CN103278153A - Three-dimensional path planning method for automobile crane based on space two-dimensional mapping - Google Patents
Three-dimensional path planning method for automobile crane based on space two-dimensional mapping Download PDFInfo
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Abstract
The invention discloses a three-dimensional path planning method for an automobile crane based on space two-dimensional mapping. Aiming at a three-dimensional path planning problem of the automobile crane, the method helps to converse a three-dimensional space into a two-dimensional map with height information, and a corresponding search algorithm and a rollback strategy are designed on the basis. An efficient solution is provided for the three-dimensional path planning problem of the automobile crane by the invention, and the security of hoisting operation is improved.
Description
Technical field
The present invention relates to a kind of truck-mounted crane three-dimensional path planning method, particularly a kind of truck-mounted crane three-dimensional path planning method based on the space two-dimensional mapping.
Background technology
The crane path planning is the key that guarantees lifting safety as the core content of Hoisting Program, and accurately effective path planning directly has influence on security and the efficient of operation.Yet the complicated and device-restrictive of lifting environment makes artificial planning efficiency all lower with the execution accuracy.Therefore, in order to improve lifting efficient, save the labour, be necessary path planning is studied, generate an executable optimization crane operation sequence automatically.
Though truck-mounted crane can be used for reference mobile robot's paths planning method, the characteristics of oneself are also arranged, traditional crane paths planning method is decomposed into following two stages with planning:
1) in the formulation stage of Hoisting Program, checks checking to obtain the key operations of crane with conventional CAD software to dangerous discrete critical path point occurring;
2) in the execute phase of Hoisting Program, rely on rich experience subjectively to be commanded with the path between the discrete key point of polishing by senior slip-stick artist.
But there is following problem in classic method:
1) restriction by CAD design software self causes the analysis of key point and chooses comprehensive inadequately;
2) to depend on commanding's subjective judgement more serious for the path planning between the key point, is difficult to guarantee security;
3) planing method of entire path system not is difficult to form the fullpath of an optimization.
By researching and analysing various planing methods, very ripe for the paths planning method under the environment known case, and the path planning algorithm at crane also has more research, but the execution time of these path planning algorithms is long or required storage area is big, and do not consider the characteristics of truck-mounted crane self, therefore need to carry out the design of introductory path planning algorithm at truck-mounted crane.
Summary of the invention
Technical matters to be solved by this invention is, at the prior art deficiency, a kind of truck-mounted crane three-dimensional path planning method based on space two-dimensional mapping is provided, for the three-dimensional path planning problem of truck-mounted crane proposes a kind of effective solution thinking, improves the security of lifting operation.
For solving the problems of the technologies described above, the technical solution adopted in the present invention is: a kind of truck-mounted crane three-dimensional path planning method based on the space two-dimensional mapping, and this method is:
1) to the initialization of lifting two-dimensional map, determines lifting initial point and impact point position; Determine that the threshold value HeightValue of each discrete point height multiply by the variable phase angle sine value of truck-mounted crane arm for the truck-mounted crane total arm length; Wherein the discrete point height refers to that discrete point is apart from the height on ground;
2) initial point is labeled as current point;
3) judge whether 4 discrete points of current periphery can arrive, and how all can not arrive, and judge that then this point is for the dead point, if then enter 11); But otherwise mark all point of arrivals, enter 4);
4) the angle of revolution θ of current some position of judgement
Initial 1With change angle θ
Initial 2And the angle of revolution θ of impact point position
Target 1With change angle θ
