CN116719326A - Robot obstacle avoidance method, system and storage medium - Google Patents
Robot obstacle avoidance method, system and storage medium Download PDFInfo
- Publication number
- CN116719326A CN116719326A CN202310912165.5A CN202310912165A CN116719326A CN 116719326 A CN116719326 A CN 116719326A CN 202310912165 A CN202310912165 A CN 202310912165A CN 116719326 A CN116719326 A CN 116719326A
- Authority
- CN
- China
- Prior art keywords
- robot
- value
- obstacle
- obstacle avoidance
- travel
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 39
- 238000013519 translation Methods 0.000 claims abstract description 49
- 230000008602 contraction Effects 0.000 claims description 6
- 230000003068 static effect Effects 0.000 claims description 3
- 230000009286 beneficial effect Effects 0.000 abstract description 2
- 230000014616 translation Effects 0.000 description 31
- 238000001514 detection method Methods 0.000 description 3
- 102100024233 High affinity cAMP-specific 3',5'-cyclic phosphodiesterase 7A Human genes 0.000 description 2
- 101001117267 Homo sapiens High affinity cAMP-specific 3',5'-cyclic phosphodiesterase 7A Proteins 0.000 description 2
- 230000001105 regulatory effect Effects 0.000 description 2
- 101100136063 Mycobacterium tuberculosis (strain ATCC 25618 / H37Rv) PE11 gene Proteins 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 238000004590 computer program Methods 0.000 description 1
- 230000002349 favourable effect Effects 0.000 description 1
- 238000012423 maintenance Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
- 231100000817 safety factor Toxicity 0.000 description 1
Abstract
The application provides a robot obstacle avoidance method, a system and a storage medium, which are characterized in that firstly obstacle information encountered in front is detected, a minimum circumscribed rectangle of an obstacle is constructed based on the obstacle information, when a robot runs to a certain distance from the minimum circumscribed rectangle of the obstacle, obstacle avoidance parameters corresponding to different transverse translation strategies are compared, and finally a running suggestion which is more beneficial to obstacle avoidance of the robot is obtained. And in the obstacle avoidance process of the robot, the robot always runs along the outline of the minimum circumscribed rectangle instead of the arc outline only by means of transverse translation and straight running, so that potential safety hazards possibly occurring in the obstacle avoidance process of the robot are guaranteed to the greatest extent.
Description
Technical Field
The application relates to the field of data processing, in particular to a robot obstacle avoidance method, a robot obstacle avoidance system and a storage medium.
Background
At present, in some underground traffic scenes, the robots can run according to preset rules, most robots usually run according to global path planning given by a navigation system, and the road obstacle information input by the navigation system can enable the robots to avoid the obstacles in advance during global path planning. However, the navigation system may not identify the road obstacle information as an obstacle to remind the robot to avoid, which may bring a certain danger to the running of the robot, because of a certain time difference in the entry of the road obstacle information, such as a road indicator placed for temporary maintenance, or even some temporarily parked robots or other objects. In addition, when the existing robot avoids the obstacle, a method of driving along the outline of the obstacle is generally adopted, and the risk of driving of the robot is increased to a certain extent, so that how to avoid the temporarily-appearing static obstacle in real time and improve the driving safety of the robot is a technical problem which needs to be solved by the person skilled in the art.
Disclosure of Invention
Aiming at the technical problems, the application adopts the following technical scheme: a robot obstacle avoidance method comprises the following steps: s100, acquiring an obstacle distance information set d= { (X1, Y1), (X2, Y2), (Xi, yi), (Xn, yn) } in a detectable range in a driving direction of the robot at the current moment, wherein (Xi, yi) is distance information of an ith detected point on the obstacle, xi is a coordinate value of the ith detected point on an X-axis of a first preset coordinate system, and Yi is a coordinate value of the ith detected point on a Y-axis of the first preset coordinate system; i is in the range of 1 to n, n is the total number of detected points on the obstacle; the first preset coordinate system takes the geometric center of the current robot as an origin, takes the current running direction of the robot as an x-axis positive direction, and takes the direction of the current running direction rotated 90 degrees anticlockwise as a y-axis positive direction; s200, constructing an external rectangle of the obstacle according to the obstacle distance information set D; and S300, when the robot runs to a first distance threshold from the circumscribed rectangle, obtaining a target running direction based on the circumscribed rectangle, and continuing running according to the target running direction, wherein the continuous running mode comprises straight running and translation.
A robot obstacle avoidance system comprising a processor and a non-transitory computer readable storage medium storing at least one instruction or at least one program, the processor loading and executing the at least one instruction or at least one program to implement the robot obstacle avoidance method described above.
A computer-readable storage medium storing a program or instructions that cause a computer to execute the aforementioned robot obstacle avoidance method.
According to the method, firstly, obstacle information encountered in front is detected, the minimum circumscribed rectangle of the obstacle is constructed based on the obstacle information, when the robot runs to a certain distance from the minimum circumscribed rectangle of the obstacle, obstacle avoidance parameters corresponding to different transverse translation strategies are compared, and finally, a running suggestion which is more beneficial to obstacle avoidance of the robot is obtained. And in the obstacle avoidance process of the robot, the robot always runs along the outline of the minimum circumscribed rectangle instead of the arc outline only by means of transverse translation and straight running, so that potential safety hazards possibly occurring in the obstacle avoidance process of the robot are guaranteed to the greatest extent.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for the description of the embodiments will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments of the present application, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a flowchart of a robot obstacle avoidance method according to an embodiment of the present application.
