CN114035513A - S-shaped speed curve look-ahead planning method and device, storage medium and computing device - Google Patents
S-shaped speed curve look-ahead planning method and device, storage medium and computing device Download PDFInfo
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- CN114035513A CN114035513A CN202111145153.1A CN202111145153A CN114035513A CN 114035513 A CN114035513 A CN 114035513A CN 202111145153 A CN202111145153 A CN 202111145153A CN 114035513 A CN114035513 A CN 114035513A
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B19/00—Programme-control systems
- G05B19/02—Programme-control systems electric
- G05B19/18—Numerical control [NC], i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form
- G05B19/416—Numerical control [NC], i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form characterised by control of velocity, acceleration or deceleration
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- G—PHYSICS
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- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B2219/00—Program-control systems
- G05B2219/30—Nc systems
- G05B2219/34—Director, elements to supervisory
- G05B2219/34119—Function generator, filter after interpolator to control position error
Abstract
The invention discloses a S-shaped speed curve look-ahead planning method and a device, which are used for solving the problem of large calculation amount of planning C ^2 continuous speed curves. Scanning a motion track to establish an S-shaped curve and storing the S-shaped curve in a linked list; marking nodes which cannot be independently programmed in an S shape in each node in the first state of the linked list as a second state; storing the speed deviation value of each node in the second state in the linked list in a deviation table; combining the nodes in the deviation table, and inserting the combined nodes which cannot be independently subjected to S-shaped planning into the deviation table again to perform adjacent node combination again until the deviation table is empty; carrying out time-optimal speed planning on the nodes in the linked list; splitting nodes which do not meet preset motion constraints in a linked list into two nodes, and performing S-shaped planning; carrying out endpoint speed reduction on the nodes which cannot be subjected to S-shaped planning after splitting; and splitting the node whose speed is reduced by the endpoint, and repeatedly executing the steps until the nodes in the linked list meet the preset motion constraint.
Description
Technical Field
The invention belongs to the technical field of computers, and particularly relates to a S-shaped speed curve look-ahead planning method and device, a storage medium and computing equipment.
Background
The feeding speed of the numerical control machine tool has a close relation with the processing precision, the productivity and the surface roughness of the workpiece. The existing popular acceleration and deceleration control is S-shaped acceleration and deceleration control, and compared with trapezoidal acceleration and deceleration and exponential acceleration and deceleration control, the S-shaped acceleration and deceleration control has the advantages of smooth and uniform speed curve, stable motion, no impact and the like.
The speed curve generally refers to a corresponding curve f ═ V (t) in a coordinate system with time t as the horizontal axis and speed V as the vertical axis, with the first derivative being the acceleration (Acc) f ═ a (t), the second derivative being the Jerk (Jerk) f ═ j (t), and the third derivative being the Jerk (Jounce or Snap) f ″ = s (t), if they are derivable.
The algebraic polynomial is used as a speed curve and can be based on the bang-bang control principle so as to achieve time optimization. The acceleration curve has C0 order continuity, is a trapezoidal acceleration and deceleration curve, and has three step states of acceleration (+ Acc, 0-Acc); having C1 continuous, which is known in the art as a sigmoid velocity curve, means that the acceleration can be continuous, but the plus acceleration step is not continuous, and can be divided into 7 stages at most. And the acceleration is continuous, the acceleration can be controlled, and the C2-order continuous speed curve can be obtained by other speed curves, but the other speed curves can partially reach the C2 continuous speed curve, but the acceleration is usually realized by a trigonometric function, so that the defects of large interpolation calculation amount, influence on real-time performance, non-time optimal control, influence on processing efficiency and the like exist.
The information disclosed in this background section is only for enhancement of understanding of the general background of the invention and should not be taken as an acknowledgement or any form of suggestion that this information forms the prior art already known to a person skilled in the art.
Disclosure of Invention
The invention aims to provide a S-shaped speed curve look-ahead planning method which is used for solving the problems that the existing planning C ^2 continuous speed curve is large in calculation amount and affects real-time performance.
In order to achieve the above object, the present invention provides a S-shaped velocity curve look-ahead planning method, which comprises:
scanning a plurality of motion tracks to correspondingly establish a plurality of S-shaped curves, and storing the S-shaped curves in a linked list, wherein corresponding nodes of the S-shaped curves marked in the linked list are in a first state;
marking nodes which cannot be independently subjected to S-shaped planning in all nodes in the first state of the linked list as second states;
calculating the speed deviation value of each node of the second state in the linked list, and storing the speed deviation values in a deviation table according to the size in sequence;
selecting a corresponding node with the maximum speed deviation value in the deviation table to be combined with an adjacent node, and inserting the combined node which cannot be independently subjected to S-shaped planning into the deviation table again to perform adjacent node combination again until the deviation table is empty;
performing time-optimal speed planning on each node capable of performing independent S-shaped planning in the linked list;
splitting the nodes which do not meet the preset motion constraint in the linked list into two nodes, and performing S-shaped planning on the split nodes;
carrying out endpoint speed reduction on the split node which cannot be subjected to S-shaped planning so as to enable the length of the shortest path required by the node from the low speed acceleration of the corresponding motion track to the endpoint speed after speed reduction to be equal to the length of the motion path of the S-shaped curve;
and splitting the node decelerated by the endpoint into nodes only containing single-segment motion tracks, and repeatedly executing the steps until the nodes in the linked list meet preset motion constraints so as to finish S-shaped speed curve planning of the plurality of segments of motion tracks.
In an embodiment, scanning a plurality of motion trajectories to correspondingly establish a plurality of S-shaped curves includes:
scanning from the last section to the first section, initializing the starting point speed of each section of motion track to the maximum allowable joining speed, initializing the end point speed to the starting point speed of the adjacent section at the corresponding joining point, and recording the path length of each section of motion track;
scanning from the first segment to the last segment, and establishing an S-shaped curve for each segment of motion track.
In an embodiment, marking, as the second state, a node that cannot be independently S-shaped programmed among the nodes in the first state of the linked list specifically includes:
judging whether the length of the shortest path required from low speed acceleration to high speed of the corresponding motion track is not greater than the length of the motion path of the corresponding S-shaped curve or not at each node of the first state in the linked list, wherein the low speed and the high speed of the motion track are obtained according to the speeds of two end points for sequencing the motion track; if so,
the corresponding node in the linked list is marked as the second state.
In an embodiment, calculating the speed deviation value of each node in the second state in the linked list specifically includes:
carrying out high-speed endpoint speed reduction on each node in the second state in the linked list, so that the length of the shortest path required by the node from the low speed acceleration of the corresponding motion track to the speed of the endpoint after speed reduction is equal to the length of the motion path of the S-shaped curve;
and calculating the difference value between the high speed of the corresponding motion track and the speed of the endpoint after the speed reduction in each node of the second state in the linked list to obtain a speed deviation value.