Target 2Magnitude relationship, the priority of choosing of 4 discrete points of current periphery is set according to following table, wherein 1 representative is the highest, 4 representatives are minimum, the discrete point that a left side current point of revolution representative is turned left and obtained, right-hand rotation representative is current when the discrete point of turning right and obtaining, and amplitude increases the current point of representative and increases direction toward amplitude and move the discrete point that obtains, and amplitude reduces to represent current point and reduces direction toward amplitude and move the discrete point that obtains;
5) obtaining priority level is 1 discrete point, judges that highly whether this point surpasses threshold value HeightValue, if do not surpass, then this discrete point is set to the Search Results point, and add in the routing table, turn to 8); Otherwise, enter 6);
6) check that priority is 2 discrete point height, judge that highly whether this point surpasses threshold value HeightValue, if do not surpass, then this discrete point is set to the Search Results point, and add must routing table in, turn to 8); Otherwise, check priority is whether 3 discrete point height surpasses threshold value HeightValue, if priority 3 discrete point height surpasses threshold value HeightValue, then this discrete point is set to the Search Results point, and add in the routing table, turn to 8); Otherwise, check that priority is 4 discrete point, if the discrete point height of priority 4 surpasses threshold value HeightValue, then this discrete point is set to the Search Results point, and add in the routing table, turn to 8); Otherwise enter 7);
7) if priority be 2,3,4 discrete point height all above described threshold value, then priority is that 1 discrete point is set to the Search Results point, and add in the routing table;
8) described current point is labeled as " in the path ", described Search Results point is labeled as new current point;
9) judge above-mentioned steps 8) in new current point whether be impact point, if, press search order output the Search Results point in the routing table, turn to 11); If not, return 3);
10) current state of judging 4 discrete points around the new current point whether be can not arrive or Already in in the routing table, if the state of 4 discrete points is any one in above two kinds on every side, 4 discrete points all can not be selected around the so new current point, this is the dead point for mark, return back on the last discrete point that gets current point new in the routing table, a last discrete point of new current point is labeled as current point, returns 3);
11) finish.
Compared with prior art, the beneficial effect that the present invention has is: the present invention is converted into the two-dimensional map that has elevation information with three dimensions, and designs corresponding searching algorithm on this basis; The present invention has improved the security of lifting operation for the three-dimensional path planning problem of truck-mounted crane has proposed a kind of effective solution thinking.
Description of drawings
Fig. 1 is one embodiment of the invention method flow diagram;
Fig. 2 is one embodiment of the invention truck-mounted crane spherical co-ordinate synoptic diagram;
Fig. 3 is one embodiment of the invention truck-mounted crane polar coordinates synoptic diagram;
Fig. 4 is one embodiment of the invention truck-mounted crane polar coordinate system discrete point synoptic diagram;
Fig. 5 is one embodiment of the invention route searching strategy synoptic diagram;
Fig. 6 is one embodiment of the invention simulation result synoptic diagram.
Embodiment
As shown in Figure 1, be one embodiment of the invention method flow diagram.
The three-dimensional work space of truck-mounted crane is described:
The truck-mounted crane path planning problem refers in working environment, seeks the path from the given position to the target location.Path planning algorithm is divided into spatial division and searching algorithm two parts.Action feature at truck-mounted crane, the crane job of this paper space is analyzed, and sets up heavy-duty machine working space coordinate system, and space object is described, the three-dimensional working space of crane is described with two-dimensional map, thereby realizes three-dimensional work space division.
Three-dimensional coordinate system is set up:
Truck-mounted crane elemental motion is mainly and hoists, revolution, luffing and flexible, in the actual hoisting process of truck-mounted crane, according to actual process and operation, sets and followingly supposes:
Therefore (1) because truck-mounted crane position in hoisting process remains constantly, suppose that the length of arm keeps initial state constant.
(2) because the truck-mounted crane brachium in case set, remains unchanged substantially, therefore suppose that crane does not include expanding-contracting action in course of action, have only 3 elemental motions: hoist, revolution and luffing operation.
(3) amplitude of fluctuation of restricting in the hoisting process is little, therefore supposes that lifting rope keeps vertical state always.