Detailed Description
The following description of the embodiments of the present application will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present application, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to fall within the scope of the application.
The embodiment of the application provides a robot obstacle avoidance method, as shown in fig. 1, comprising the following steps:
s100, acquiring an obstacle distance information set d= { (X1, Y1), (X2, Y2), (Xi, yi), (Xn, yn) } in a detectable range in a driving direction of the robot at the current moment, wherein (Xi, yi) is distance information of an ith detected point on the obstacle, xi is a coordinate value of the ith detected point on an X-axis of a first preset coordinate system, and Yi is a coordinate value of the ith detected point on a Y-axis of the first preset coordinate system; i is in the range of 1 to n, n is the total number of detected points on the obstacle; the first preset coordinate system takes the geometric center of the current robot as an origin, the current running direction of the robot as an x-axis positive direction, and the direction of the current running direction rotated 90 degrees anticlockwise as a y-axis positive direction.
In the application, the robot can at least perform functions including straight forward, straight backward, lateral translation (including left lateral translation and right lateral translation), and the like. The brand, model, etc. of the robot are not particularly limited in the present application, and those skilled in the art will understand that all robots capable of implementing the above functions are within the scope of the present application. Specifically, a detection unit provided on the robot itself may be used to detect obstacle information in front of the robot in real time. And in the present application, only the detection information of the detection unit that can acquire the obstacle information is used as the obstacle distance information set D.
S200, constructing an circumscribed rectangle of the obstacle according to the obstacle distance information set D.
In a preferred embodiment of the present application, the circumscribing rectangle includes at least a first rectangle to avoid unnecessary detour of the robot, etc.; at this time, S200 specifically includes: s201, taking the obstacle distance information set D as a target input data set of an external rectangle acquisition function to obtain the first rectangle.
The external rectangle obtaining function executes the following steps:
s001, acquiring a longitudinal maximum value and a longitudinal minimum value of the obstacle according to the target input data set, wherein the longitudinal maximum value is the maximum value of x-axis coordinate values of all detected points in the target input data set, and the longitudinal minimum value is the minimum value of x-axis coordinate values of all detected points in the target input data set. In this embodiment, when the obstacle distance information set D is the target input data set, the longitudinal maximum value=max (X1, X2,) is an.
S002, obtaining the transverse maximum value and the transverse minimum value of the obstacle according to the target input data set, wherein the transverse maximum value is the maximum value of the y-axis coordinate values of all detected points in the target input data set, and the transverse minimum value is the minimum value of the y-axis coordinate values of all detected points in the target input data set. As is known from S001, at this time, the lateral maximum value=max (Y1, Y2,) and Yi, yn, and the lateral minimum value=min (Y1, Y2,) and Yi, yn.
S003, outputting a minimum circumscribed rectangle based on a longitudinal maximum value, a longitudinal minimum value, a transverse maximum value and a transverse minimum value, wherein (the longitudinal maximum value, the transverse maximum value), (the longitudinal maximum value, the transverse minimum value), (the longitudinal minimum value, the transverse maximum value), (the longitudinal minimum value and the transverse minimum value) are four vertexes of the minimum circumscribed rectangle.
According to the above, when the circumscribed rectangle acquisition function is used and the obstacle distance information set D is used as the target input data set of the circumscribed rectangle acquisition function, the first rectangle output is the minimum circumscribed rectangle based on D.
Further, in another preferred embodiment of the present application, the circumscribed rectangle further comprises a plurality of first sub-rectangles.
At this time, S200 further includes the following:
s202, acquiring a rectangular division point value pair S= { (Y) based on the obstacle distance information set D 1,1 ，Y 1,2 )，(Y 2,1 ，Y 2,2 )，......，(Y j,1 ，Y j,2 )，......，(Y m,1 ，Y m,2 ) }, wherein Y 1,1 ＞Y 1,2 ＞Y 2,1 ＞Y 2,2 ＞......＞Y j,1 ＞Y j,2 ＞......＞Y m,1 ＞Y m,2 ，(Y j,1 ，Y j,2 ) Dividing the value pair of points for the j-th rectangle, Y j,1 ∈{Y1，Y2，......，Yi，......，Yn}，Y j,2 ∈{Y1，Y2，......，Yi，......，Yn}，Y j,1 And Y j,2 Adjacent, and Y j,1 -Y j,2 The value range of j is 1 to m, and m is the number of rectangular dividing point value pairs; first preset interval threshold = robot width + lateral extension float space threshold, and the lateral extension float space threshold is greater than 0. Preferably, the value range of the transverse extension floating space threshold value is [0.3m,1m ]]So as to ensure that the robot can smoothly pass through and avoid accidents.
S203, traversing all the value pairs in the value pairs S of the rectangular dividing points, and constructing m+1 sub-obstacle distance information sets E of the obstacle based on the transverse maximum value and the transverse minimum value in the obstacle distance information set D 1 、E 2 、......、E k 、......、E m+1 The method comprises the steps of carrying out a first treatment on the surface of the Wherein the lateral maximum value=max (Y1, Y2,) is the same as the lateral minimum value=min k For the k-th sub-obstacle distance information set, k has a value of 1, 2.