In one embodiment, selecting a corresponding node with the largest speed deviation value in the deviation table to merge with an adjacent node, and reinserting the merged node that cannot be independently programmed in an S shape into the deviation table to perform merging of the adjacent node again until the deviation table is empty specifically includes:
selecting a corresponding node with the maximum speed deviation value in the deviation table, and combining the node with an adjacent node by taking a high-speed endpoint of the node as a joint point, wherein the maximum speed value of the combined node is a lower value of node constraint before combination; and/or the presence of a gas in the gas,
when merging, inquiring whether the two nodes before merging are in a second state; if so,
the merged two nodes are removed from the deviation table.
In an embodiment, performing time-optimal speed planning on each node capable of performing independent S-shaped planning in the linked list specifically includes:
calculating the d value of each node of the independent S-shaped plan in the linked list:
d＝L-L(Vs,Vmax)-L(Ve,Vmax)
wherein L is the corresponding moving rail of nodePath length of trace, L (V)s,Vmax) Starting point velocity V of motion track corresponding to nodesAccelerating to the maximum speed V allowedmaxRequired shortest path length, L (V)e,Vmax) Endpoint velocity V of motion trajectory for nodeeAccelerating to the maximum speed V allowedmaxThe required shortest path length;
judging whether the d value of each node is greater than or equal to 0; if so,
determining that a uniform velocity segment exists and completing S-shaped planning of the corresponding node; if not, the user can not select the specific application,
the optimum speed V is determinedbest∈[max{Vs,Ve},Vmax]So that the objective function f (V) of the corresponding nodebest)＝L-L(Vs,Vbest)-L(Ve,Vbest) Equal to 0 and the S-shaped planning of the corresponding node is completed.
In an embodiment, splitting a node that does not satisfy a preset motion constraint in the linked list into two nodes specifically includes:
calculating the corresponding speed on the S-shaped programming speed curve by the merging nodes in the linked list according to the length of each motion track;
determining whether the corresponding speed is not greater than a speed allowed by a point of engagement therewith; if not, the user can not select the specific application,
splitting the corresponding merged node into two nodes at the position where the speed of the connecting point is maximum.
The invention also provides a S-shaped speed curve look-ahead planning device, which comprises:
the scanning module is used for scanning a plurality of sections of motion tracks to correspondingly establish a plurality of S-shaped curves and storing the S-shaped curves in a linked list, wherein corresponding nodes of the S-shaped curves marked in the linked list are in a first state;
the marking module is used for marking the nodes which cannot be independently subjected to S-shaped planning in all the nodes in the first state of the linked list as a second state;
the calculation module is used for calculating the speed deviation value of each node in the second state in the linked list and storing the speed deviation values in the deviation table according to the size in sequence;
the merging module is used for selecting the corresponding node with the maximum speed deviation value in the deviation table to merge with the adjacent nodes, and reinserting the merged nodes which cannot be independently subjected to S-shaped planning into the deviation table to perform merging of the adjacent nodes again until the deviation table is empty;
the planning module is used for carrying out time-optimal speed planning on each node which can be independently planned in an S shape in the linked list;
the splitting module is used for splitting the nodes which do not meet the preset motion constraint in the linked list into two nodes and performing S-shaped planning on the split nodes;
the speed regulating module is used for carrying out endpoint speed reduction on the split node which cannot be subjected to S-shaped planning so as to enable the length of the shortest path required by the node to be equal to the length of the motion path of the S-shaped curve when the node is accelerated from the low speed of the corresponding motion track to the endpoint speed after speed reduction;
the splitting module is further configured to split the node whose speed is reduced by the endpoint into nodes that only include a single-segment motion trajectory, and repeat the above steps until all nodes in the linked list satisfy a preset motion constraint, so as to complete S-shaped speed curve planning of the plurality of segments of motion trajectories.
The present invention also provides a computing device comprising:
at least one processor; and
a memory storing instructions that, when executed by the at least one processor, cause the at least one processor to perform the method as described above.
The invention also provides a machine-readable storage medium having stored thereon executable instructions that, when executed, cause the machine to perform the method as described above.
Compared with the prior art, according to the S-shaped speed curve forward-looking planning method, C ^2 continuous can be obtained, namely, the speed, the acceleration and the acceleration are continuous and limited, the acceleration step is added but limited, 15 curve stage stages can be obtained at most, the obtained speed curve is smoother, and the motion is more stable; in an actual application scene, 2048 or even more continuous paths can be subjected to rapid prospective planning, the real-time performance is not influenced even on an ARM platform with relatively weak calculation power, and the method has obvious advantages in high-speed and high-precision machining.
Drawings
FIG. 1 is a diagram of a logic architecture according to one embodiment of a S-shaped velocity curve look-ahead planning method of the present invention;
FIG. 2 is a flow diagram of one embodiment of a S-shaped velocity profile look-ahead planning method according to the present invention;
FIG. 3 is a block diagram of an embodiment of a S-shaped look-ahead apparatus for velocity profiles in accordance with the present invention;
FIG. 4 is a hardware block diagram of one embodiment of a sigmoid velocity curve look-ahead planning computing device according to the present invention.
Detailed Description
The following detailed description of the present invention is provided in conjunction with the accompanying drawings, but it should be understood that the scope of the present invention is not limited to the specific embodiments.
Throughout the specification and claims, unless explicitly stated otherwise, the word "comprise", or variations such as "comprises" or "comprising", will be understood to imply the inclusion of a stated element or component but not the exclusion of any other element or component.
The S-shaped speed curve plan of the invention is a plan for determining a motion track for a plurality of segments (k is 1,2, …, n). Setting the maximum speed V allowed by the systemmaxMaximum acceleration AmaxMaximum jerk JmaxMaximum jerk SmaxMaximum allowable bow height error epsilon, interpolation period T0. The goal of the planning is to perform a velocity look-ahead planning of these motion trajectories so that they satisfy the velocity curve C ^2 continuation.
Referring to fig. 1, motion constraints can be set for each motion trajectory, and the motion constraint parameters are combined into
And, can also set up
Where ρ is the minimum curvature radius of the motion trajectory to ensure that the interpolated trajectory does not exceed the bow-height error ε.
For the starting point of the first segment motion track and the ending point of the last segment motion track, corresponding motion parameters can be set
And
is fixed. Wherein the initial velocity of the first motion track
Except for the allowed non-0, all the others should be 0. Here, the initial velocity
If not 0, it is generally used for scroll planning, that is, the previous planning interpolation outputs a part, and the speed can be reduced to 0 at a designated point, and the current planning end point position is further backward, so that the deceleration to the stop state can be ensured, and the overshoot phenomenon does not occur.
When k is larger than 1, at the joint of the starting points of the motion tracks, motion constraint parameters can be further set. Specifically, the deflection angle of the tangent line of the previous motion track at the connecting point is defined as theta, and the vector of the tangent line of the previous motion track at the end point is defined as
The tangent vector of the starting point of the current motion track is
Then can pass through
Or
And calculating to obtain the deflection angle. At this juncture, assuming the direction deflection is completed within one instruction cycle, the direction of the instruction is changed by
Obtaining the starting point speed of the motion track
In the same way, can obtain
For the engagement speed, the bow height error is further constrained, and the result is:
for the motion constraint parameters at the end positions of the motion tracks of all the segments, except for the motion constraint parameters of the last segment
All of which can be zero or other motion tracks
I.e. equal to the starting point constraint of the next motion trajectory.