According to hypothesis 1 and 2 as can be known, gib arm of crane end track is all the time on first sphere that with the brachium is radius, as shown in Figure 2, and arbitrarily some coordinates such as A point coordinate are (R*cos θ 2*cos θ 1, R*cos θ 2*sin θ 1, R*sin θ 2) on the sphere, wherein R is radius, immobilize, the coordinate of putting on the sphere is only relevant with angle of revolution θ 1 these two angles with change angle θ 2 so, θ 1 and θ 2 unique definite umbilical points.According to these characteristics, the point on the sphere vertically is mapped on the xoz plane, and is the coordinate center with the centre of sphere, set up polar coordinate system, the coordinate of polar coordinate system mid point is represented with change angle θ 2 and angle of revolution θ 1, shown in Fig. 2 .2.Set up through mapping and polar coordinate system, point just can replace with the polar coordinate system mid point on the sphere so, as A among Fig. 2 .2, and B, namely represent A and B point on the sphere.
Because the feasible zone of arm end track is whole first sphere among Fig. 2, after through vertical mapping, the feasible zone of track is whole circle among Fig. 3.Therefore, under polar coordinates, the track feasible zone of arm end can be represented with following set:
S={X(θ2,θ1)|0°<=θ1<=360°,0°<=θ2<=90°}。
In addition, according to hypothesis 3 as can be known, hanging object and arm end are on the same vertical curve, therefore, the x coordinate of suspended object is identical with the coordinate of arm end with the z coordinate, suppose suspended object a certain position M under the A point in Fig. 2, impact point is a certain position N below the B point, so, suspended object will be from M to N point, the arm end position must be from the A point to the B point, be reflected under the polar coordinate system is exactly that A is to B, this shows, realize the three-dimensional path planning of suspended object, must satisfy the path planning requirement of arm end position under polar coordinates.Yet, the path planning that only satisfies the arm end is not enough, this is because suspended object is when carrying out three-dimensional path planning, will inevitably produce the variation of height because of object height in the scene, therefore, when solving arm end path planning, also need to consider the height problem of object in suspended object and the scene.
According to above analysis, the path planning problem of suspended object can be divided into two parts, a part is 2D path planning problem under polar coordinate system, another part is the height change problem of suspended object.By setting up polar coordinate system and the arm end vertically being shone upon, solved first's problem, the second portion problem will be set forth below.
The description of object scene under the coordinate system:
Foundation through coordinate system, though the three-dimensional planning problem of lifting object is converted into 2D path planning problem under the polar coordinate system, but the path that this planning obtains only comprises angle of revolution and change angle information, do not embody the height change of lifting object, this be since under the polar coordinate system coordinate of feasible zone mid point only comprise revolution and change angle, the elevation information that lacks space object on the current location, at this problem, this paper is thought of as among the feasible zone S each some X, and (θ 2, θ 1) all add the elevation information of object on this aspect, like this, when considering 2D path planning, can carry out descending operation to lifting object according to the elevation information that adds on the current location, thereby solve the problem of above-mentioned second portion.
Because feasible zone S mid point all is continuity point, consider in the actual hoisting process when crane turns round and operates with luffing, the angle changing of a minimum is always arranged, therefore, this paper considers the feasible region S under the polar coordinates is carried out discretize according to the minimum change angle, supposes that revolution minimum change angle is α, and the luffing minimum angles is β, so the zone is divided as shown in Figure 4, wherein, be to turn round operation as the P point to the Q point, the P point then is the luffing operation to the M point.As discrete point, feasible region S1 can replace with following set so with intersection point among the figure:
S1={X(θ2,θ1)|0°<=θ1<=360°,0o<=θ2<=90°}
θ 1=δ α, δ is integer
According to considering before, for each point among the feasible zone S adds elevation information, yet after discretize, whole space is represented by discrete point set S1, therefore, only need the elevation information of current some present position space object of adding in each discrete point just can reach requirement.Like this, each discrete angle of revolution and change angle information of having pointed out before comprising has also comprised elevation information, and this elevation information is the maximum height of object on the current discrete point.Be 5 as scene object height, this object has covered 3 discrete points, and then the height of these three discrete points is 5, if current object height surpasses arm end height, illustrates that discrete point that this object covers is for can not the point of arrival.In addition, if there is not space object on the discrete point, then this discrete point height is 0.By the feasible zone under the polar coordinate system being dispersed and adding elevation information, just can obtain having the two-dimensional map of elevation information, this map can be described the three-dimensional work space of truck-mounted crane.