Specifically, in the present application, when 2.ltoreq.k.ltoreq.m, Y is based on k-1,2 Corresponding detected point Y k,1 Corresponding detected point Y k-1,2 And Y k,1 Distance information of all detected points included in the distance information set E, and a kth sub-obstacle distance information set E is obtained k ；
Wherein when k=1, based on Y 1,1 Corresponding detected point, the crossTo the detected point Y corresponding to the maximum value 1,1 And distance information of all detected points included between the transverse maximum values, obtaining a 1 st sub-obstacle distance information set E 1 ；
When k=m+1, based on Y m,2 Corresponding detected point, detected point corresponding to the transverse minimum value, Y m,2 And distance information of all detected points included between the transverse minimum values, obtaining an (m+1) th sub-obstacle distance information set E m+1 ；
S204, the kth sub-obstacle distance information set E k And a target input data set serving as the circumscribed rectangle acquisition function is used for obtaining a kth first sub-rectangle.
As can be seen from the above, S202-S204 further divide the first rectangle into a plurality of different first sub-rectangles according to a preset rule based on the obstacle distance information set D. By dividing the different first sub-rectangles, invalid situations such as robot detouring and the like can be further avoided.
And S300, when the robot runs to a first distance threshold from the circumscribed rectangle, obtaining a target running direction based on the circumscribed rectangle, and continuing running according to the target running direction to avoid the obstacle, wherein the continuous running mode comprises straight running and translation. Preferably, the first distance threshold refers to a distance between a geometric center of the robot and the circumscribed rectangle, so that a certain safety distance is reserved between the robot and the obstacle, and running safety of the robot is further guaranteed.
In a preferred embodiment of the present application, the robot further includes a mechanical arm that can extend and retract along a current driving direction, and the mechanical arm in the present application is not limited to the current driving method, and may extend and retract in any direction as required. Thus, in the present application, the first distance threshold is obtained by:
s301, acquiring the current speed V1 of the robot at the current moment and the current state data of the mechanical arm, wherein the current state data of the mechanical arm at least comprise current fault information, current telescopic speed and current extended length. Specifically, in the present application, the current fault information is used to indicate a fault state of the mechanical arm, for example, 0 indicates that the mechanical arm is in a non-fault state, 1 indicates that the mechanical arm is in a fault state, whether the mechanical arm is in a fault state or not may be simply determined based on the information of the current telescopic speed, the current extended length and the like, and the present application does not exclude that other conventional parameters may be combined to determine whether the mechanical arm is in a fault state or not. The current telescopic speed represents the current corresponding speed, and the current extended length represents the extending length of the mechanical arm from the robot body.
S302, if the current fault information indicates that the mechanical arm is in a static fault state, the value range of the first distance threshold value is [ 1.5m+the current extended length, 3m+the current extended length ].
S303, if the current fault information indicates that the mechanical arm is in a normal contraction working state, and V1/t1 is less than or equal to a first preset deceleration increment value, the value range of the first distance threshold is [1.5m,3m ], wherein t1=current extended length/current contraction speed.
S304, if the current fault information indicates that the mechanical arm is in a normal contraction working state and V1/t1 is greater than a first preset deceleration increment value, the value range of the first distance threshold is [ 1.5m+current extended length-current expansion speed t2, 3m+current extended length-current expansion speed t2], where t2=v1/first preset deceleration increment value.
And S305, if the current fault information indicates that the mechanical arm is in a normal extending working state, the value range of the first distance threshold value is [ 1.5m+the whole arm length of the mechanical arm, 3m+the whole arm length of the mechanical arm ].
Through steps S301-S305, damage to the mechanical arm can be avoided in the running process of the robot.
Specifically, in one embodiment of the present application, a target traveling direction is obtained based on the circumscribed rectangle, and traveling is continued according to the target traveling direction, including the steps of:
s310, based on the condition that the robot runs to a first distance threshold from the circumscribed rectangleThe method comprises the steps of obtaining global path information, and obtaining a first distance D relative to the global path when a robot transversely translates to the right to a first position Tm+1 and transversely translates to the left to a second position Tm+2 respectively 1 And a second distance D 2 The method comprises the steps of carrying out a first treatment on the surface of the Wherein min (Y1, Y2,) is greater than or equal to the second distance threshold, tdtm+2-max (Y1, Y2,) is greater than or equal to the second distance threshold, TDm +1 is a Y-axis coordinate value of the first position tm+1 in the first preset coordinate system, and TDm +2 is a Y-axis coordinate value of the second position tm+2 in the first preset coordinate system. In general, a robot travels along a road prompted by a global path during traveling, and the global path information is a piece of global path information provided by a navigation system according to an input departure place and destination. Thus, a first distance D of the robot relative to the global path 1 And a second distance D 2 It can be understood that: and when the robot is at the first position and the second position, the vertical distance (namely the distance on the y axis of the first preset coordinate system after transverse translation) between the robot and the position when the robot runs to be at the first distance threshold from the circumscribed rectangle. The second distance threshold is at least greater than the width of the robot.
S320, obtaining a third distance D between the robot and the destination in the global path information when the robot is located at the first position and the second position respectively 3 And a fourth distance D 4 . In this step, the distance between the robot and the destination may be understood as a straight line distance between two points, and may be understood as a distance between the first and second positions and the destination in the global path acquired again when the robot is located at the first and second positions.
Specifically, in the process of performing calculation, for example, when data such as global path information, a distance between the robot and the destination is acquired, a reference coordinate system in the navigation system may be used as a unique reference coordinate system, that is, the first preset coordinate system and the reference coordinate system may be mutually converted, so as to acquire accurate data.