The above is the process of setting the overall constraint and speed limit (determining the speed sensitive area and the motion parameter upper limit allowed in each area) of the system, and a specific embodiment of the S-shaped speed curve look-ahead planning method of the present invention is described with reference to fig. 1 and 2 on the basis of the above setting. In this embodiment, the method comprises:
and S11, scanning a plurality of motion tracks to correspondingly establish a plurality of S-shaped curves, and storing the S-shaped curves in a linked list.
The scanning here corresponds to the process of initialization. Specifically, the scanning may be performed from the last segment to the first segment of the plurality of segments of curves, and the starting point speed of each segment of the motion trajectory is initialized to the maximum allowable joining speed, the ending point speed is initialized to the starting point speed of the adjacent segment at the corresponding joining point, and the path length of each segment of the motion trajectory is recorded; then, scanning from the first segment to the last segment, and establishing an S-shaped curve for each segment of motion track.
The established S-shaped curves are stored in a linked list form, and corresponding nodes of the S-shaped curves are marked to be in a first state INIT.
And S12, marking the nodes which can not be independently S-shaped planned in each node of the first state of the linked list as a second state.
This corresponds to the process of whether the heuristic can be S-shaped planning. Specifically, first, the current sigmoid planning constraint (A) may be appliedmax,Jmax,Smax) Sorting the two end point speeds corresponding to the motion trail from a low speed VlowTo high speed VhighAnd making the starting acceleration and the stopping acceleration both be 0, and planning out a speed curve with optimal time so as to obtain the low-speed VlowSpeeding up to high speed VhighRequired shortest path length L (V)low,Vhigh)。
Then, the shortest path length L (V) is determinedlow,Vhigh) Whether the motion path length L is not more than the motion path length L of the corresponding S-shaped curve; if yes, marking the corresponding node in the linked list as the state TRY _ PASS; if not, the corresponding node in the linked list can be marked as the second state TRY _ FAIL.
And S13, calculating the speed deviation value of each node in the second state in the linked list, and storing the speed deviation values in a deviation table according to the sizes in sequence.
Specifically, the speed reduction of the high-speed end point may be performed on each node in the second state in the linked list, so that the length of the shortest path required when the node is accelerated from the low speed corresponding to the motion trajectory to the speed of the end point after speed reduction is equal to the length of the motion path of the S-shaped curve, and then the difference between the high speed corresponding to the motion trajectory and the speed of the end point after speed reduction in each node in the second state in the linked list is calculated, so as to obtain the speed deviation value.
A kind of entityIn the embodiment, the low speed and the high speed (V) can be obtained by an iterative algorithmlow,Vhigh) A certain proper speed V in betweentryTo make it from low speed VlowSpeeding up to VtryRequired shortest path length L (V)low,Vtry) Exactly equal to the path length L of the motion corresponding to the sigmoid curve, let Δ V equal Vhigh- VtryAnd recording the speed deviation value of the non-S-shaped speed planning node into a deviation table. The deviation table can always sort the deviation values from large to small, and link the node information of the linked list as the basis for dynamically combining the sequence in the next step.
And S14, selecting the corresponding node with the maximum speed deviation value in the deviation table to be combined with the adjacent node, and inserting the combined node which cannot be independently subjected to S-shaped planning into the deviation table again to perform adjacent node combination again until the deviation table is empty.
If the deviation table itself is empty, it means that the second linked list starts, i.e. there is no node in the second state TRY _ FAIL (node that cannot be S-shaped speed planning). If the deviation table is not empty, it indicates that the second linked list has the node in the second state TRY _ FAIL, and the above-mentioned process of obtaining the deviation table through speed reduction in step S13 is the basis for node merging to convert the node in the second state TRY _ FAIL in the linked list into the state TRY _ PASS.
Specifically, the corresponding node with the largest speed deviation value in the deviation table may be selected, and the high speed endpoint thereof is taken as the connection point to be merged with the adjacent node. The path length of the new node after combination is the sum of the path lengths of the two nodes before combination; the starting and stopping endpoint speed is the starting and stopping endpoint speed of the two nodes before merging; it (V)max,Amax,Jmax,Smax) Respectively taking the lower values of the original two node constraints and combining the latter three variables (A)max,Jmax,Smax) Further adjustment is made to meet the motion constraint at the splice point (as the splice point translates from the endpoint into the new sigmoid curve segment). It should be noted that the maximum speed V of the S-shape of the new node is nowmaxCan be temporarily independent of the velocity of the splice point, otherwise the overall velocity can be severely reduced,if the location is out of specification, the location is checked and specified in a later step.
When merging, whether two nodes before merging are in the second state TRY _ FAIL should be inquired firstly; and if so, deleting the two merged nodes from the deviation table. If the merged node can be independently S-shaped planned, the "heuristic" process in step S12 may be invoked, and if the state corresponds to the state TRY _ PASS, it indicates that the merged node can be independently S-shaped planned; if the state corresponds to the second state TRY _ FAIL, it indicates that the merged node still cannot be independently S-shaped programmed, and the velocity deviation value needs to be calculated again and can be inserted into the appropriate position in the deviation table again according to the size sorting.
It can be seen that by successively combining two nodes in the deviation table and combining the dynamic update of the deviation table, the dynamic combination of the nodes which cannot be subjected to S-shaped planning can be realized until the deviation table is emptied.
And S15, performing time-optimal speed planning on each node capable of being independently planned in the S shape in the linked list.
Here corresponds to the construction process, and the nodes in the deviation table correspond to the state TRY PASS. Specifically, it is assumed that each node in the linked list that can be independently S-shaped programmed can reach the maximum speed VmaxAnd calculating the d value:
d＝L-L(Vs,Vmax)-L(Ve,Vmax)
wherein L is the length of the motion path of the motion trail corresponding to the node, L (V)s,Vmax) Starting point velocity V of motion track corresponding to nodesAccelerating to the maximum speed V allowedmaxRequired shortest path length, L (V)e,Vmax) Endpoint velocity V of motion trajectory for nodeeAccelerating to the maximum speed V allowedmaxThe required shortest path length. Wherein, L (V)s,Vmax) And L (V)e,Vmax) The algorithm can be realized by the same module, and the algorithm does not relate to special technology, so the details are not described herein.
Secondly, judging whether the d value of each node is more than or equal to 0; if yes, determining that the constant-speed section exists and completing S-shaped planning of the corresponding node; if not, determining that the constant speed section does not exist.
Under the condition that the constant speed section does not exist, the node state is TRY _ PASS, and the optimal speed V is continuously determinedbest∈[max{Vs,Ve},Vmax]So that the objective function f (V) of the corresponding nodebest)＝L- L(Vs,Vbest)-L(Ve,Vbest) Equal to 0 and the S-shaped planning of the corresponding node is completed. The specific process of determining the optimal speed may be implemented, for example, by a newton's iterative algorithm.
For nodes that have completed the sigmoid programming, it may be marked as state MADE.