By above analysis, utilize the two-dimensional map that has height parameter under the polar coordinate system that whole three dimensions is divided and described, the three-dimensional path planning problem of truck-mounted crane just is converted into the 2D path planning problem, for searching algorithm afterwards design lays the foundation.
The truck-mounted crane path search algorithm:
According to above analysis, the path planning problem of truck-mounted crane is converted into a certain discrete point on the gained two-dimensional map to the path planning problem of another discrete point.This paper carries out the searching algorithm design at the path planning problem of the two-dimensional map that has height parameter.
Path optimization's target:
Lifting object is being winched to from starting point the process of terminal point, may exist mulitpath to meet the demands, but not necessarily optimum, therefore need the design path optimization aim, carry out routing according to optimization aim.And according to reality lifting characteristics, the quality in path depends primarily on security and economic benefit two aspects.Wherein, security mainly relates to collision problem and overload problems, and economic benefit conveniently is mainly reflected on the ease-to-operate.This paper only considers ease-to-operate, will lift ease-to-operate as optimization aim.
Path point selection strategy:
Because each discrete point has 4 kinds of choice directions in two-dimensional map: left revolution, right-hand rotation, amplitude increase and amplitude reduces, and therefore, need take certain path point search strategy to carry out choosing of path point.
At the simplest path optimization of lifting operation target, this paper designs two kinds of routing strategies, and a kind of is the global search strategy, and a kind of is the Local Search strategy.
The global search strategy refers to the general direction searched for.Specific strategy is:
(1) judge whether 4 discrete points of current periphery can reach, how all unreachable, this judges that this point is the dead point, but otherwise marks the point of arrival.
(2) angle of revolution θ target 2 and change angle θ target 2 magnitude relationship of judgement current location angle of revolution θ initial 1 and change angle θ initial 2 and target location, according to the priority of choosing that 4 discrete points of current periphery are set shown in the following table 1, wherein 1 representative is the highest, and 4 representatives are minimum.
Judge in conjunction with attainability in (1) according to priority (3), the selection priority of each point is adjusted that if the high priority discrete point can not arrive, this should remove from priority by point, the priority level lower than this priority all subtracts 1.
(4) select next discrete point according to priority, the result points that the point that priority is the highest is exported as the global search strategy.
Table 1 priority Rule of judgment
The Local Search strategy is replenishing of global search strategy and perfect.Consider situation as shown in Figure 5, wherein M is current point, B is impact point, suppose discrete point N point highly be go out around 10, the N point M point outward all the other 3 discrete point height all be 0, if according to the fixed direction of global search strategy, route is M-〉N-〉P-〉B, apparent, this selection is not as M-〉Q-〉D-〉L-〉P-〉B, therefore, be necessary considering the local strategy of global search strategy basis employing.At this situation, this paper adopts a kind of simple threshold decision method, if the height difference of the height of resulting next discrete point of global search strategy and current point surpasses a certain threshold value HeightValue, then carries out the Local Search strategy.The specific strategy step is as follows:
(1) carry out the global search strategy, obtain priority level and be 1 discrete point, judge that highly whether this point satisfies the threshold value requirement, if meet the demands, then this discrete point is set to the Search Results point, otherwise, turn to (2);
(2) according to the priority orders that records in the global search strategy, check that priority is 2 discrete point height, judges that highly whether this point satisfies the threshold value requirement, if satisfy, then this discrete point is set to the Search Results point, otherwise, check priority is whether 3 discrete point height satisfies condition; If the priority 3 discrete point meets the demands, then this discrete point is set to the Search Results point, otherwise, check that priority is 4 discrete point; If the discrete point height of priority 4 meets the demands, then this discrete point is set to the Search Results point, otherwise turns to (3).
(3) all do not satisfy the threshold value requirement if priority is 2,3,4 discrete point, then priority is that 1 discrete point is set to the Search Results point.
(4) current point is labeled as " in the path ", and gained Search Results point is sought next point as current point.