S330, based on the first distance D 1 Second distance D 2 Third distance D 3 Fourth distance D 4 Obtaining a first driving obstacle avoidance parameter L1 and a second driving obstacle avoidance parameter L2 of the robot, wherein l1=β (d 1) (α1d1+α02×d3), l2=α3 (d 2) (α1d2+α22×d4), wherein d1 represents lateral translation direction information when the robot is laterally translated to a position T1, d2 represents lateral translation direction information when the robot is laterally translated to a position T2, α1 is a first preset weight, α2 is a second preset weight, and α4 () is used for obtaining a third preset weight corresponding to different lateral translation directions. In the present application, α1 and α2 are preset values, and preferably α1+α2=1. When d1 or d2 accords with the built-in obstacle avoidance priority driving direction of the robot, beta=preset initial value-adjustable floating value, and when d1 or d2 does not accord with the built-in obstacle avoidance priority driving direction of the robot, beta=preset initial value+adjustable floating value. The preset initial value may be empirically set, for example, may be 0.5, and the adjustable float value satisfies greater than 0 and less than the preset initial value. The built-in obstacle avoidance priority driving direction can be set when the robot leaves the factory, and can also be set in a self-defined mode according to actual conditions. There are various methods for representing them, for example, the numerals 1 and 0 are used to represent left and right, respectively. Those skilled in the art will appreciate that the foregoing is merely exemplary and is not intended to limit the scope of the present application.
S340, performing transverse translation according to the transverse translation direction corresponding to the smaller value in L1 and L2.
In another preferred embodiment of the present application, a target traveling direction is obtained based on the circumscribed rectangle, and traveling is continued according to the target traveling direction, comprising the steps of:
s3100, based on global path information corresponding to when the robot travels to a first distance threshold from the circumscribed rectangle, acquiring relative path distances TD1, TD2, and tm+2 relative to the global path when the robot is laterally translated to positions T1, T2, & gt, th, & gt, tm+2, respectively, wherein when h=m+1, min (Y1, Y2, & gt, yi, & gt, yn) -TDm +1 is greater than or equal to a second distance threshold, TDm +1 is a Y-axis coordinate value of tm+1 in a first preset coordinate system, and when h=m+2, TDm +2-max (Y1, Y2, & gt, yi, & gt, yn) is greater than or equal to a second distance thresholdTDm +2 is the Y-axis coordinate value of Tm+2 in the first preset coordinate system, and when h is 1-m, th= (Y) h,1 +Y h,2 )/2. The relative path distance between the robot and the global path after the robot horizontally translates the position can be referred to the related content in the foregoing embodiment, and will not be described herein.
S3200, acquiring relative destination distances DD1, DD2, DDh, DDm +2 between the robots and the destinations in the global path information when the robots are located at the positions T1, T2, and Th, and tm+2, respectively.
S3300, based on the relative path distances TD1, TD2, TDh, tm+2, and the relative destination distances DD1, DD2, DDh, DDm +2, obtaining m+2 travel obstacle avoidance parameters M1, M2 for the robot, mh, mm+2. Wherein mh=β (dh) (α1×tdh+α2×ddh), where dh represents lateral translation direction information when the robot is laterally translated to the position Th, α1 is a first preset weight, α2 is a second preset weight, and β () is used to obtain a third preset weight corresponding to a different lateral translation direction.
S3400, performing lateral translation according to a lateral translation direction corresponding to a smaller value of M1, M2, mh.
In summary, the present application first detects the obstacle information encountered in front, constructs the minimum bounding rectangle of the obstacle based on the obstacle information, and when the robot travels a certain distance from the minimum bounding rectangle of the obstacle, finally obtains the travel advice more favorable for the robot to avoid the obstacle by comparing the obstacle avoidance parameters corresponding to different lateral translation strategies. And in the obstacle avoidance process of the robot, the robot always runs along the outline of the minimum circumscribed rectangle instead of the arc outline only by means of transverse translation and straight running, so that potential safety hazards possibly occurring in the obstacle avoidance process of the robot are guaranteed to the greatest extent.
In another embodiment of the present application, S300 further comprises the following steps:
s400, if the position of the robot after transverse translation is located at the position of Tm+1 or Tm+2, acquiring an obstacle distance information set in a detectable range of the current robot in the driving direction of the original robot to construct an external rectangle of the obstacle, otherwise, continuing to drive the robot in the driving direction of the original robot, and acquiring the obstacle distance information set in the detectable range in the current driving direction to construct the external rectangle of the obstacle. In the present application, since there is a limitation in the detectable range of the robot, the distance information of the detected obstacle may be only a part of the obstacle, and thus, when the robot is laterally translated to the leftmost end or the rightmost end of the first rectangle, it is necessary to acquire the obstacle information in the original robot traveling direction after the translation of the robot in real time in order to secure safety. When the position of the robot after the transverse translation is not at the leftmost end or the rightmost end of the first rectangle, the distance between two adjacent points exceeds the width of one robot, so that the robot can directly run in a straight line, and then obstacle information in the current running direction of the robot can be continuously detected.
Through step S400, the robot can continuously detect the obstacle in the detectable range and acquire the optimal obstacle avoidance scheme.
In a preferred embodiment of the application, the method further comprises the steps of:
s0001, acquiring a travel data set w= { W1, W2, & gt, wq }, on all travel routes of the robot within a preset period, wherein the travel data wq= { TMq, TMq, PEq1, PEq2, SFq1, SFq }, on the Q-th travel route, is obtained, at least one of the travel start point and the travel end point is different, TMq is a sum of travel times of only left lateral translation of the target travel direction on the Q-th travel route, TMq2 is a sum of travel times of only right lateral translation of the target travel direction on the Q-th travel route, PEq is a sum of travel times of only left lateral translation of the target travel direction on the Q-th travel route, PEq is a sum of travel times of only right lateral translation of the target travel direction on the Q-th travel route, SFq is a sum of only left lateral translation safety coefficient on the Q-th travel route, SFq is a sum of the travel times of only left lateral translation of the target travel direction on the Q-th travel route, and Q is a value of only Q, Q is taken as the Q is a value.
