CN103278153B - A kind of truck-mounted crane three-dimensional path planning method mapped based on space two-dimensional - Google Patents
A kind of truck-mounted crane three-dimensional path planning method mapped based on space two-dimensional Download PDFInfo
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Abstract
The invention discloses a kind of truck-mounted crane three-dimensional path planning method mapped based on space two-dimensional, for the three-dimensional path planning problem of truck-mounted crane, three dimensions is converted into the two-dimensional map with elevation information, and designs corresponding searching algorithm and rollback strategy on this basis.The present invention is that the three-dimensional path planning problem of truck-mounted crane proposes a kind of effective resolving ideas, improves the security of lifting operation.
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 mapped based on space two-dimensional.
Background technology
Crane path planning, as the core content of Hoisting Program, is the key ensureing Hoisting Security, and accurately effective path planning directly has influence on security and the efficiency of operation.But the complicated and device-restrictive of lifting environment makes artificial planning efficiency and performs accuracy all lower.Therefore, in order to improve lifting efficiency, saving labour, being necessary to study path planning, automatically generate an executable optimization crane operation sequence.
Although truck-mounted crane can use for reference the paths planning method of mobile robot, also have the feature of oneself, planning is decomposed into following two stages by traditional crane paths planning method:
1) in the formulation stage of Hoisting Program, verify with the key operations obtaining crane occurring that dangerous discrete critical path point carries out checking with the CAD software of routine;
2) in the execute phase of Hoisting Program, by senior slip-stick artist rely on rich experience subjectively to command with the discrete key point of polishing between path.
But there is following problem in classic method:
1) cause the analysis of key point by the restriction of CAD design software self and choose comprehensive not;
2) subjective judgement that the path planning between key point depends on commanding is relatively more serious, is difficult to ensure security;
3) planing method in whole path not system, is difficult to the fullpath that formation one is optimized.
By researching and analysing various planing method, very ripe for the paths planning method under environment known case, and also have more research for the path planning algorithm of crane, but the execution time of these path planning algorithms is large compared with long or required storage area, and do not consider the feature of truck-mounted crane self, therefore need carry out the design of introductory path planning algorithm for truck-mounted crane.
Summary of the invention
Technical matters to be solved by this invention is, not enough for prior art, there is provided a kind of truck-mounted crane three-dimensional path planning method mapped based on space two-dimensional, the three-dimensional path planning problem for truck-mounted crane proposes a kind of effective resolving ideas, 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 mapped based on space two-dimensional, and the method is:
1) to the initialization of lifting two-dimensional map, lifting initial point and aiming spot is determined; Determine that the threshold value HeightValue of each discrete point height is the variable phase angle sine value that truck-mounted crane total arm length is multiplied by Car Crane Retractable Arms; Wherein discrete point height refers to the height on discrete point distance ground;
2) initial point is labeled as current point;
3) judge whether current point periphery 4 discrete points can arrive, and how all can not arrive, then judge that this point is dead point, if so, then enter 11); Otherwise mark all can the point of arrival, enter 4);
4) the angle of revolution θ of current point position is judged
initial 1with change angle θ
initial 2and the angle of revolution θ of impact point position
target 1with change angle θ
target 2magnitude relationship, what arrange current point periphery 4 discrete points according to following table chooses priority, wherein 1 representative is the highest, 4 represent minimum, left revolution represents current point and to turn left the discrete point obtained, right-hand rotation represents current when turning right the discrete point obtained, and amplitude increase represents current point and moves toward amplitude increase direction the discrete point obtained, and amplitude reduces to represent current point and moves toward amplitude reduction direction the discrete point obtained;
5) obtaining priority level is the discrete point of 1, judges that highly whether this point exceedes threshold value HeightValue, if do not exceeded, then this discrete point is set to Search Results point, and add in routing table, turn to 8); Otherwise, enter 6);
6) check that priority is the discrete point height of 2, judge that highly whether this point exceedes threshold value HeightValue, if do not exceeded, then this discrete point is set to Search Results point, and add in routing table, turn to 8); Otherwise, check priority be 3 discrete point height whether exceed threshold value HeightValue, if priority 3 discrete point height does not exceed threshold value HeightValue, then this discrete point is set to Search Results point, and add in routing table, turn to 8); Otherwise, check that priority is the discrete point of 4, if the discrete point height of priority 4 does not exceed threshold value HeightValue, then this discrete point be set to Search Results point, and add in routing table, turn to 8); Otherwise enter 7);
7) if the discrete point height that priority is 2,3,4 all exceedes described threshold value, be then that the discrete point of 1 is set to Search Results point by priority, and add in routing table;
8) described current point is labeled as " in the paths ", 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 so, press search order export the Search Results point in routing table, turn to 11); If not, 3 are returned);
10) judge the current state of 4 discrete points around new current point be whether can not arrive or Already in in routing table, if around the state of 4 discrete points is any one in above two kinds, around so new current point, 4 discrete points all can not be selected, marking this point is dead point, return back to current point new in routing table a upper discrete point on, a upper discrete point of new current point is labeled as current point, returns 3);
11) terminate.