Path rollback strategy:
Because after carrying out path point selection strategy, might obtain such point: gone out a last discrete point around this point, all the other 3 points all are unreachable, or the point that obtains has suffered in the path, algorithm will occur being absorbed in dead band or the endless loop like this, therefore, need take path rollback strategy.
The rollback strategy is: search for by the next discrete point that path point selection strategy is obtained, whether the current state of judging 4 points around this point is can not arrive or Already in the gained path, if the state of 4 points all is any one in above two kinds on every side, 4 points all can not be selected around this point so, show that this point is the dead point, need return back to in the path on last discrete point.In discrete point, the dead point of this point of mark for having searched for continues to seek next eligible point by the route searching strategy then on returning back to.
This paper utilizes C++ to carry out the path planning algorithm design according to above analysis result, has solved lifting object three-dimensional path planning problem, and the result is carried out analysis verification.
According to above theoretical analysis, at truck-mounted crane three-dimensional path planning problem, need finish foundation and two steps of path planning algorithm of the two-dimensional map of band height parameter, at this 2 point, need utilize the two-dimensional map of C++ and searching algorithm to carry out the class formation design, for the realization of searching algorithm is laid the groundwork.
According to above-mentioned analysis result, three dimensions is reduced to a two-dimensional map that has height parameter, and according to minimum angle of revolution and minimum change angle with the two-dimensional map discretize, each point includes object height information in the space.According to these characteristics, this paper designs a Mynode class and represents map, stores two-dimensional map information, and such includes change angle, angle of revolution and the object height information of current point.Again owing to will consider the rollback strategy, add the state that a variable comes the current point of mark, state has 3 kinds, is respectively to search for, search in the path sequence neutralization, therefore, such comprises three variablees: change angle, angle of revolution, height and current dotted state.
After map class is determined, consider and to preserve route programming result, therefore, this paper design path storage class Node_In_Table is as a result come the storing path program results, and such comprises peripheral 4 the feasible state up and down of change angle, angle of revolution, this point of discrete point.
Under the situation that two-dimensional map has been set up, design a Quadtree_structure class and carry out the realization of algorithm.Such realizes the initial work, path planning algorithm of map and output function as a result.Such comprises Quadtree_structure map initialization function, search route searching function and Node_In_Table store results variable.
The current minimum angle of revolution of This document assumes that is 6 degree, and minimum change angle also is 6 degree, and discrete point adds up to N*M among the feasible zone S1 so, N=360/6=60 wherein, and M=90/6=15, so discrete counting is S
1=60*15=900.
The initialization condition of hypothesis instance 1 is: the starting point change angle is 2, and the angle of revolution also is 2, and the height of starting point lifting object is 3, and the change angle of target location is 10, and the angle of revolution is that 10 object heights are 6.And consider that scene has object height information, as by as table 2 mode discrete point is carried out the height setting, wherein 1500 represent this point and can not arrive, all the other discrete point height all are 0, and height threshold is set is 7.
Table 2 part discrete point elevation information
Initialization information is brought in the search function obtains the result as shown in Figure 6, algorithm execution time is 4.336 milliseconds, and the algorithm iteration number of times is 17.
At above example, if adopt the locational space describing method that three-dimensional working space is divided, so according to the hypothesis in the example 1, three dimensions can be carried out discretize, be divided into 60*15*20 small cubes, each small cubes represents a discrete point.According to the height initialization condition of table 4-1, these small cubes attributes are carried out initialization, if on the current small cubes object is arranged, then this cube attribute is set to 1, otherwise is 0, thereby finishes the work the space initialization.Then, on search strategy described herein basis, for each discrete point increases upper and lower two directions of search of lifting object, utilize searching algorithm that initialization condition identical in the example 1 is searched for, it is as follows to obtain the three-dimensional search path,
(2,2,3)->(3,2,3)->(4,2,3)->(5,2,3)->(6,2,3)->(7,2,3)->(8,2,3)->(9,2,3)->(10,2,3)->(10,3,3)->(10,4,3)->(10,5,3)->(10,6,3)->(10,7,3)->(10,8,3)->(10,9,3)->(10,10,3)->(10,10,4)->(10,10,5)->(10,10,6)。Wherein three coordinates of each point represent the angle of revolution respectively, change angle and height, and be 6.959 milliseconds search time, iterations 20 times.