As an example, assuming that there are 10 routes traveled by the robot within a month, wherein for the first travel route, the number of left lateral translations is 4, and in these 4 times, the time taken for the robot to travel through the first travel route (i.e. from the start point to the end point) is 1 hour, 1.5 hours, 0.9 hours and 1.1 hour, respectively, and the corresponding safety factors are 0.5, 0.2, 0.5 and 0.5, respectively, TMq 1=4, peq1=4.5 hours, SFq 1=1.7 are referred to the foregoing for the corresponding data of right lateral translations only, and the other travel related data are also analogized, which will not be repeated here. In a preferred embodiment of the present application, TMq 1.1.noteq.0, TMq2.noteq.0.
S0002, acquiring obstacle avoidance indexes P1, P2, P3 and P4 in the obstacle avoidance preferential traveling direction which accords with the built-in obstacle avoidance preferential traveling direction of the robot based on a traveling data set W, wherein P1 is the ratio of the sum of traveling times of the object traveling direction which accords with the built-in obstacle avoidance preferential traveling direction of the robot on all traveling routes to the sum of corresponding travel times, P2 is the ratio of the sum of traveling times of the object traveling direction which does not accord with the built-in obstacle avoidance preferential traveling direction of the robot on all traveling routes to the sum of traveling times of the corresponding travel times, P3 is the ratio of the sum of safety coefficients of the object traveling direction which accords with the built-in obstacle avoidance preferential traveling direction of the robot on all traveling routes to the sum of traveling times of the object traveling direction which accords with the built-in obstacle avoidance preferential traveling direction of the robot on all traveling routes, and P4 is the ratio of the sum of the safety coefficients of the object traveling direction which does not accord with the built-in obstacle avoidance preferential traveling direction of the robot on all traveling routes; for example, when the built-in obstacle avoidance priority travel direction is a left lateral translation, p1= (tm11+tm21+).
+TMQ1)/(PE11+PE21+......+PEQ1)，P2＝(TM12+TM22+......+TMQ2)/(PE12+PE22+......+PEQ2)，P3＝(SF11+SF21+......+SFQ1)/(TM11+TM21+......+TMQ1)，P4＝(SF12+SF22+......+SFQ2)/(TM12+TM22+......+TMQ2)。
S0003, if P2/P1 > the first value and P4/P3 > the second value, increasing the adjustable floating value and modifying the built-in obstacle avoidance priority driving direction. The first value and the second value are preset values greater than 1, preferably, the first value and the second value are values greater than 1.5, and the first value and the second value are different, so that the third preset weight beta can be adaptively regulated and controlled, and the subsequent target running direction of the robot can be regulated. Increasing the magnitude of the adjustable float value can be set by itself.
Through the steps S0001-S0003, beta can be continuously updated, so that an obstacle avoidance scheme which is more in line with the actual running road condition is provided, and the safety of the robot is improved.
The embodiment of the application also provides a robot obstacle avoidance system, which comprises a processor and a non-transitory computer readable storage medium, wherein the storage medium is used for storing at least one instruction or at least one section of program, and the processor loads and executes the at least one instruction or the at least one section of program to realize the robot obstacle avoidance method disclosed in any one of the previous embodiments.
Another embodiment of the present application also discloses a computer-readable storage medium storing a program or instructions that cause a computer to execute the method provided in the above embodiment.
Embodiments of the present application also provide an electronic device comprising a processor and the aforementioned non-transitory computer-readable storage medium.
Embodiments of the present application also provide a computer program product comprising program code for causing an electronic device to carry out the steps of the method according to the various exemplary embodiments of the application as described in the specification, when said program product is run on the electronic device.
While certain specific embodiments of the application have been described in detail by way of example, it will be appreciated by those skilled in the art that the above examples are for illustration only and are not intended to limit the scope of the application. Those skilled in the art will also appreciate that many modifications may be made to the embodiments without departing from the scope and spirit of the application. The scope of the application is defined by the appended claims.
Claims (10)
1. The robot obstacle avoidance method is characterized by comprising the following steps of:
s100, acquiring an obstacle distance information set d= { (X1, Y1), (X2, Y2), (Xi, yi), (Xn, yn) } in a detectable range in a driving direction of the robot at the current moment, wherein (Xi, yi) is distance information of an ith detected point on the obstacle, xi is a coordinate value of the ith detected point on an X-axis of a first preset coordinate system, and Yi is a coordinate value of the ith detected point on a Y-axis of the first preset coordinate system; i is in the range of 1 to n, n is the total number of detected points on the obstacle; the first preset coordinate system takes the geometric center of the current robot as an origin, takes the current running direction of the robot as an x-axis positive direction, and takes the direction of the current running direction rotated 90 degrees anticlockwise as a y-axis positive direction;
s200, constructing an external rectangle of the obstacle according to the obstacle distance information set D;
and S300, when the robot runs to a first distance threshold from the circumscribed rectangle, obtaining a target running direction based on the circumscribed rectangle, and continuing running according to the target running direction, wherein the continuous running mode comprises straight running and translation.