And S16, splitting the nodes which do not meet the preset motion constraint in the linked list into two nodes, and performing S-shaped planning on the split nodes.
Before splitting the nodes, the nodes in the state MADE in the linked list are checked. If the node itself is single-segment motion trajectory, it has satisfied all motion constraints and can be further labeled as state CHECK _ PASS; if the node is combined by multiple motion tracks, then as mentioned above, it needs to be further determined whether the speed of the joint point between the internal motion tracks meets the motion constraint.
In one embodiment, the merging nodes in the linked list may sequentially calculate the corresponding speed on the S-shaped programming speed curve according to the length of each motion track; simultaneously determining whether the corresponding speed is not greater than the speed allowed by the joint point; if not, the speed of the join point is over-limit, the join point is marked as a state CHECK _ FAIL, and the position with the maximum over-limit value in the merge node is recorded.
Then, the corresponding merged node may be split into two nodes at the point where the speed of the node exceeds the maximum. The split two nodes are composed of respective corresponding motion trajectories and are relabeled to be in a first state INIT.
It should be noted that in some alternative embodiments, the node splitting may be performed without performing the splitting at the position where the speed of the splicing point exceeds the maximum, and these alternative embodiments should also fall within the scope of the present invention.
And S17, performing endpoint speed reduction on the split node which cannot be subjected to S-shaped planning, so that the length of the shortest path required by the node from the low speed of the corresponding motion track to the endpoint speed after speed reduction is equal to the motion path length of the S-shaped curve.
For the split node, the "heuristic" process in step S12 may be continuously invoked, and if the correspondence is the state TRY _ PASS, it indicates that the split node can be independently S-shaped planned; if the state is the second state TRY _ FAIL, the split node still can not be independently planned in a S shape.
At this time, the endpoint speed reduction can be performed on the corresponding node, for example, by an iterative algorithm, and the endpoint high speed V can be obtainedhighAnd low speed VlowA certain speed V in betweentryLet the corresponding node go from VlowSpeeding up to VtryRequired shortest path length L (V)low,Vtry) Exactly equal to L, then force the higher end point velocity VhighDown-regulated to Vtry. It should be noted that, since this involves a joining speed, the starting and ending end point speeds of the motion trajectories of the adjacent segments at the joining point need to be adjusted at the same time, and the smaller value of the adjusted starting and ending end point speeds is taken as the new joining end point speed.
And S18, splitting the node decelerated by the endpoint into nodes only containing single-section motion tracks, and repeatedly executing the steps until the nodes in the linked list meet preset motion constraints so as to complete S-shaped speed curve planning of the plurality of sections of motion tracks.
The splitting process corresponds to the splitting process, and the node subjected to speed reduction by the endpoint is further split into the nodes only containing the single-segment motion trail, and after the state is marked as the first state INIT again, the process enters a new round of circulation to execute the steps. The split-cycle process herein allows for greater process efficiency.
And when all the nodes in the linked list meet the preset motion constraint (the state is CHECK _ PASS), the S-shaped speed curve planning of a plurality of motion tracks is finished. The programmed speed curves of the nodes in the linked list can be mapped to the corresponding motion segments for storage, and the status is marked as APPLY.
Through the S-shaped speed curve forward-looking planning method of the embodiment, C ^2 is continuous, namely, the speed, the acceleration and the acceleration are continuous and limited, the acceleration step is limited, the acceleration step can be limited, the maximum speed can be divided into 15 curve stages, the obtained speed curve is smoother, and the motion is more stable. That is, each motion segment may have 15 Stage information, and each Stage structure stores an initial velocity, an initial acceleration, an initial jerk, a jerk, and corresponding durations and path lengths, which may provide sufficient motion information for subsequent interpolation. In interpolation, the motion information and the geometric information can be combined, the motion amount in a single command period of each motion axis is calculated, and a related command is output to the equipment according to time sequence.
In general, the sigmoidal velocity profile obtained by the above embodiments is a global time-optimal solution, namely: a path of motion, possibly comprising a plurality of S-shaped stages; an S-shaped stage (C ^2 continuous S-shaped, total 15 stages) may also contain multi-stage path motion. That is, at each junction, there may be an acceleration or deceleration interval, and there is no problem that the algorithm of the prior art requires an additional limit of acceleration of 0 at the junction, thereby affecting the processing efficiency.
In an actual application scene, the S-shaped speed curve look-ahead planning method can carry out quick look-ahead planning on 2048 continuous paths, does not influence the real-time performance even on an ARM platform with relatively weak computational power, and has obvious advantages in high-speed and high-precision machining.
Referring to fig. 3, the present invention further provides a specific embodiment of the S-shaped velocity curve look-ahead planning apparatus. The S-shaped speed curve look-ahead planning device comprises a scanning module, a marking module, a calculating module, a merging module, a planning module and a speed regulating module.
The scanning module is used for scanning a plurality of sections of motion tracks to correspondingly establish a plurality of S-shaped curves and storing the S-shaped curves in a linked list, wherein corresponding nodes of the S-shaped curves marked in the linked list are in a first state;
the marking module is used for marking the nodes which cannot be independently subjected to S-shaped programming in all the nodes in the first state of the linked list as a second state;
the calculation module is used for calculating the speed deviation value of each node in the second state in the linked list and storing the speed deviation values in the deviation table according to the size in sequence;
the merging module is used for selecting the corresponding node with the maximum speed deviation value in the deviation table to merge with the adjacent nodes, and reinserting the merged nodes which cannot be independently subjected to S-shaped planning into the deviation table to perform merging of the adjacent nodes again until the deviation table is empty;
the planning module is used for carrying out time-optimal speed planning on each node which can be independently planned in an S shape in the linked list;
the splitting module is used for splitting the nodes which do not meet the preset motion constraint in the linked list into two nodes and performing S-shaped planning on the split nodes;
the speed regulating module is used for carrying out endpoint speed reduction on the split node which cannot be subjected to S-shaped planning so as to enable the length of the shortest path required by the node from the low speed of the corresponding motion track to the endpoint speed after speed reduction to be equal to the length of the motion path of the S-shaped curve;
the splitting module is further configured to split the node whose speed is reduced by the endpoint into nodes that only include a single-segment motion trajectory, and repeat the above steps until all nodes in the linked list satisfy a preset motion constraint, so as to complete S-shaped speed curve planning of the plurality of segments of motion trajectories.
The scanning module is specifically configured to: scanning from the last section to the first section, initializing the starting point speed of each section of motion track to the maximum allowable joining speed, initializing the end point speed to the starting point speed of the adjacent section at the corresponding joining point, and recording the path length of each section of motion track; scanning from the first segment to the last segment, and establishing an S-shaped curve for each segment of motion track.
The marking module is specifically configured to: judging whether the length of the shortest path required from low speed acceleration to high speed of the corresponding motion track is not greater than the length of the motion path of the corresponding S-shaped curve or not at each node of the first state in the linked list, wherein the low speed and the high speed of the motion track are obtained according to the speeds of two end points for sequencing the motion track; and if so, marking the corresponding node in the linked list as a second state.