Compared with prior art, the beneficial effect that the present invention has is: three dimensions is converted into the two-dimensional map with elevation information by the present invention, and designs corresponding searching algorithm on this basis; The present invention is that the three-dimensional path planning problem of truck-mounted crane proposes a kind of effective resolving ideas, improves the security of lifting operation.
Accompanying drawing explanation
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 schematic diagram;
Fig. 3 is one embodiment of the invention truck-mounted crane polar coordinates schematic diagram;
Fig. 4 is one embodiment of the invention truck-mounted crane polar coordinate system discrete point schematic diagram;
Fig. 5 is one embodiment of the invention route searching strategy schematic diagram;
Fig. 6 is one embodiment of the invention simulation result schematic diagram.
Embodiment
As shown in Figure 1, be one embodiment of the invention method flow diagram.
Truck-mounted crane three-dimensional working space describes:
Truck-mounted crane path planning problem refers in the work environment, finds a path from given position to target location.Path planning algorithm is divided into spatial division and searching algorithm two parts.For the action feature of truck-mounted crane, herein crane job space is analyzed, set up heavy-duty machine working space coordinate system, and space object is described, three-dimensional for crane working space two-dimensional map is described, thus realizes three-dimensional working space division.
Three-dimensional establishment of coordinate system:
Truck-mounted crane elemental motion be mainly hoist, turn round, luffing and flexible, in the actual hoisting process of truck-mounted crane, according to actual process and operation, setting is following to be supposed:
(1) because truck-mounted crane position in hoisting process remains constant, therefore suppose that the length of arm keeps initial state constant.
(2) due to truck-mounted crane brachium once setting, substantially remain unchanged, therefore suppose crane in course of action, do not include expanding-contracting action, only have 3 elemental motions: hoist, turn round and luffing operation.
(3) amplitude of fluctuation of restricting in hoisting process is little, therefore supposes that lifting rope keeps vertical state always.
According to hypothesis 1 and 2, gib arm of crane end track is all the time on first sphere taking brachium as radius, as shown in Figure 2, and any point coordinate such as A point coordinate is (R*cos θ 2*cos θ 1, R*cos θ 2*sin θ 1, R*sin θ 2) on sphere, wherein R is radius, immobilize, the coordinate so sphere put is only relevant with these two angles of change angle θ 2 and angle of revolution θ 1, and θ 1 and θ 2 uniquely determines umbilical point.According to this feature, be vertically mapped in xoz plane by the point on sphere, and be coordinate center with the centre of sphere, set up polar coordinate system, the coordinate of polar coordinate system mid point represents, as shown in Fig. 2 .2 with change angle θ 2 and angle of revolution θ 1.Through mapping and polar coordinate system foundation, so on sphere, point just can replace with polar coordinate system mid point, as A in Fig. 2 .2, and B, namely represent A and the B point on sphere.