In example 1, utilize the space-division method of this paper, three dimensions is carried out two-dimensional map, then according to search strategy operation of the present invention, discrete point (2,3) on the right of discrete point just forwards to from (2,2) as can be known according to the Local Search strategy; Because (3,3) point does not highly surpass threshold value, just undertaken by the global search strategy then, surpass threshold value again to (4,3) point, then press Local Search policy selection (3,4); Then since (6,4) on every side 3 all can not arrive, therefore (6,4) are the dead points, adopt the rollback strategy, turn to (5,5) from (5,4), routing meets the search strategy of this paper equally afterwards.
In addition, example 1 and example 2 are compared shown in table 4-2 from algorithm execution time, iterations and storage area.Example 1 is that this paper adopts two-dimensional map map division methods, and example 2 is conventional three dimensions division methods.Both contrasts significantly reduce algorithm in this paper storage area as can be known, and search time and iteration reduce, and reach the purpose of the three-dimensional path planning complicacy that reduces truck-mounted crane.
Table 3 example 1 and example 2 contrasts
Claims (1)
1. truck-mounted crane three-dimensional path planning method based on space two-dimensional mapping is characterized in that this method is:
1) to the initialization of lifting two-dimensional map, determines lifting initial point and impact point position, determine that the threshold value HeightValue of each discrete point height multiply by the variable phase angle sine value of truck-mounted crane arm for the truck-mounted crane total arm length; Wherein the discrete point height refers to that discrete point is apart from the height on ground;
2) initial point is labeled as current point;
3) judge whether 4 discrete points of current periphery can arrive, if all can not arrive, judge that then this point is for the dead point, if then enter 11); But otherwise mark all point of arrivals, enter 4);
4) the angle of revolution θ of current some position of judgement
Initial 1With change angle θ
Initial 2And the angle of revolution θ of impact point position
Target 1With change angle θ
Target 2Magnitude relationship, the priority of choosing of 4 discrete points of current periphery is set according to following table, wherein 1 representative is the highest, 4 representatives are minimum, the discrete point that a left side current point of revolution representative is turned left and obtained, right-hand rotation representative is current when the discrete point of turning right and obtaining, and amplitude increases the current point of representative and increases direction toward amplitude and move the discrete point that obtains, and amplitude reduces to represent current point and reduces direction toward amplitude and move the discrete point that obtains;
5) obtaining priority level is 1 discrete point, judges that highly whether this point surpasses threshold value HeightValue, if do not surpass, then this discrete point is set to the Search Results point, and add in the routing table, turn to 8); Otherwise, enter 6);
6) check that priority is 2 discrete point height, judge that highly whether this point surpasses threshold value HeightValue, if do not surpass, then this discrete point is set to the Search Results point, and add must routing table in, turn to 8); Otherwise, check priority is whether 3 discrete point height surpasses threshold value HeightValue, if priority 3 discrete point height surpasses threshold value HeightValue, then this discrete point is set to the Search Results point, and add in the routing table, turn to 8); Otherwise, check that priority is 4 discrete point, surpass threshold value HeightValue if priority is 4 discrete point height, then this discrete point is set to the Search Results point, and add in the routing table, turn to 8); Otherwise enter 7);
7) if priority be 2,3,4 discrete point height all above described threshold value, then priority is that 1 discrete point is set to the Search Results point, and add in the routing table;
8) described current point is labeled as " in the path ", described Search Results point is labeled as new current point;
9) judge above-mentioned steps 8) in new current point whether be impact point, if, press search order output the Search Results point in the routing table, turn to 11); If not, return 3);
10) current state of judging 4 discrete points around the new current point whether be can not arrive or Already in in the routing table, if the state of 4 discrete points is any one in above two kinds on every side, 4 discrete points all can not be selected around the so new current point, this is the dead point for mark, return back on the last discrete point that gets current point new in the routing table, a last discrete point of new current point is labeled as current point, returns 3);
11) finish.