The calculation module is specifically configured to: carrying out high-speed endpoint speed reduction on each node in the second state in the linked list, so that the length of the shortest path required by the node from the low speed acceleration of the corresponding motion track to the speed of the endpoint after speed reduction is equal to the length of the motion path of the S-shaped curve; and calculating the difference value between the high speed of the corresponding motion track and the speed of the endpoint after the speed reduction in each node of the second state in the linked list to obtain a speed deviation value.
The merging module is specifically configured to: selecting a corresponding node with the maximum speed deviation value in the deviation table, and combining the node with an adjacent node by taking a high-speed endpoint of the node as a joint point, wherein the maximum speed value of the combined node is a lower value of node constraint before combination; and/or, when merging, inquiring whether the two nodes before merging are in the second state; if yes, deleting the two merged nodes from the deviation table.
The planning module is specifically configured to: calculating the d value of each node of the independent S-shaped plan in the linked list:
d＝L-L(Vs,Vmax)-L(Ve,Vmax)
wherein L is the length of the motion path of the motion trail corresponding to the node, L (V)s,Vmax) Starting point velocity V of motion track corresponding to nodesAccelerating to the maximum speed V allowedmaxRequired shortest path length, L (V)e,Vmax) Endpoint velocity V of motion trajectory for nodeeAccelerating to the maximum speed V allowedmaxThe required shortest path length;
judging whether the d value of each node is greater than or equal to 0; if so,
determining that a uniform velocity segment exists and completing S-shaped planning of the corresponding node; if not, the user can not select the specific application,
the optimum speed V is determinedbest∈[max{Vs,Ve},Vmax]To target the corresponding nodeFunction f (V)best)＝L-L(Vs,Vbest)-L(Ve,Vbest) Equal to 0 and the S-shaped planning of the corresponding node is completed.
The splitting module is specifically configured to: calculating the corresponding speed on the S-shaped programming speed curve by the merging nodes in the linked list according to the length of each motion track; determining whether the corresponding speed is not greater than a speed allowed by a point of engagement therewith; if not, splitting the corresponding merged node into two nodes at the position where the speed of the connecting point is maximum.
FIG. 4 illustrates a hardware block diagram of a computing device 30 for S-shaped velocity profile look-ahead planning according to an embodiment of the present description. As shown in fig. 4, computing device 30 may include at least one processor 301, storage 302 (e.g., non-volatile storage), memory 303, and a communication interface 304, and at least one processor 301, storage 302, memory 303, and communication interface 304 are connected together via a bus 305. The at least one processor 301 executes at least one computer readable instruction stored or encoded in the memory 302.
It should be appreciated that the computer-executable instructions stored in the memory 302, when executed, cause the at least one processor 301 to perform the various operations and functions described above in connection with fig. 1-2 in the various embodiments of the present specification.
In embodiments of the present description, computing device 30 may include, but is not limited to: personal computers, server computers, workstations, desktop computers, laptop computers, notebook computers, mobile computing devices, smart phones, tablet computers, cellular phones, Personal Digital Assistants (PDAs), handheld devices, messaging devices, wearable computing devices, consumer electronics, and so forth.
According to one embodiment, a program product, such as a machine-readable medium, is provided. A machine-readable medium may have instructions (i.e., elements described above as being implemented in software) that, when executed by a machine, cause the machine to perform various operations and functions described above in connection with fig. 1-2 in the various embodiments of the present specification. Specifically, a system or apparatus may be provided which is provided with a readable storage medium on which software program code implementing the functions of any of the above embodiments is stored, and causes a computer or processor of the system or apparatus to read out and execute instructions stored in the readable storage medium.
In this case, the program code itself read from the readable medium can realize the functions of any of the above-described embodiments, and thus the machine-readable code and the readable storage medium storing the machine-readable code form part of this specification.
Examples of the readable storage medium include floppy disks, hard disks, magneto-optical disks, optical disks (e.g., CD-ROMs, CD-R, CD-RWs, DVD-ROMs, DVD-RAMs, DVD-RWs), magnetic tapes, nonvolatile memory cards, and ROMs. Alternatively, the program code may be downloaded from a server computer or from the cloud via a communications network.
It will be understood by those skilled in the art that various changes and modifications may be made in the above-disclosed embodiments without departing from the spirit of the invention. Accordingly, the scope of the present description should be limited only by the attached claims.
It should be noted that not all steps and units in the above flows and system structure diagrams are necessary, and some steps or units may be omitted according to actual needs. The execution order of the steps is not fixed, and can be determined as required. The apparatus structures described in the above embodiments may be physical structures or logical structures, that is, some units may be implemented by the same physical client, or some units may be implemented by multiple physical clients, or some units may be implemented by some components in multiple independent devices.
In the above embodiments, the hardware units or modules may be implemented mechanically or electrically. For example, a hardware unit, module or processor may comprise permanently dedicated circuitry or logic (such as a dedicated processor, FPGA or ASIC) to perform the corresponding operations. The hardware units or processors may also include programmable logic or circuitry (e.g., a general purpose processor or other programmable processor) that may be temporarily configured by software to perform the corresponding operations. The specific implementation (mechanical, or dedicated permanent, or temporarily set) may be determined based on cost and time considerations.
The detailed description set forth above in connection with the appended drawings describes exemplary embodiments but does not represent all embodiments that may be practiced or fall within the scope of the claims. The term "exemplary" used throughout this specification means "serving as an example, instance, or illustration," and does not mean "preferred" or "advantageous" over other embodiments. The detailed description includes specific details for the purpose of providing an understanding of the described technology. However, the techniques may be practiced without these specific details. In some instances, well-known structures and devices are shown in block diagram form in order to avoid obscuring the concepts of the described embodiments.
The previous description of the disclosure is provided to enable any person skilled in the art to make or use the disclosure. Various modifications to the disclosure will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other variations without departing from the scope of the disclosure. Thus, the disclosure is not intended to be limited to the examples and designs described herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (10)
1. A S-shaped speed curve look-ahead planning method is characterized by comprising the following steps:
scanning a plurality of motion tracks to correspondingly establish a plurality of S-shaped curves, and storing the S-shaped curves in a linked list, wherein corresponding nodes of the S-shaped curves marked in the linked list are in a first state;
marking nodes which cannot be independently subjected to S-shaped planning in all nodes in the first state of the linked list as second states;
calculating the speed deviation value of each node of the second state in the linked list, and storing the speed deviation values in a deviation table according to the size in sequence;
selecting a corresponding node with the maximum speed deviation value in the deviation table to be combined with an adjacent node, and inserting the combined node which cannot be independently subjected to S-shaped planning into the deviation table to perform adjacent node combination again until the deviation table is empty;
performing time-optimal speed planning on each node capable of performing independent S-shaped planning in the linked list;
splitting the nodes which do not meet the preset motion constraint in the linked list into two nodes, and performing S-shaped planning on the split nodes;
carrying out endpoint speed reduction on the split node which cannot be subjected to S-shaped planning so as to enable the length of the shortest path required by the node from the low speed acceleration of the corresponding motion track to the endpoint speed after speed reduction to be equal to the length of the motion path of the S-shaped curve;
and splitting the node decelerated by the endpoint into nodes only containing single-segment motion tracks, and repeatedly executing the steps until the nodes in the linked list meet preset motion constraints so as to finish S-shaped speed curve planning of the plurality of segments of motion tracks.