Feasible zone due to arm end track is first sphere whole in Fig. 2, and after vertically mapping, the feasible zone of track is whole circle in Fig. 3.Therefore, under polar coordinates, the track feasible zone of arm end can use following set expression:
S={X(θ2,θ1)|0°<=θ1<=360°,0°<=θ2<=90°}。
In addition, according to hypothesis 3, hanging object and arm end are on same vertical curve, therefore, the x coordinate of suspended object is identical with the coordinate of arm end with z coordinate, suppose suspended object a certain position M immediately below A point in fig. 2, impact point is at a certain position N in B point below, so, suspended object will from M to N point, arm end position is inevitable from A point to B point, be exactly A to B under being reflected to polar coordinate system, as can be seen here, the three-dimensional path planning of suspended object be realized, the path planning requirement of arm end position under polar coordinates must be met.But, the path planning only meeting arm end is inadequate, this is because suspended object is when carrying out three-dimensional path planning, the change of height will inevitably be produced because of object height in scene, therefore, while solution arm end path planning, also need the height problem considering object in suspended object and 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, and another part is the height change problem of suspended object.By setting up polar coordinate system and vertically mapping arm end, solve Part I problem, Part II problem will be set forth below.
The description of object scene under coordinate system:
Through the foundation of coordinate system, although the three-dimensional planning problem of lifting object to be converted into the 2D path planning problem under 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 is because the coordinate of feasible zone mid point under polar coordinate system only comprises revolution and change angle, lack the elevation information of space object in current location, for this problem, be thought of as each some X (θ 2 in feasible zone S herein, θ 1) all add the elevation information of object on this aspect, like this, while consideration 2D path planning, descending operation can be carried out to lifting object according to the elevation information that current location adds, thus solve the problem of above-mentioned Part II.
Because feasible zone S mid point is all continuity point, consider in actual hoisting process, when crane carries out revolution and luffing operation, always have the angle changing that minimum, therefore, consider the feasible region S under polar coordinates to carry out discretize according to minimum change angle herein, suppose that revolution minimum change angle is α, luffing minimum angles is β, so region is carried out dividing as shown in Figure 4, wherein, if P point is carry out revolution operation to Q point, P point is then luffing operation to M point.Using intersection point in figure as discrete point, so feasible region S1 can replace with following set:
S1={X(θ2,θ1)|0°<=θ1<=360°,0o<=θ2<=90°}
θ 1=δ α, δ is integer
θ 2=λ β, λ is integer
According to considering before, for point each in feasible zone S adds elevation information, but after discretize, whole space is then represented by discrete point set S1, therefore, the elevation information that only need add current point present position space object in each discrete point just can reach requirement.Like this, eachly discretely pointed out the angle of revolution before comprising and change angle information, further comprises elevation information, this elevation information is the maximum height of object on current discrete point.If scene object height is 5, this object covers 3 discrete points, then the height of these three discrete points is 5, if current object height exceedes arm end height, illustrates that the discrete point that this object covers is the point that can't arrive.In addition, if discrete point does not have space object, then this discrete point height is 0.By carrying out discrete to the feasible zone under polar coordinate system and adding elevation information, just can obtain the two-dimensional map with elevation information, this map can be described truck-mounted crane three-dimensional working space.
By above analysis, the two-dimensional map with height parameter under polar coordinate system is utilized to divide whole three dimensions and describe, the three-dimensional path planning problem of truck-mounted crane is just converted into 2D path planning problem, for searching algorithm design afterwards lays the foundation.
Truck-mounted crane path search algorithm:
According to above analysis, the path planning problem of truck-mounted crane to be converted on gained two-dimensional map a certain discrete point to the path planning problem of another discrete point.Path planning problem herein for the two-dimensional map with height parameter carries out searching algorithm design.
Path optimization's target:
Lifting object is being winched to the process of terminal from starting point, mulitpath may there is and meet the demands, but not necessarily optimum, therefore need design path optimization aim, carry out routing according to optimization aim.And according to reality lifting feature, the quality in path depends primarily on security and economic benefit two aspect.Wherein, security mainly relates to collision problem and overload problems, and economic benefit is conveniently mainly reflected in ease-to-operate.Only consider ease-to-operate herein, ease-to-operate will be lifted as optimization aim.