2. The robotic obstacle avoidance method of claim 1 wherein the circumscribed rectangle comprises at least a first rectangle;
s200 specifically comprises:
s201, taking the obstacle distance information set D as a target input data set of an external rectangle acquisition function to obtain the first rectangle;
the external rectangle obtaining function executes the following steps:
s001, acquiring a longitudinal maximum value and a longitudinal minimum value of the obstacle according to the target input data set, wherein the longitudinal maximum value is the maximum value of x-axis coordinate values of all detected points in the target input data set, and the longitudinal minimum value is the minimum value of x-axis coordinate values of all detected points in the target input data set;
s002, acquiring a transverse maximum value and a transverse minimum value of the obstacle according to the target input data set, wherein the transverse maximum value is the maximum value of y-axis coordinate values of all detected points in the target input data set, and the transverse minimum value is the minimum value of y-axis coordinate values of all detected points in the target input data set;
s003, outputting a minimum circumscribed rectangle based on a longitudinal maximum value, a longitudinal minimum value, a transverse maximum value and a transverse minimum value, wherein (the longitudinal maximum value, the transverse maximum value), (the longitudinal maximum value, the transverse minimum value), (the longitudinal minimum value, the transverse maximum value), (the longitudinal minimum value and the transverse minimum value) are four vertexes of the minimum circumscribed rectangle.
3. The robot obstacle avoidance method of claim 2 wherein the circumscribed rectangle further comprises a plurality of first sub-rectangles;
s200 further includes:
s202, acquiring a rectangular division point value pair S= { (Y) based on the obstacle distance information set D 1,1 ，Y 1,2 )，(Y 2,1 ，Y 2,2 )，......，(Y j,1 ，Y j,2 )，......，(Y m,1 ，Y m,2 ) }, wherein Y 1,1 ＞Y 1,2 ＞Y 2,1 ＞Y 2,2 ＞......＞Y j,1 ＞Y j,2 ＞......＞Y m,1 ＞Y m,2 ，(Y j,1 ，Y j,2 ) Dividing the value pair of points for the j-th rectangle, Y j,1 ∈{Y1，Y2，......，Yi，......，Yn}，Y j,2 ∈{Y1，Y2，......，Yi，......，Yn}，Y j,1 And Y j,2 Adjacent, and Y j,1 -Y j,2 The value range of j is 1 to m, and m is the number of rectangular dividing point value pairs; a first preset interval threshold = robot width + lateral extension float space threshold, and the lateral extension float space threshold is greater than 0;
s203, traversing all the value pairs in the value pairs S of the rectangular dividing points, and constructing m+1 sub-obstacle distance information sets E of the obstacle based on the transverse maximum value and the transverse minimum value 1 、E 2 、......、E k 、......、E m+1 ；E k For the k-th sub-obstacle distance information set, the value of k is 1, 2.
Wherein when k is 2.ltoreq.m, Y is based on k-1,2 Corresponding detected point Y k,1 Corresponding detected point Y k-1,2 And Y k,1 Distance information of all detected points included in the distance information set E, and a kth sub-obstacle distance information set E is obtained k ；
When k=1, based on Y 1,1 Corresponding detected point, detected point corresponding to the transverse maximum value, Y 1,1 And distance information of all detected points included between the transverse maximum values, obtaining a 1 st sub-obstacle distance information set E 1 ；
When k=m+1, based on Y m,2 Corresponding detected point, detected point corresponding to the transverse minimum value, Y m,2 And distance information of all detected points included between the transverse minimum values, obtaining an (m+1) th sub-obstacle distance information set E m+1 ；
S204, the kth sub-obstacle distance information set E k And a target input data set serving as the circumscribed rectangle acquisition function is used for obtaining a kth first sub-rectangle.
4. The robot obstacle avoidance method according to claim 3, wherein a target traveling direction is obtained based on the circumscribed rectangle, and traveling is continued in accordance with the target traveling direction, comprising the steps of:
s310, acquiring a first distance D relative to the global path when the robot transversely translates to the right to a first position Tm+1 and transversely translates to the left to a second position Tm+2 respectively based on global path information corresponding to the robot when the robot travels to a first distance threshold from the circumscribed rectangle 1 And a second distance D 2 The method comprises the steps of carrying out a first treatment on the surface of the Wherein min (Y1, Y2,) is..., yn) -TDm +1 is greater than or equal to a second distance threshold, TDm +2-max (Y1, Y2,) is greater than or equal to a second distance threshold, TDm +1 is a Y-axis coordinate value of the first position tm+1 in the first preset coordinate system, and TDm +2 is a Y-axis coordinate value of the second position tm+2 in the first preset coordinate system;
s320, obtaining a third distance D between the robot and the destination in the global path information when the robot is located at the first position Tm+1 and the second position Tm+2 respectively 3 And a fourth distance D 4 ；
S330, based on the first distance D 1 Second distance D 2 Third distance D 3 Fourth distance D 4 Acquiring a first driving obstacle avoidance parameter L1 and a second driving obstacle avoidance parameter L2 of the robot, wherein l1=β (d 1) (α1d1+α2d3), l2=β (d 2) (α1d2+α2d4), wherein d1 represents lateral translation direction information when the robot is laterally translated to a position T1, d2 represents lateral translation direction information when the robot is laterally translated to the position T2, α1 is a first preset weight, α2 is a second preset weight, and β () is used for acquiring a third preset weight corresponding to different lateral translation directions;
s340, performing transverse translation according to the transverse translation direction corresponding to the smaller value in L1 and L2.