2. The S-shaped velocity curve look-ahead planning method of claim 1, wherein scanning a plurality of motion trajectories to correspondingly establish a plurality of S-shaped curves comprises:
scanning from the last section to the first section, initializing the starting point speed of each section of motion track to the maximum allowable joining speed, initializing the end point speed to the starting point speed of the adjacent section at the corresponding joining point, and recording the path length of each section of motion track;
scanning from the first segment to the last segment, and establishing an S-shaped curve for each segment of motion track.
3. The S-shaped velocity curve look-ahead planning method of claim 1, wherein marking nodes that cannot be independently S-shaped planned among the nodes in the first state of the linked list as a second state specifically comprises:
judging whether the length of the shortest path required from low speed acceleration to high speed of the corresponding motion track is not greater than the length of the motion path of the corresponding S-shaped curve or not at each node of the first state in the linked list, wherein the low speed and the high speed of the motion track are obtained according to the speeds of two end points for sequencing the motion track; if so,
the corresponding node in the linked list is marked as the second state.
4. The S-shaped velocity curve look-ahead planning method of claim 3, wherein calculating the velocity bias value of each node of the second state in the linked list specifically comprises:
carrying out high-speed endpoint speed reduction on each node in the second state in the linked list, so that the length of the shortest path required by the node from the low speed acceleration of the corresponding motion track to the speed of the endpoint after speed reduction is equal to the length of the motion path of the S-shaped curve;
and calculating the difference value between the high speed of the corresponding motion track and the speed of the endpoint after the speed reduction in each node of the second state in the linked list to obtain a speed deviation value.
5. The S-shaped speed curve look-ahead planning method of claim 1, wherein the method of selecting the corresponding node with the largest speed deviation value in the deviation table to merge with the adjacent nodes, and reinserting the merged node which cannot be independently S-shaped planned into the deviation table to perform the merging of the adjacent nodes again until the deviation table is empty comprises:
selecting a corresponding node with the maximum speed deviation value in the deviation table, and combining the node with an adjacent node by taking a high-speed endpoint of the node as a joint point, wherein the maximum speed value of the combined node is a lower value of node constraint before combination; and/or the presence of a gas in the gas,
when merging, inquiring whether the two nodes before merging are in a second state; if so,
the merged two nodes are removed from the deviation table.
6. The S-shaped velocity curve look-ahead planning method of claim 1, wherein time-optimal velocity planning is performed on each node of the linked list that can be independently S-shaped planned, specifically comprising:
calculating the d value of each node of the independent S-shaped plan in the linked list:
d＝L-L(Vs，Vmax)-L(Ve，Vmax)
wherein L is the length of the motion path of the motion trail corresponding to the node, L (V)s，Vmax) Starting point velocity V of motion track corresponding to nodesAccelerating to the maximum speed V allowedmaxRequired shortest path length, L (V)e，Vmax) Endpoint velocity V of motion trajectory for nodeeAccelerating to the maximum speed V allowedmaxThe required shortest path length;
judging whether the d value of each node is greater than or equal to 0; if so,
determining that a uniform velocity segment exists and completing S-shaped planning of the corresponding node; if not, the user can not select the specific application,
the optimum speed V is determinedbest∈[max{Vs，Ve}，Vmax]So that the objective function f (V) of the corresponding nodebest)＝L-L(Vs，Vbest)-L(Ve，Vbest) Equal to 0 and the S-shaped planning of the corresponding node is completed.
7. The S-shaped velocity curve look-ahead planning method according to claim 1, wherein splitting a node that does not satisfy a preset motion constraint in the linked list into two nodes specifically comprises:
calculating the corresponding speed on the S-shaped programming speed curve by the merging nodes in the linked list according to the length of each motion track;
determining whether the corresponding speed is not greater than a speed allowed by a point of engagement therewith; if not, the user can not select the specific application,
splitting the corresponding merged node into two nodes at the position where the speed of the connecting point is maximum.
8. An S-shaped speed curve look-ahead planning device, comprising:
the scanning module is used for scanning a plurality of sections of motion tracks to correspondingly establish a plurality of S-shaped curves and storing the S-shaped curves in a linked list, wherein corresponding nodes of the S-shaped curves marked in the linked list are in a first state;
the marking module is used for marking the nodes which cannot be independently subjected to S-shaped planning in all the nodes in the first state of the linked list as a second state;
the calculation module is used for calculating the speed deviation value of each node in the second state in the linked list and storing the speed deviation values in the deviation table according to the size in sequence;
the merging module is used for selecting the corresponding node with the maximum speed deviation value in the deviation table to merge with the adjacent nodes, and inserting the merged nodes which cannot be independently subjected to S-shaped planning into the deviation table to perform merging of the adjacent nodes again until the deviation table is empty;
the planning module is used for carrying out time-optimal speed planning on each node which can be independently planned in an S shape in the linked list;
the splitting module is used for splitting the nodes which do not meet the preset motion constraint in the linked list into two nodes and performing S-shaped planning on the split nodes;
the speed regulating module is used for carrying out endpoint speed reduction on the split node which cannot be subjected to S-shaped planning so as to enable the length of the shortest path required by the node to be equal to the length of the motion path of the S-shaped curve when the node is accelerated from the low speed of the corresponding motion track to the endpoint speed after speed reduction;
the splitting module is further configured to split the node whose speed is reduced by the endpoint into nodes that only include a single-segment motion trajectory, and repeat the above steps until all nodes in the linked list satisfy a preset motion constraint, so as to complete S-shaped speed curve planning of the plurality of segments of motion trajectories.
9. A computing device, comprising:
at least one processor; and
a memory storing instructions that, when executed by the at least one processor, cause the at least one processor to perform the method of any one of claims 1 to 7.
10. A machine-readable storage medium storing executable instructions that, when executed, cause the machine to perform the method of any one of claims 1 to 7.
