7. The method for controlling a restricted area by an unmanned tower crane according to claim 6, characterized in that: The method further comprises: defining a corresponding avoidance path according to the final forbidden area and the moving area corresponding to the moving trajectory, and defining an optimized moving trajectory according to the avoidance path, the safe activity range of the tower crane part and the moving trajectory. In each avoidance space, collect the safe range of movement of the tower crane; An avoidance path, a safe range of movement of the crane part, and a moving trajectory are associated; and an optimized moving trajectory is defined based on the avoidance path, the safe range of movement of the crane part, and the moving trajectory.

8. The method for controlling a restricted area by an unmanned tower crane according to claim 7, characterized in that: The tower crane part detects multiple environmental features in real time during the movement, and defines the dynamic avoidance logic of the tower crane part according to the multiple environmental features, the corresponding distances and the impact levels of the environmental features, including: The tower crane part moves along the optimized moving trajectory; The tower crane performs real-time detection during movement and collects multiple surrounding environment data; A plurality of environmental features are defined according to a plurality of surrounding environment data and a characteristic logic of a tower crane part; positions of the plurality of environmental features are marked, and corresponding distances are defined according to the positions of the plurality of environmental features.

9. The method for controlling a restricted area by an unmanned tower crane according to claim 8, characterized in that: The tower crane part detects multiple environmental features in real time during the movement, and defines the dynamic avoidance logic of the tower crane part according to the multiple environmental features, the corresponding distances and the impact levels of the environmental features, and also includes: Associating a plurality of environmental features and corresponding distances, and defining an environmental impact area based on the plurality of environmental features and the corresponding distances; Freeze multiple environmental features and mark the impact levels of the corresponding environmental features; The environmental impact area and the impact level of the environmental characteristics are associated, and the dynamic avoidance logic of the tower crane part is defined based on the environmental impact area and the impact level of the environmental characteristics.

10. A control system for unmanned tower cranes in restricted areas, characterized in that: The control system of the unmanned tower crane for the restricted area is applied to the control method of the unmanned tower crane for the restricted area as claimed in any one of claims 1 to 9, and the control system of the unmanned tower crane for the restricted area includes: A moving trajectory module is used to define the moving trajectory of the tower crane part according to the current position and target position of the tower crane part of the unmanned tower crane; The forbidden entry feature module is used to trigger the path detection based on the moving trajectory of the tower crane part and collect multiple forbidden entry features in the path detection; A forbidden sub-area module, used to define multiple forbidden sub-areas according to the protection ranges of multiple forbidden features and the locations of multiple forbidden features; A keep-out area module, used to define a final keep-out area based on area optimization of multiple keep-out sub-areas; An optimization module is used to define a corresponding avoidance path according to the final forbidden area and the moving area corresponding to the moving trajectory, and to define an optimized moving trajectory according to the avoidance path, the safe activity range of the tower crane part and the moving trajectory; The dynamic avoidance module is used to detect multiple environmental features in real time during the movement of the tower crane, and define the dynamic avoidance logic of the tower crane according to the multiple environmental features, the corresponding distances and the impact levels of the environmental features.

Images