5. The robot obstacle avoidance method according to claim 3, wherein a target traveling direction is obtained based on the circumscribed rectangle, and traveling is continued in accordance with the target traveling direction, comprising the steps of:
s3100, based on global path information corresponding to when the robot travels to a first distance threshold from the circumscribed rectangle, acquiring relative path distances TD1, TD2, and tm+2 with respect to the global path when the robot is laterally translated to positions T1, T2, & gt, th, & gt, tm+2, respectively, wherein when h=m+1, min (Y1, Y2, & gt, yi, & gt, Y, & gt, yn) -TDm +1 is greater than or equal to a second distance threshold, TDm +1 is a Y-axis coordinate value of tm+1 in a first preset coordinate system, when h=m+2, TDm +2-max (Y1, Y2, & gt, yi, & gt, yn) is greater than or equal to a second distance threshold, TDm +2 is a Y-axis coordinate value of tm+2 in a first preset coordinate system,when 1.ltoreq.h.ltoreq.m, th= (Y) h,1 +Y h,2 )/2；
S3200, acquiring relative destination distances DD1, DD2, DDh, DDm +2 between the robots and the destinations in the global path information when the robots are located at the positions T1, T2, and the positions Th, and Tm, respectively;
s3300, based on the relative path distances TD1, TD2, TDh, tm+2, and the relative destination distances DD1, DD2, DDh, DDm +2, obtaining m+2 travel obstacle avoidance parameters M1, M2 for the robot, mh, mm+2. Wherein mh=β (dh) (α1tdh+α2ddh), dh represents lateral translation direction information when the robot is laterally translated to the position Th, α1 is a first preset weight, α2 is a second preset weight, and β () is used to obtain a third preset weight corresponding to different lateral translation directions;
s3400, performing lateral translation according to a lateral translation direction corresponding to a smaller value of M1, M2, mh.
6. The robot obstacle avoidance method according to claim 5, wherein when dh is in accordance with the obstacle avoidance priority travel direction built-in the robot, β (dh) =a preset initial value-an adjustable float value, and when dh is not in accordance with the obstacle avoidance priority travel direction built-in the robot, β (dh) =a preset initial value+an adjustable float value, the adjustable float value > 0.
7. The robotic obstacle avoidance method of claim 6, further comprising the steps of:
s0001, acquiring a travel data set w= { W1, W2, & gt, wq }, on all travel routes of the robot within a preset period, wherein the travel data wq= { TMq1, TMq2, PEq1, PEq2, SFq1, SFq }, on the Q-th travel route, the travel start point and the travel end point of different travel routes are at least one different, TMq1 is a sum of travel times of only left lateral translation of the target travel direction on the Q-th travel route, TMq2 is a sum of travel times of only right lateral translation of the target travel direction on the Q-th travel route, PEq1 is a sum of travel times of only left lateral translation of the target travel direction on the Q-th travel route, PEq is a sum of travel times of only right lateral translation of the target travel direction on the Q-th travel route, SFq is a safety coefficient of only left lateral translation of the target travel direction on the Q-th travel route, SFq is a safety coefficient of only left lateral translation of the Q-th travel route, and Q is a safety coefficient of the Q-th travel range of the Q, and Q is a value of the Q is taken;
s0002, acquiring obstacle avoidance indexes P1, P2, P3 and P4 in the obstacle avoidance preferential traveling direction which accords with the built-in obstacle avoidance preferential traveling direction of the robot based on a traveling data set W, wherein P1 is the ratio of the sum of traveling times of the object traveling direction which accords with the built-in obstacle avoidance preferential traveling direction of the robot on all traveling routes to the sum of corresponding travel times, P2 is the ratio of the sum of traveling times of the object traveling direction which does not accord with the built-in obstacle avoidance preferential traveling direction of the robot on all traveling routes to the sum of traveling times of the corresponding travel times, P3 is the ratio of the sum of safety coefficients of the object traveling direction which accords with the built-in obstacle avoidance preferential traveling direction of the robot on all traveling routes to the sum of traveling times of the object traveling direction which accords with the built-in obstacle avoidance preferential traveling direction of the robot on all traveling routes, and P4 is the ratio of the sum of the safety coefficients of the object traveling direction which does not accord with the built-in obstacle avoidance preferential traveling direction of the robot on all traveling routes;
s0003, if P2/P1 > the first value and P4/P3 > the second value, increasing the adjustable floating value and modifying the built-in obstacle avoidance priority driving direction.
8. The robot obstacle avoidance method of claim 1 wherein the robot further comprises a robotic arm that is telescopic along the current travel direction; the first distance threshold is obtained by the following steps:
s301, acquiring the current speed V1 of the robot at the current moment and the current state data of the mechanical arm, wherein the current state data of the mechanical arm at least comprises current fault information, current telescopic speed and current extended length;
s302, if the current fault information indicates that the mechanical arm is in a static fault state, the value range of the first distance threshold value is [ 1.5m+the current extended length, 3m+the current extended length ];
s303, if the current fault information indicates that the mechanical arm is in a normal contraction working state, and V1/t1 is less than or equal to a first preset deceleration increment value, the value range of the first distance threshold is [1.5m,3m ], wherein t1=current extended length/current contraction speed;
s304, if the current fault information indicates that the mechanical arm is in a normal contraction working state and V1/t1 is larger than a first preset deceleration increment value, the value range of the first distance threshold is [ 1.5m+current extended length-current expansion speed t2, 3m+current extended length-current expansion speed t2], wherein t2=v1/first preset deceleration increment value;
and S305, if the current fault information indicates that the mechanical arm is in a normal extending working state, the value range of the first distance threshold value is [ 1.5m+the whole arm length of the mechanical arm, 3m+the whole arm length of the mechanical arm ].