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Citations (37)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US4773025A (en) * | 1986-11-20 | 1988-09-20 | Unimation, Inc. | Multiaxis robot control having curve fitted path control |
| JPH06259567A (en) * | 1993-03-05 | 1994-09-16 | Hiroshi Makino | Method for interpolating free curve |
| US6242880B1 (en) * | 1998-09-08 | 2001-06-05 | Cimplus, Inc. | Tolerance based motion control system |
| JP2001166802A (en) * | 1999-12-13 | 2001-06-22 | Toyo Electric Mfg Co Ltd | S-shape acceleration/deceleration pattern generator |
| JP2005276155A (en) * | 2004-02-27 | 2005-10-06 | Thk Co Ltd | Numerical control method and device |
| US20070046677A1 (en) * | 2005-03-23 | 2007-03-01 | Hurco Companies, Inc. | Method of tolerance-based trajectory planning |
| JP2007330079A (en) * | 2006-06-09 | 2007-12-20 | Shinko Electric Co Ltd | Speed control device with acceleration instruction, and method for controlling speed of motor |
| CN101470434A (en) * | 2007-12-28 | 2009-07-01 | 中国科学院沈阳计算技术研究所有限公司 | Speed look-ahead control method based on filter technique |
| CN101493687A (en) * | 2009-03-02 | 2009-07-29 | 广西大学 | Real time forward looking whole-process acceleration and deceleration controlled NURBS curve self-adapting subsection interpolation method |
| JP2009173105A (en) * | 2008-01-23 | 2009-08-06 | Advics Co Ltd | Motion controller for vehicle |
| CN101833306A (en) * | 2010-05-12 | 2010-09-15 | 中国科学院沈阳计算技术研究所有限公司 | Multi-program-segment continuous acceleration and deceleration control method based on advanced-filter technology |
| CN102419570A (en) * | 2011-09-29 | 2012-04-18 | 上海大学 | Acceleration and deceleration look-ahead control method for high-speed machining of numerical control machine tool |
| JP2014048095A (en) * | 2012-08-30 | 2014-03-17 | Mitsutoyo Corp | Industrial machinery, control method for industrial machinery, shape measurement device and control method for shape measurement device |
| CN103970139A (en) * | 2014-05-09 | 2014-08-06 | 上海交通大学 | Robot continuous point position motion planning method and motion controller thereof |
| JP2014174842A (en) * | 2013-03-11 | 2014-09-22 | Tamagawa Seiki Co Ltd | S-shaped acceleration/deceleration control program, operation control program, recording medium, controller, s-shaped acceleration/deceleration control calculation method, and work operation control system |
| CN104076742A (en) * | 2014-06-20 | 2014-10-01 | 北京航空航天大学 | Continuous multi-type curved segment mixed interpolation cubic polynomial feeding speed proactive planning method |
| CN104238458A (en) * | 2013-06-08 | 2014-12-24 | 沈阳高精数控技术有限公司 | NURBS curve high-speed prospective interpolation method |
| CN104375468A (en) * | 2014-11-25 | 2015-02-25 | 苏州谷夫道自动化科技有限公司 | Numerical control device CNC system look-ahead rolling processing method |
| CN104483906A (en) * | 2015-01-07 | 2015-04-01 | 浙江师范大学 | S-curve acceleration and deceleration control method and device of discrete sampling |
| CN104551341A (en) * | 2014-11-25 | 2015-04-29 | 苏州谷夫道自动化科技有限公司 | Numerical control ring welding machine and interpolation control method thereof |
| CN104678899A (en) * | 2015-02-11 | 2015-06-03 | 北京配天技术有限公司 | Curve velocity planning method and device, as well as numerical control machining path data processing method |
| WO2017113069A1 (en) * | 2015-12-28 | 2017-07-06 | 深圳配天智能技术研究院有限公司 | S-shaped curve planning method and device, and numerically-controlled machine tool |
| WO2017113195A1 (en) * | 2015-12-30 | 2017-07-06 | 深圳配天智能技术研究院有限公司 | Processing path planning method, processing path planning apparatus and numerically controlled machine tool |
| CN107368639A (en) * | 2017-07-10 | 2017-11-21 | 深圳市同川科技有限公司 | Speed planning method, apparatus, computer equipment and storage medium |
| JP2017228318A (en) * | 2017-09-21 | 2017-12-28 | Ntn株式会社 | Control device for link operation device |
| CN107817764A (en) * | 2017-10-23 | 2018-03-20 | 山东大学 | A kind of nurbs curve bidirectional self-adaptive interpolation algorithm based on the S curve plus-minus short-cut counting method |
| CN108037737A (en) * | 2017-12-19 | 2018-05-15 | 苏州谷夫道自动化科技有限公司 | The point-to-point S-shaped speed planning method of quick response |
| CN108829044A (en) * | 2018-07-27 | 2018-11-16 | 山东大学 | There is the S curve deceleration planning method of negative value in a kind of reply whole story speed |
| CN108958173A (en) * | 2018-07-27 | 2018-12-07 | 山东大学 | S curve deceleration planning method under any velocity of displacement based on trapezoidal solution |
| CN109032081A (en) * | 2018-08-10 | 2018-12-18 | 山东易码智能科技股份有限公司 | Multi-axis robot point synchronization control method and system based on S curve acceleration and deceleration |
| CN109683615A (en) * | 2018-12-25 | 2019-04-26 | 上海新时达机器人有限公司 | The speed look-ahead approach and robot controller in the path that robot continuously moves |
| CN110703684A (en) * | 2019-11-01 | 2020-01-17 | 哈工大机器人（合肥）国际创新研究院 | Trajectory planning method and device with unlimited endpoint speed |
| CN111796558A (en) * | 2020-06-08 | 2020-10-20 | 五邑大学 | Multi-axis linkage real-time dynamic look-ahead trajectory planning method and device and storage medium |
| WO2021036630A1 (en) * | 2019-08-29 | 2021-03-04 | 山东大学 | Laser-cladding joining control method, and laser head dynamic height adjustment method and system |
| CN112547425A (en) * | 2020-12-08 | 2021-03-26 | 深圳市华成工业控制股份有限公司 | Track look-ahead-based dispenser motion planning method and system |
| CN112650145A (en) * | 2020-12-24 | 2021-04-13 | 苏州谋迅智能科技有限公司 | S-shaped speed curve self-adaptive combination evaluation method |
| DE112019006713T5 (en) * | 2019-01-21 | 2021-10-28 | Megarobo Technologies Co., Ltd. | A method for controlling a movement, a device and a system and a storage medium of the same |
-
2021
- 2021-09-28 CN CN202111145153.1A patent/CN114035513A/en active Pending
Patent Citations (39)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US4773025A (en) * | 1986-11-20 | 1988-09-20 | Unimation, Inc. | Multiaxis robot control having curve fitted path control |
| JPH06259567A (en) * | 1993-03-05 | 1994-09-16 | Hiroshi Makino | Method for interpolating free curve |
| US6242880B1 (en) * | 1998-09-08 | 2001-06-05 | Cimplus, Inc. | Tolerance based motion control system |
| JP2001166802A (en) * | 1999-12-13 | 2001-06-22 | Toyo Electric Mfg Co Ltd | S-shape acceleration/deceleration pattern generator |
| JP2005276155A (en) * | 2004-02-27 | 2005-10-06 | Thk Co Ltd | Numerical control method and device |