Path point selection strategy:
Because discrete point each in two-dimensional map has 4 kinds of choice directions: left revolution, right-hand rotation, amplitude increase and amplitude reduction, therefore, need to take certain path point search strategy to carry out choosing of path point.
For lifting operation the simplest path optimization target, design two kinds of routing strategies herein, one is global search strategy, and one is local searching strategy.
Global search strategy refers to the general direction of search.Specific strategy is:
(1) judge whether current point periphery 4 discrete points can reach, how all unreachable, this judges that this point is dead point, otherwise mark institute can the point of arrival.
(2) angle of revolution θ target 2 and change angle θ target 2 magnitude relationship of current location angle of revolution θ initial 1 and change angle θ initial 2 and target location is judged, what arrange current point periphery 4 discrete points shown in foundation following table 1 chooses priority, wherein 1 representative the highest, 4 represent minimum.
(3) combine attainability in (1) according to priority to judge, adjust the selection priority of each point, if high priority discrete point can not arrive, this point removes by this from priority, and the priority level lower than this priority all subtracts 1.
(4) next discrete point is selected according to priority, the result points that the point that priority is the highest exports as global search strategy.
Table 1 priority Rule of judgment
Local searching strategy is the supplementary and perfect of global search strategy.Consider situation as shown in Figure 5, wherein M is current point, B is impact point, suppose that discrete point N point is highly 10, going out M point all the other 3 discrete point height outer around N point is all 0, if according to the direction that global search strategy is fixed, route is M->N->P->B, obviously, this selection is not as M->Q->D->L-Gre atT.GreaT.GTP->B, therefore, be necessary to adopt local policy on consideration global search policy grounds.For this situation, adopt a kind of simple thresholding method herein, if the height of next discrete point that obtains of global search strategy and the height difference of current point exceed a certain threshold value HeightValue, then carry out local searching strategy.Specific strategy step is as follows:
(1) carry out global search strategy, obtaining priority level is the discrete point of 1, judges that highly whether this point meets threshold requirement, if met the demands, then this discrete point is set to Search Results point, otherwise, turn to (2);
(2) according to the priority orders recorded in global search strategy, check that priority is the discrete point height of 2, judge that highly whether this point meets threshold requirement, if met, then this discrete point is set to Search Results point, otherwise, check priority be 3 discrete point height whether satisfy condition; If priority 3 discrete point meets the demands, then this discrete point is set to Search Results point, otherwise, check that priority is the discrete point of 4; If the discrete point height of priority 4 meets the demands, then this discrete point is set to Search Results point, otherwise turns to (3).
(3) if the discrete point that priority is 2,3,4 does not all meet threshold requirement, be then that the discrete point of 1 is set to Search Results point by priority.
(4) current point is labeled as " in the paths ", and gained Search Results point is found next point as current point.
Path rollback strategy:
Due to after carrying out path point selection strategy, likely obtain such point: this point has gone out a upper discrete point around, all the other 3 points are all unreachable, or the point that obtains in the paths, such algorithm just there will be and is absorbed in dead band or endless loop, therefore, need to take path rollback strategy.
Rollback strategy is: searched for by the next discrete point obtained path point selection strategy, judge that whether the current state of 4 points around this point is can not to arrive or Already in gained path, if around the state of 4 points is all any one in above two kinds, so around this point, 4 points all can not be selected, show that this point is dead point, need to return back to in path on last discrete point.On returning back to while a discrete point, marking this point is the dead point searched for, and then continues through route searching strategy and finds next eligible point.
Herein according to above analysis result, utilize C++ to carry out path planning algorithm design, solve lifting object three-dimensional path planning problem, and analysis verification is carried out to result.
According to above theoretical analysis, for truck-mounted crane three-dimensional path planning problem, foundation and path planning algorithm two steps of the two-dimensional map being with height parameter are needed, for this 2 point, need to utilize C++ to carry out class formation design to two-dimensional map and searching algorithm, 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 with height parameter, and according to minimum angle of revolution and minimum change angle by two-dimensional map discretize, each point includes object height information in space.According to this feature, design a Mynode class herein and represent map, store two-dimensional map information, such includes the change angle of current point, angle of revolution and object height information.Again due to rollback strategy will be considered, add a variable to mark the state of current point, state has 3 kinds, is respectively to search for, search in path sequence and, therefore, such comprises three variablees: change angle, angle of revolution, height and current point state.
After map class is determined, consider and need to preserve route programming result, therefore, herein design path result storage class Node_In_Table carrys out storing path program results, and such comprises the change angle of discrete point, angle of revolution, this periphery able state of 4 up and down.
When two-dimensional map is set up, design the realization that a Quadtree_structure class carries out algorithm.Such realizes the initial work of map, path planning algorithm and result output function.Such comprises Quadtree_structure map initialization function, search route searching function and Node_In_Table store results variable.
This document assumes that current minimum angle of revolution is 6 degree, minimum change angle is also 6 degree, and so in feasible zone S1, discrete point adds up to N*M, wherein N=360/6=60, M=90/6=15, so discretely counts as S
1=60*15=900.
The initialization condition of hypothesis instance 1 is: starting point change angle is 2, and angle of revolution is also 2, and the height of starting point lifting object is 3, and the change angle of target location is 10, and angle of revolution is 10 object heights is 6.And consider that scene has object height information, arrange as carried out height by such as table 2 mode to discrete point, wherein 1500 represent this point and can not arrive, all the other discrete point height are all 0, and rational height threshold value is 7.
Table 2 some discrete point elevation information
Be brought into by initialization information in search function and obtain result as shown in Figure 6, algorithm execution time is 4.336 milliseconds, and algorithm iteration number of times is 17.
For above example, if adopt locational space describing method to divide three-dimensional working space, so according to the hypothesis in 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 current small cubes has object, then this cube attribute is set to 1, otherwise is 0, thus space initialization of finishing the work.Then, on search strategy basis described herein, for each discrete point increases upper and lower two directions of search of lifting object, utilize searching algorithm to search for initialization condition identical in example 1, obtain three-dimensional search path as follows,
(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 each point three coordinates represent angle of revolution respectively, and change angle and height, search time is 6.959 milliseconds, iterations 20 times.
In example 1, utilize space-division method herein, three dimensions is carried out two-dimensional map, then runs according to search strategy of the present invention, just forward the right discrete point (2,3) to from (2,2) according to the known discrete point of local searching strategy; Then because (3,3) point does not highly exceed threshold value, just undertaken by global search strategy, exceed again threshold value to (4,3) point, then press local searching strategy and select (3,4); Then because (6,4) surrounding 3 all can not arrive, therefore (6,4) are dead points, adopt rollback strategy, turn to (5,5) from (5,4), and routing meets search strategy herein equally afterwards.
In addition, example 1 and example 2 are carried out such as showing shown in 4-2 from algorithm execution time, iterations and storage area.Example 1 adopts two-dimensional map map partitioning method herein, and example 2 is conventional three dimensions division methods.Both greatly reduce the known algorithm storage area in this paper of contrast, and search time and iteration reduce, and reach the object of the three-dimensional path planning complicacy reducing truck-mounted crane.
Table 3 example 1 and example 2 contrast
Claims (1)
1., based on the truck-mounted crane three-dimensional path planning method that space two-dimensional maps, it is characterized in that, the method is:
1) to the initialization of lifting two-dimensional map, determine lifting initial point and aiming spot, determine that the threshold value HeightValue of each discrete point height is the variable phase angle sine value that truck-mounted crane total arm length is multiplied by Car Crane Retractable Arms; Wherein discrete point height refers to the height on discrete point distance ground;
2) initial point is labeled as current point;
3) judge whether current point periphery 4 discrete points can arrive, if all can not arrive, then judge that this point is dead point, if so, then enter 11); Otherwise mark all can the point of arrival, enter 4);
4) the angle of revolution θ of current point position is judged
initial 1with change angle θ
initial 2and the angle of revolution θ of impact point position
target 1with change angle θ
target 2magnitude relationship, what arrange current point periphery 4 discrete points according to following table chooses priority, wherein 1 representative is the highest, 4 represent minimum, left revolution represents current point and to turn left the discrete point obtained, right-hand rotation represents current when turning right the discrete point obtained, and amplitude increase represents current point and moves toward amplitude increase direction the discrete point obtained, and amplitude reduces to represent current point and moves toward amplitude reduction direction the discrete point obtained;
5) obtaining priority level is the discrete point of 1, judges that highly whether this point exceedes threshold value HeightValue, if do not exceeded, then this discrete point is set to Search Results point, and add in routing table, turn to 8); Otherwise, enter 6);
6) check that priority is the discrete point height of 2, judge that highly whether this point exceedes threshold value HeightValue, if do not exceeded, then this discrete point is set to Search Results point, and add in routing table, turn to 8); Otherwise, check priority be 3 discrete point height whether exceed threshold value HeightValue, if priority 3 discrete point height does not exceed threshold value HeightValue, then this discrete point is set to Search Results point, and add in routing table, turn to 8); Otherwise, check that priority is the discrete point of 4, if the discrete point height of priority 4 does not exceed threshold value HeightValue, then this discrete point be set to Search Results point, and add in routing table, turn to 8); Otherwise enter 7);
7) if the discrete point height that priority is 2,3,4 all exceedes described threshold value, be then that the discrete point of 1 is set to Search Results point by priority, and add in routing table;
8) described current point is labeled as " in the paths ", 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 so, press search order export the Search Results point in routing table, turn to 11); If not, 10 are turned to);
10) judge the current state of 4 discrete points around new current point be whether can not arrive or Already in in routing table, if around the state of 4 discrete points is any one in above two kinds, around so new current point, 4 discrete points all can not be selected, marking this point is dead point, return back to current point new in routing table a upper discrete point on, a upper discrete point of new current point is labeled as current point, returns 3);
11) terminate.
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| CN104484510B (en) * | 2014-11-28 | 2017-06-23 | 大连理工大学 | A kind of new crane hanging component action planning method |
| CN105469445B (en) * | 2015-12-08 | 2018-06-29 | 电子科技大学 | A kind of step-length changeably drawing generating method |
| 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 |
| JP2022535503A (en) * | 2019-06-14 | 2022-08-09 | バイエリシエ・モトーレンウエルケ・アクチエンゲゼルシヤフト | Road model manifold for 2D trajectory planning |
| 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 |
| CN118293923B (en) * | 2024-06-04 | 2024-08-16 | 中建科工集团有限公司 | Double-machine lifting safety path planning method, device, equipment and storage medium |
Citations (4)
| 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 | Crane hoisting object path planning method |
| WO2012173496A1 (en) * | 2011-06-14 | 2012-12-20 | Crown Equipment Limited | Method and apparatus for facilitating map data processing for industrial vehicle navigation |
| CN103017757A (en) * | 2012-12-06 | 2013-04-03 | 中联重科股份有限公司 | Engineering machinery entry path planning method and path planning device |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| 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 |
-
2013
- 2013-04-27 CN CN201310152931.9A patent/CN103278153B/en not_active Expired - Fee Related
Patent Citations (4)
| 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 |
| CN102542361A (en) * | 2012-01-11 | 2012-07-04 | 中联重科股份有限公司 | Crane hoisting object path planning method |
| CN103017757A (en) * | 2012-12-06 | 2013-04-03 | 中联重科股份有限公司 | Engineering machinery entry path planning method and path planning device |
Non-Patent Citations (1)
| Title |
|---|
| 移动式起重机吊装路径规划仿真平台设计;林远山等;《计算机工程与应用》;20121231;第48卷(第24期);全文 * |
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