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104484510A (en) * | 2014-11-28 | 2015-04-01 | 大连理工大学 | Novel hoisting action planning method for crane |
| CN105469445A (en) * | 2015-12-08 | 2016-04-06 | 电子科技大学 | Step size changeable map generation method |
| CN106966298A (en) * | 2017-04-17 | 2017-07-21 | 山东建筑大学 | The intelligent hanging method of assembled architecture based on machine vision and system |
| CN108415383A (en) * | 2018-02-28 | 2018-08-17 | 上海士翌测试技术有限公司 | Driving intellectualizing system based on Internet of Things |
| CN112069698B (en) * | 2020-09-27 | 2024-04-19 | 中国化学工程第六建设有限公司 | BIM-based hoisting simulation construction method and system |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101441736A (en) * | 2007-11-21 | 2009-05-27 | 新乡市起重机厂有限公司 | Path planning method of motor crane robot |
| CN102542361A (en) * | 2012-01-11 | 2012-07-04 | 中联重科股份有限公司 | Method for planning path of lift object for crane |
| WO2012173496A1 (en) * | 2011-06-14 | 2012-12-20 | Crown Equipment Limited | Method and apparatus for facilitating map data processing for industrial vehicle navigation |
| US20130054129A1 (en) * | 2011-08-26 | 2013-02-28 | INRO Technologies Limited | Method and apparatus for using unique landmarks to locate industrial vehicles at start-up |
| CN103017757A (en) * | 2012-12-06 | 2013-04-03 | 中联重科股份有限公司 | Engineering machinery entering path planning method and path planning apparatus |
-
2013
- 2013-04-27 CN CN201310152931.9A patent/CN103278153B/en not_active Expired - Fee Related
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101441736A (en) * | 2007-11-21 | 2009-05-27 | 新乡市起重机厂有限公司 | Path planning method of motor crane robot |
| WO2012173496A1 (en) * | 2011-06-14 | 2012-12-20 | Crown Equipment Limited | Method and apparatus for facilitating map data processing for industrial vehicle navigation |
| US20130054129A1 (en) * | 2011-08-26 | 2013-02-28 | INRO Technologies Limited | Method and apparatus for using unique landmarks to locate industrial vehicles at start-up |
| CN102542361A (en) * | 2012-01-11 | 2012-07-04 | 中联重科股份有限公司 | Method for planning path of lift object for crane |
| CN103017757A (en) * | 2012-12-06 | 2013-04-03 | 中联重科股份有限公司 | Engineering machinery entering path planning method and path planning apparatus |
Non-Patent Citations (1)
| Title |
|---|
| 林远山等: "移动式起重机吊装路径规划仿真平台设计", 《计算机工程与应用》 * |
Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104484510A (en) * | 2014-11-28 | 2015-04-01 | 大连理工大学 | Novel hoisting action planning method for crane |
| CN104484510B (en) * | 2014-11-28 | 2017-06-23 | 大连理工大学 | A kind of new crane hanging component action planning method |
| CN105469445A (en) * | 2015-12-08 | 2016-04-06 | 电子科技大学 | Step size changeable map generation method |
| CN105469445B (en) * | 2015-12-08 | 2018-06-29 | 电子科技大学 | A kind of step-length changeably drawing generating method |
| CN106966298A (en) * | 2017-04-17 | 2017-07-21 | 山东建筑大学 | The intelligent hanging method of assembled architecture based on machine vision and system |
| CN106966298B (en) * | 2017-04-17 | 2018-08-14 | 山东建筑大学 | Assembled architecture intelligence hanging method based on machine vision and system |
| CN108415383A (en) * | 2018-02-28 | 2018-08-17 | 上海士翌测试技术有限公司 | Driving intellectualizing system based on Internet of Things |
| CN112069698B (en) * | 2020-09-27 | 2024-04-19 | 中国化学工程第六建设有限公司 | BIM-based hoisting simulation construction method and system |
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| CN103278153B (en) | 2016-01-13 |
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