| US20070046677A1 (en) * | 2005-03-23 | 2007-03-01 | Hurco Companies, Inc. | Method of tolerance-based trajectory planning |
| JP2007330079A (en) * | 2006-06-09 | 2007-12-20 | Shinko Electric Co Ltd | Speed control device with acceleration instruction, and method for controlling speed of motor |
| CN101470434A (en) * | 2007-12-28 | 2009-07-01 | 中国科学院沈阳计算技术研究所有限公司 | Speed look-ahead control method based on filter technique |
| JP2009173105A (en) * | 2008-01-23 | 2009-08-06 | Advics Co Ltd | Motion controller for vehicle |
| CN101493687A (en) * | 2009-03-02 | 2009-07-29 | 广西大学 | Real time forward looking whole-process acceleration and deceleration controlled NURBS curve self-adapting subsection interpolation method |
| CN101833306A (en) * | 2010-05-12 | 2010-09-15 | 中国科学院沈阳计算技术研究所有限公司 | Multi-program-segment continuous acceleration and deceleration control method based on advanced-filter technology |
| CN102419570A (en) * | 2011-09-29 | 2012-04-18 | 上海大学 | Acceleration and deceleration look-ahead control method for high-speed machining of numerical control machine tool |
| JP2014048095A (en) * | 2012-08-30 | 2014-03-17 | Mitsutoyo Corp | Industrial machinery, control method for industrial machinery, shape measurement device and control method for shape measurement device |
| JP2014174842A (en) * | 2013-03-11 | 2014-09-22 | Tamagawa Seiki Co Ltd | S-shaped acceleration/deceleration control program, operation control program, recording medium, controller, s-shaped acceleration/deceleration control calculation method, and work operation control system |
| CN104238458A (en) * | 2013-06-08 | 2014-12-24 | 沈阳高精数控技术有限公司 | NURBS curve high-speed prospective interpolation method |
| CN103970139A (en) * | 2014-05-09 | 2014-08-06 | 上海交通大学 | Robot continuous point position motion planning method and motion controller thereof |
| CN104076742A (en) * | 2014-06-20 | 2014-10-01 | 北京航空航天大学 | Continuous multi-type curved segment mixed interpolation cubic polynomial feeding speed proactive planning method |
| CN104375468A (en) * | 2014-11-25 | 2015-02-25 | 苏州谷夫道自动化科技有限公司 | Numerical control device CNC system look-ahead rolling processing method |
| CN104551341A (en) * | 2014-11-25 | 2015-04-29 | 苏州谷夫道自动化科技有限公司 | Numerical control ring welding machine and interpolation control method thereof |
| CN104483906A (en) * | 2015-01-07 | 2015-04-01 | 浙江师范大学 | S-curve acceleration and deceleration control method and device of discrete sampling |
| CN104678899A (en) * | 2015-02-11 | 2015-06-03 | 北京配天技术有限公司 | Curve velocity planning method and device, as well as numerical control machining path data processing method |
| US20180088551A1 (en) * | 2015-02-11 | 2018-03-29 | Shenzhen A&E Intelligent Technology Institute Co., Ltd. | Curve velocity planning method, device, and numerical control machining route data processing method thereof |
| WO2017113069A1 (en) * | 2015-12-28 | 2017-07-06 | 深圳配天智能技术研究院有限公司 | S-shaped curve planning method and device, and numerically-controlled machine tool |
| CN107850887A (en) * | 2015-12-28 | 2018-03-27 | 深圳配天智能技术研究院有限公司 | S types curve plans method, apparatus and Digit Control Machine Tool |
| WO2017113195A1 (en) * | 2015-12-30 | 2017-07-06 | 深圳配天智能技术研究院有限公司 | Processing path planning method, processing path planning apparatus and numerically controlled machine tool |
| CN107368639A (en) * | 2017-07-10 | 2017-11-21 | 深圳市同川科技有限公司 | Speed planning method, apparatus, computer equipment and storage medium |
| JP2017228318A (en) * | 2017-09-21 | 2017-12-28 | Ntn株式会社 | Control device for link operation device |
| CN107817764A (en) * | 2017-10-23 | 2018-03-20 | 山东大学 | A kind of nurbs curve bidirectional self-adaptive interpolation algorithm based on the S curve plus-minus short-cut counting method |
| CN108037737A (en) * | 2017-12-19 | 2018-05-15 | 苏州谷夫道自动化科技有限公司 | The point-to-point S-shaped speed planning method of quick response |
| CN108829044A (en) * | 2018-07-27 | 2018-11-16 | 山东大学 | There is the S curve deceleration planning method of negative value in a kind of reply whole story speed |
| CN108958173A (en) * | 2018-07-27 | 2018-12-07 | 山东大学 | S curve deceleration planning method under any velocity of displacement based on trapezoidal solution |
| CN109032081A (en) * | 2018-08-10 | 2018-12-18 | 山东易码智能科技股份有限公司 | Multi-axis robot point synchronization control method and system based on S curve acceleration and deceleration |
| CN109683615A (en) * | 2018-12-25 | 2019-04-26 | 上海新时达机器人有限公司 | The speed look-ahead approach and robot controller in the path that robot continuously moves |
| DE112019006713T5 (en) * | 2019-01-21 | 2021-10-28 | Megarobo Technologies Co., Ltd. | A method for controlling a movement, a device and a system and a storage medium of the same |
| WO2021036630A1 (en) * | 2019-08-29 | 2021-03-04 | 山东大学 | Laser-cladding joining control method, and laser head dynamic height adjustment method and system |
| CN110703684A (en) * | 2019-11-01 | 2020-01-17 | 哈工大机器人（合肥）国际创新研究院 | Trajectory planning method and device with unlimited endpoint speed |
| CN111796558A (en) * | 2020-06-08 | 2020-10-20 | 五邑大学 | Multi-axis linkage real-time dynamic look-ahead trajectory planning method and device and storage medium |
| CN112547425A (en) * | 2020-12-08 | 2021-03-26 | 深圳市华成工业控制股份有限公司 | Track look-ahead-based dispenser motion planning method and system |
| CN112650145A (en) * | 2020-12-24 | 2021-04-13 | 苏州谋迅智能科技有限公司 | S-shaped speed curve self-adaptive combination evaluation method |
Non-Patent Citations (9)
| Title |
|---|
| TSAI, MENG-SHIUN: "A novel integrated dynamic acceleration/deceleration interpolation algorithm for a CNC controller", INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, pages 279 - 292 * |
| YE P: "Interpolation of continuous micro line segment trajectories hased on look-ahead algorithm in high-speed machining", INTERNATIONAL JOURNAL OF ADVANCED MANUF ACTURING TECHNOLOGY, pages 881 - 897 * |
| ZHAO H: "A real-time look-ahead interpolation methodology with curvature-continuous B-spline transition scheme for CNC machning of micro linesegments", INTERNATIONAL JOURNAL OF MACHINE AND MANUFACTURE, pages 88 - 98 * |
| 刘强;刘焕;周胜凯;李传军;袁松梅;: "连续多类型曲线段进给速度前瞻规划", 计算机集成制造系统, no. 09, pages 117 - 125 * |
| 叶百胜: "小线段S型加减速方式高速衔接算法", 轻工机械, pages 34 - 38 * |
| 孙征: "基于前瞻S曲线的B样条连续小线段插补算法", 华北理工大学学报(自然科学版), pages 113 - 118 * |
| 李建伟;林浒;孙玉娥;: "基于S曲线加减速的NURBS实时插补前瞻控制方法", 组合机床与自动化加工技术, no. 11, pages 46 - 50 * |
| 杨亮亮: "基于牛顿迭代法的S形加减速时间算法研究", 中国机械工程, pages 912 - 916 * |
| 陶佳安: "连续微段前瞻及加减速算法", 计算机辅助设计与图形学学报, pages 1570 - 1577 * |
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