9. A robot obstacle avoidance system comprising a processor and a non-transitory computer readable storage medium storing at least one instruction or at least one program, wherein the processor loads and executes the at least one instruction or at least one program to implement the robot obstacle avoidance method of any of claims 1 to 8.
10. A computer-readable storage medium storing a program or instructions that cause a computer to execute the robot obstacle avoidance method according to any one of claims 1 to 8.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310912165.5A CN116719326A (en) | 2023-07-24 | 2023-07-24 | Robot obstacle avoidance method, system and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310912165.5A CN116719326A (en) | 2023-07-24 | 2023-07-24 | Robot obstacle avoidance method, system and storage medium |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN116719326A true CN116719326A (en) | 2023-09-08 |
Family
ID=87871695
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310912165.5A Pending CN116719326A (en) | 2023-07-24 | 2023-07-24 | Robot obstacle avoidance method, system and storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116719326A (en) |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2017041730A1 (en) * | 2015-09-09 | 2017-03-16 | 北京进化者机器人科技有限公司 | Method and system for navigating mobile robot to bypass obstacle |
| CN110815202A (en) * | 2018-08-07 | 2020-02-21 | 杭州海康机器人技术有限公司 | Obstacle detection method and device |
| WO2021238001A1 (en) * | 2020-05-29 | 2021-12-02 | 苏州科瓴精密机械科技有限公司 | Robot travelling control method and system, robot, and readable storage medium |
| CN114489050A (en) * | 2021-12-31 | 2022-05-13 | 坎德拉（深圳）科技创新有限公司 | Obstacle avoidance route control method, device, equipment and storage medium for straight line driving |
| CN115437384A (en) * | 2022-10-20 | 2022-12-06 | 山东新一代信息产业技术研究院有限公司 | Obstacle avoidance method, equipment and medium for mobile robot |
| CN115903843A (en) * | 2022-12-21 | 2023-04-04 | 国广顺能(上海)能源科技有限公司 | Avoidance method of mobile charging robot |
-
2023
- 2023-07-24 CN CN202310912165.5A patent/CN116719326A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2017041730A1 (en) * | 2015-09-09 | 2017-03-16 | 北京进化者机器人科技有限公司 | Method and system for navigating mobile robot to bypass obstacle |
| CN110815202A (en) * | 2018-08-07 | 2020-02-21 | 杭州海康机器人技术有限公司 | Obstacle detection method and device |
| WO2021238001A1 (en) * | 2020-05-29 | 2021-12-02 | 苏州科瓴精密机械科技有限公司 | Robot travelling control method and system, robot, and readable storage medium |
| CN114489050A (en) * | 2021-12-31 | 2022-05-13 | 坎德拉（深圳）科技创新有限公司 | Obstacle avoidance route control method, device, equipment and storage medium for straight line driving |
| CN115437384A (en) * | 2022-10-20 | 2022-12-06 | 山东新一代信息产业技术研究院有限公司 | Obstacle avoidance method, equipment and medium for mobile robot |
| CN115903843A (en) * | 2022-12-21 | 2023-04-04 | 国广顺能(上海)能源科技有限公司 | Avoidance method of mobile charging robot |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US11460311B2 (en) | Path planning method, system and device for autonomous driving | |
| CN112673234B (en) | Path planning method and path planning device | |
| KR102495412B1 (en) | Materials handling vehicle path validation and dynamic path modification | |
| Ayawli et al. | Mobile robot path planning in dynamic environment using Voronoi diagram and computation geometry technique | |
| CN111089594B (en) | Autonomous parking trajectory planning method suitable for multiple scenes | |
| EP4180894A1 (en) | Method and device for planning obstacle avoidance path for traveling device | |
| CN112810630A (en) | Method and system for planning track of automatic driving vehicle | |
| CN110867131A (en) | Method, apparatus, device and storage medium for updating map | |
| CN113635898A (en) | Method, apparatus, storage medium, and program product for vehicle speed limit control | |
| JP7047576B2 (en) | Cartography device | |
| JP2007328486A (en) | Moving robot | |
| CN114670823A (en) | Method, device and equipment for correcting running track and automatic driving vehicle | |
| CN114475585B (en) | Automatic intersection driving method and device, electronic equipment and automatic driving vehicle | |
| Vailland et al. | Cubic bézier local path planner for non-holonomic feasible and comfortable path generation | |
| CN116719326A (en) | Robot obstacle avoidance method, system and storage medium | |
| CN113759892A (en) | Unmanned vehicle obstacle detouring method and device, unmanned vehicle and storage medium | |
| WO2023137938A1 (en) | Path planning method and apparatus for virtual character, electronic device, and storage medium | |
| Xu et al. | A hybrid receding horizon control method for path planning in uncertain environments | |
| CN115535003A (en) | Intersection control method, device, electronic device and medium for automatically driving vehicle | |
| CN113401141B (en) | Route processing method and device | |
| CN113501000A (en) | Method, apparatus, storage medium, and program product for vehicle speed limit control | |
| CN112650238A (en) | Real-time path planning method using visibility information | |
| US20190086216A1 (en) | Map data update system and non-transitory computer-readable storage medium | |
| CN114355921B (en) | Vehicle tracking track generation method and device, electronic equipment and storage medium | |
| CN116540748B (en) | Method and system for planning robot bypass path on navigation path |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |