CN109782756A - With independently around the Intelligent Mobile Robot of barrier walking function - Google Patents
With independently around the Intelligent Mobile Robot of barrier walking function Download PDFInfo
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Abstract
The invention discloses a kind of with independently around the Intelligent Mobile Robot of barrier walking function, mainly including robot control system, the global high accuracy positioning that is connected with robot control system and around hindering navigation system；The overall situation high accuracy positioning and mainly include carrier phase real time dynamic differential GPS, Inertial Measurement Unit, laser radar around barrier navigation system, for accurately providing position and course information of the robot in substation, perceives the barrier in environment-identification；By crusing robot progress path planning and autonomous inspection and avoidance based on feeler navigation algorithm, the autonomous around barrier walking function of robot is realized.High-precision, high-frequency Global localization can be achieved in the present invention, and realize that the autonomous inspection of robot and avoidance are walked based on feeler navigation algorithm, the complex environment adaptability and task for being obviously improved Intelligent Mobile Robot complete efficiency, reduce manual intervention, improve full utonomous working duration.
Description
Technical field
The present invention relates to the automation of transformation substations and robot fields, have independently more particularly to one kind around barrier walking function
Intelligent Mobile Robot.
Background technique
With the continuous development of science and technology, the intelligence electricity characterized by " information-based, digitlization automates, interactive "
Gradually deeply, robot used for intelligent substation patrol is included in that " first emphasis of State Grid Corporation of China spreads the new technique mesh for net construction
Record ", robot used for intelligent substation patrol enters the popularization and application stage.Applied robot's routine is maked an inspection tour, meter is made a copy of and automatic
The functions such as comparative analysis, bad weather tour, infrared accurate thermometric, the automatic archive analysis in backstage are stored, change is effectively promoted
Power station routing inspection efficiency and benefit alleviate the work load of teams and groups, base worker at the production line.
As Intelligent Mobile Robot continues strengthened research, some urgent problems to be solved are also exposed, wherein leading
A main problem in terms of boat function is exactly: since the airmanship that current crusing robot uses is limited, when inspection route
On when there is barrier or the region and carrying out service work, crusing robot cannot be identified and be detoured in real time, need work people
Member gets around barrier by artificial treatment barrier or remote manual control robot.This not only influences inspection machine task efficiency
With substation adaptability, and the workload of staff is also added, reduces robot inspection and replace manually patrolling
The benefit of inspection.
Therefore it is urgent to provide it is a kind of it is novel have independently solved around the Intelligent Mobile Robot of barrier walking function
State problem.
Summary of the invention
Technical problem to be solved by the invention is to provide a kind of with independently around the substation inspection machine of barrier walking function
Device people, being capable of high-precision, high-frequency Global localization and autonomous inspection and avoidance walking.
In order to solve the above technical problems, one technical scheme adopted by the invention is that: it provides a kind of with independently around barrier row
The Intelligent Mobile Robot of function is walked, mainly includes robot control system, the overall situation height being connected with robot control system
Precision positions and around barrier navigation system；
It is described the overall situation high accuracy positioning and around barrier navigation system mainly include carrier phase real time dynamic differential GPS, inertia
Measuring unit, laser radar perceive in environment-identification for accurately providing position and course information of the robot in substation
Barrier；
By crusing robot progress path planning and autonomous inspection and avoidance based on feeler navigation algorithm, machine is realized
People's is autonomous around barrier walking function.
In a preferred embodiment of the present invention, the method that the crusing robot carries out path planning are as follows:
S101: the globally consistent priori environment cartographic model of substation is established offline using laser radar；
S102: it is matched using the scanning result of laser radar with globally consistent priori environment map, obtains current machine
The estimation of device people position and course；
S103: using Inertial Measurement Unit to carrier phase real time dynamic differential GPS and based on the method for map match into
Row interpolation realizes that high-precision of the crusing robot in substation is positioned with high-frequency.
Further, the specific steps of step S103 include:
S103.1: the robot control system receives the word from carrier phase real time dynamic differential GPS using serial ports
Symbol string, every bag data mainly includes longitude and latitude, height above sea level, speed；
S103.2: the robot control system is according to pre-set communication in carrier phase real time dynamic differential GPS
String data is parsed longitude and latitude and altitude information by agreement；
S103.3: the longitude and latitude parsed and altitude coordinates are converted into the rectangular co-ordinate under WGS84 coordinate system, then become
The rectangular co-ordinate being changed under topocentric coordinate system obtains the estimation of crusing robot current location；
S103.4: the 3-axis acceleration of Inertial Measurement Unit and three axis angular rates are integrated, the fortune of crusing robot is obtained
Dynamic estimation, including position, posture, speed, and using the result of Inertial Measurement Unit integral to carrier phase real time dynamic differential
The positioning result of GPS carries out linear interpolation.
In a preferred embodiment of the present invention, the autonomous inspection based on feeler navigation is wrapped with the step of obstacle avoidance algorithm
It includes:
S201: the period is executed at each, obtains the data of the laser radar, part is established according to the data and occupies grid
Lattice map；
S202: a series of virtual feelers are generated；
S203: the grating map established using step S201 judges the passability of each virtual feeler；
S204: optimal feeler is chosen simultaneously at a distance from destination path according to the passable distance of crusing robot and feeler
It executes.
Further, in step S201, local grid map is established with the lattice dimensions specification of 0.1m*0.1m, with inspection
The artificial origin of machine establishes cartesian coordinate system, is converted to cartesian coordinate according to laser radar range result, falls in and work as front gate
Lattice, 1 is set by its corresponding grid point value that occupies, is otherwise provided as 0, and then generates part and occupies grating map.
Further, in step S202, the geometry form of the virtual feeler simulated hexapod feeler, it is assumed that symbiosis is at n
Group feeler, every group of feeler have m feeler, and corresponding crusing robot, which has, executes route in n*m；
The linear velocity v of every group of feelerjCalculation formula such as formula (1):
Wherein, vmax=1m/s, vmin=0.2m/s, n >=1；
The radius r of every group of feelerkCalculation formula such as formula (2):
Wherein,ρ=1.15 (constant)；
The arc length l of every group of feelerkCalculation formula such as formula (3):
Further, m is odd number.
Further, in step S203, each virtual passable judgment criteria of feeler are as follows:
If crusing robot is greater than current robot most at a distance from the nearest barrier in preantenna respective path
Short braking distance, then it is assumed that this paths is passable.
Further, the specific steps of step S203 include:
S203.1: assuming that when the passable region of preantenna is classification area, speed and radius are dc, best feeler region
For Support, speed and radius are ds, dc<ds, the speed of crusing robot is v, it sets:
Each Support and classification area correspond to several grids in local grid map respectively；
S203.2: it will be decomposed into when preantenna by nhThe histogram that a primitive is constituted, for each in current class area
A grid obtains corresponding histogram primitive number k respectively to the histogram rectangular projectioni, calculation formula such as formula (5):
L=θ rk
Wherein, rkFor when the radius of preantenna, θ is the horizontal sextant angle of grid projection line to be calculated, l is the arc when preantenna
It is long, lkFor the arc length between grid projection line to be calculated and horizontal line；
S203.3: one is defined by nwHistogram sliding window (the n that a histogram primitive is constitutedw< nh), it is obtained in step S203.2
To histogram on move sliding window to terminal from the off to traverse entire histogram, and histogram pair in sliding window is counted with this
The sum of numerical value is answered, if should and be greater than threshold value ns(ns>=1), then it is assumed that the corresponding position of sliding window starting point is exactly apart from robot at this time
The position of nearest barrier, then can calculate at a distance from nearest barrier.
Further, in step S204, first to feeler at a distance from nearest barrier, feeler is at a distance from given route
Be normalized, then passable feeler give a mark using formula (6) and therefrom select one it is best:
SFeeler=SAt a distance from nearest barrier+αSAt a distance from given route (6)
Wherein, [0, ∞] α ∈.
The beneficial effects of the present invention are:
(1) intelligent inspection robot of the present invention is perceived by high accuracy positioning and environmental scanning, can evade inspection automatically
It repairs region or automatically bypasses barrier walking, recover immediately set inspection route walking again after cut-through object；
(2) high-precision, high-frequency Global localization can be achieved in the present invention, and realizes robot based on feeler navigation algorithm
Autonomous inspection and avoidance are walked, and the complex environment adaptability and task for being obviously improved Intelligent Mobile Robot complete efficiency,
Reduce manual intervention, improves full utonomous working duration；
(3) present invention has the function of Global localization ability and around hindering, and significant increase crusing robot is in different substation
Arrange the robust adaptability of crusing robot after the convenience used and substation change.
Detailed description of the invention
Fig. 1 is that the present invention has independently around the structural block diagram of the Intelligent Mobile Robot of barrier walking function；
Fig. 2 is the flow chart of the autonomous inspection based on feeler navigation and obstacle avoidance algorithm；
Fig. 3 is the schematic diagram that the part occupies grating map update mode；
Fig. 4 is the schematic diagram that the part established occupies grating map；
Fig. 5 is the schematic diagram of different groups of virtual feelers；
Fig. 6 is the schematic diagram that crusing robot linear velocity is calculated according to feeler linear velocity；
Fig. 7 is the geometric shape schematic diagram of the Support；
Fig. 8 is the geometric shape schematic diagram in the classification area；
Fig. 9 is the schematic diagram of the histogram；
Figure 10 is the schematic diagram for calculating feeler and nearest obstacle distance.
Specific embodiment
The preferred embodiments of the present invention will be described in detail with reference to the accompanying drawing, so that advantages and features of the invention energy
It is easier to be readily appreciated by one skilled in the art, so as to make a clearer definition of the protection scope of the present invention.
Fig. 1 and Fig. 2 are please referred to, the embodiment of the present invention includes:
It is a kind of with independently around barrier walking function Intelligent Mobile Robot, mainly include robot control system, with
The connected global high accuracy positioning of robot control system and around barrier navigation system.It is described the overall situation high accuracy positioning and around barrier navigate
System mainly includes carrier phase real time dynamic differential GPS (RTK), Inertial Measurement Unit (IMU), laser radar.The intelligence
Crusing robot and the GPS of base station carry out information transmission and interaction and accurately provide machine by merging the data of these three sensors
Position and course information of the device people in substation perceive the barrier in environment-identification, carry out path by crusing robot
The autonomous around barrier walking function of robot is realized in planning and autonomous inspection and avoidance based on feeler navigation algorithm.
Firstly, the crusing robot needs global high accuracy positioning, the method for carrying out path planning are as follows:
RTK GPS can realize the Global localization precision of Centimeter Level in an ideal case, however be easy be blocked Deng environment
It influences and positioning accuracy is caused sharply to decline.For the robustness for ensureing crusing robot operation, the positioning side based on map is added
Method.Firstly, establishing the globally consistent priori environment cartographic model of substation offline using laser radar, and in robot reality
When operation, using the scanning result and priori map match of laser radar, the estimation in current robot position and course is obtained, from
And ensure the still available high-precision positioning result in RTK GPS satellite signal losing lock.
By the constraint of crusing robot cost and vehicle computing platform, either still it is based on ground based on RTK GPS
Scheme matched method, the positioning result of high-frequency (usually requiring that > 10Hz) can not be all provided, this also gives the quick of crusing robot
Smooth motion brings very big challenge.Therefore, the present invention to RTK GPS and is based on map using Inertial Measurement Unit (IMU)
The method matched carries out interpolation, to realize that high-precision of the crusing robot in substation is positioned with high-frequency.Its main algorithm
Process is as follows:
1) robot control system receives the character string from RTK GPS using serial ports, and every bag data mainly includes as follows
Several contents: longitude and latitude, height above sea level and velocity information etc..When the position identifiers of RTK is " NARROW_INT ", illustrate RTK
GPS comes into differential state, can reach the other positioning accuracy of Centimeter Level at this time；When position identifiers is " NARROW_FLOAT "
When, it can reach the other positioning accuracy of decimeter grade；
2) string data is parsed longitude and latitude and height above sea level by the communication protocol defined according to RTK GPS manufacturer；
3) rectangular co-ordinate under WGS84 coordinate system is converted to according to the longitude and latitude and altitude coordinates that parse, then again
Coordinate is transformed to the rectangular co-ordinate under topocentric coordinate system, to obtain the estimation of carrier current location；
4) 3-axis acceleration of IMU and three axis angular rates are integrated, obtain the estimation of carrier, including position, posture,
Speed, and linear interpolation is carried out using positioning result of the result of IMU integral to RTK GPS, to improve the frequency of positioning result
Rate.
For the automatic obstacle avoiding path planning for realizing crusing robot, the invention also provides one kind to be based on feeler navigation algorithm
Autonomous inspection and obstacle avoidance algorithm.Its basic thought is to imitate the barrier-avoiding method with feeler insect, generates touching for robot artificial
Angle simultaneously detects travelable region.
To describe respectively from following four parts below: first part is setting for robot size and some basic parameters
It is fixed；Second part is the explanation to creation and the update for occupying grating map；Part III is to virtual feeler structure and generation
The introduction of mode；Part IV is the introduction of the mechanism for the feeler that can be executed by feeler and finally to selection.
1) robot size and preset parameter
According to the performance of crusing robot motion platform and entrained sensor, this algorithm implementation phase using with
Next group of parameter:
Robot size: 0.4m × 0.4m；
Robot cruising speed: 0.2m/s -1m/s；
Laser radar range angle: 0 ° -180 °；
Laser radar range range: 0.2m -5m；
Lattice dimensions specification: 0.1m × 0.1m；
Grating map size: 10m × 5m.
2) grating map is occupied
For convenience of obstacle detection is carried out, needs to establish and local occupy grating map.According to lattice dimensions and grid in 1)
The size of lattice map is it is found that in the present embodiment, establish the local grid map being made of 100 × 50 grids.By
In the laser radar be two-dimensional laser radar, therefore as shown in figure 3, occupying grid update mode are as follows: if a certain laser radar
Distance measurement result falls in current grid after being converted to cartesian coordinate system, then its corresponding grid point value that occupies is set as 1, otherwise
It is set to 0.Fig. 4 show the local grid map generated using laser radar range result.
3) virtual feeler structure and generating mode
N=9 group feeler is used in the present embodiment altogether, each group of feeler has m=17 feeler again, as shown in figure 5, because
This shares 17 × 9=153 feeler, has corresponded to the totally 153 kinds of execution route selections of robot subsequent time.Every group of feeler corresponding one
The speed of a determination, distribution vmin—vmax, in the present embodiment, corresponding is 0.2m/s -1m/s.Each group pair
The speed calculation formula answered is as follows:
Wherein, n arrives just infinite positive integer for 1.From above-mentioned formula as can be seen that n value it is smaller when VELOCITY DISTRIBUTION more
Intensively, distribution is more sparse when opposite fast speed.
Feeler can also obtain its corresponding radius and arc after the speed for obtaining every group of feeler using the form of circular arc
It is long, it just can determine that the shape of the feeler.The calculation formula of its radius is as follows:
Wherein,ρ=1.15 (constant)；
The calculation formula of its arc length is as follows:
After linear velocity, arc length and radius that arc-shaped feeler has been determined, so that it may the linear speed of unique corresponding robot
Degree and angular speed, calculation method is as shown in fig. 6, calculation formula is as follows:
V=(vr+vl)/2, vl/vr=(R-L)/R
Wherein, vrIt is crusing robot right wheel speed, vlIt is crusing robot revolver speed, R is the radius of feeler, and L is to patrol
The axle length of robot is examined, v is the corresponding linear velocity of feeler, can calculate the linear velocity of crusing robot in this way.
After the geometry form of feeler is determined, it is thus necessary to determine that two regions.First region is Support, for grid
Each of lattice map grid, if it is less than d at a distance from the corresponding points on feelers, then belong to Support；Two Areas
It is classification area, similarly for each of grating map grid, if it is less than d at a distance from the corresponding points on feelerc, then belong to
In classification area, wherein dc<ds.Classification area is to work as whether preantenna can pass through for judgement, and Support is then same as selection " best "
Feeler.Its geometric shape indicates respectively as shown in Fig. 8,7.
If when the corresponding speed of preantenna is slower, it is contemplated that implementation procedure noise is also smaller, then dcIt may be configured as slightly big
It can guarantee safety in robot radius.When fast speed, process noise is larger, therefore dcBe also configured as one it is biggish
Value.When robot speed is minimum value 0.2m/s, dc is set as 0.25m.When speed reaches maximum value 1m/s, dc is set as
0.4m, and ds is set as 0.4m always.Its value set is shown below:
Since each feeler uniquely corresponds to radius and arc length, while corresponding to the d for determining valuecAnd ds, therefore
Also Support that is unique and determining and classification area are corresponded to, and clearly corresponds to the grid in grating map respectively.Assuming that wherein
One Support is by nsA grid composition:
For wherein any one grid Ci, Ci={ oi,ki,fi}.The use of four parameters is respectively as follows:
·oi: position of the grid in grating map is marked, (row serial number, column serial number)；
·ki: mark position number of the grid in histogram；
·fi: mark the grid whether in classification area, 1 represents the grid in classification area.
Work as whether preantenna can pass through to determine, while also determining and working as in preantenna at a distance from first barrier, it will
When preantenna is resolved by nhThe histogram that a primitive is constituted.It is straight to this respectively for each grid in current class area
Square figure rectangular projection obtains corresponding histogram primitive number ki, as shown in figure 9, the feeler center of circle is (0, r).
Calculation such as following formula:
L=θ rk
Wherein, rkFor when the radius of preantenna, θ is the horizontal sextant angle of grid projection line to be calculated, l is the arc when preantenna
It is long, lkFor the arc length between grid projection line to be calculated and horizontal line.
4) feeler selection mechanism
After obtaining the distance measurement result of laser radar, the grating map of a part is generated, the grid should be utilized at this time
Lattice map judges that the corresponding path of which feeler is passable.Definition can be by feeler: if robot with when preantenna pair
The distance of the nearest barrier on path is answered to be greater than the most short braking distance of current robot, then it is assumed that this paths is can to pass through
's.Therefore judge which feeler is passable, it should first calculating robot with work as it is nearest in preantenna respective path
The distance of barrier.
One is defined by n in conjunction with Figure 10 for the distance for calculating nearest barrierw=4 histogram primitives constitute straight
Square figure sliding window.It moves sliding window to terminal from the off to traverse entire histogram, and histogram in sliding window is counted with this and is corresponded to
The sum of numerical value, if should and be greater than threshold value ns=1, then it is assumed that the corresponding position of sliding window starting point is exactly to hinder recently apart from robot at this time
Hindering the position of object, then can calculate at a distance from nearest barrier, calculation formula s=x/n*l, wherein l is feeler length,
N is the sum of grid in histogram, and x is which histogram is sliding window be moved to.
Passable feeler can be separated by the above method, next be the road according to crusing robot
Diameter inspection and avoidance demand select the feeler for being best suitable for demand to execute.
Since crusing robot needs avoiding barrier during inspection to guarantee safety, it is therefore desirable to will be with nearest barrier
Hinder the distance of object as the one aspect for measuring feeler.On the other hand, crusing robot needs to carry out set polling path
Tracking, it is therefore desirable to which feeler end is enabled into an importance as measurement feeler superiority and inferiority at a distance from given route
With passable feeler give a mark with following formula and therefrom select one it is best:
SFeeler=SAt a distance from nearest barrier+αSAt a distance from given route, wherein α ∈ [0, ∞].
When giving a mark in terms of the avoidance in terms of two and inspection two, it should to feeler with nearest barrier at a distance from, touch
Angle is normalized at a distance from given route, then carries out comprehensive marking evaluation again, finally selects a scoring highest
Feeler as the feeler path currently needed to be implemented.
Intelligent inspection robot of the present invention is perceived by high accuracy positioning and environmental scanning, can evade maintenance area automatically
Domain automatically bypasses barrier walking, recovers immediately set inspection route walking again after cut-through object；It can be achieved high-precision
Degree, high-frequency Global localization, and realize that the autonomous inspection of robot and avoidance are walked based on feeler navigation algorithm, it is obviously improved
The complex environment adaptability and task of Intelligent Mobile Robot complete efficiency, reduce manual intervention, improve complete autonomous
Operating time；Have the function of Global localization ability and around barrier, significant increase crusing robot is arranged in different substation and used
Convenience and substation change after crusing robot robust adaptability.
The above description is only an embodiment of the present invention, is not intended to limit the scope of the invention, all to utilize this hair
Equivalent structure or equivalent flow shift made by bright specification and accompanying drawing content is applied directly or indirectly in other relevant skills
Art field, is included within the scope of the present invention.
Claims (10)
1. a kind of with independently around the Intelligent Mobile Robot of barrier walking function, which is characterized in that mainly include robot control
System processed, the global high accuracy positioning being connected with robot control system and around barrier navigation system；
It is described the overall situation high accuracy positioning and around barrier navigation system mainly include carrier phase real time dynamic differential GPS, inertia measurement
Unit, laser radar perceive the barrier in environment-identification for accurately providing position and course information of the robot in substation
Hinder object；
By crusing robot progress path planning and autonomous inspection and avoidance based on feeler navigation algorithm, robot is realized
Independently around barrier walking function.
2. according to claim 1 have independently around the Intelligent Mobile Robot of barrier walking function, which is characterized in that institute
State the method that crusing robot carries out path planning are as follows:
S101: the globally consistent priori environment cartographic model of substation is established offline using laser radar；
S102: it is matched using the scanning result of laser radar with globally consistent priori environment map, obtains current robot
The estimation of position and course；
S103: using Inertial Measurement Unit to carrier phase real time dynamic differential GPS and the method based on map match carry out it is slotting
It mends, realizes that high-precision of the crusing robot in substation is positioned with high-frequency.
3. according to claim 2 have independently around the Intelligent Mobile Robot of barrier walking function, which is characterized in that step
Suddenly the specific steps of S103 include:
S103.1: the robot control system receives the character string from carrier phase real time dynamic differential GPS using serial ports,
Every bag data mainly includes longitude and latitude, height above sea level, speed；
S103.2: the robot control system according to pre-set communication protocol in carrier phase real time dynamic differential GPS,
String data is parsed into longitude and latitude and altitude information；
S103.3: the longitude and latitude parsed and altitude coordinates are converted into the rectangular co-ordinate under WGS84 coordinate system, then are transformed to
Rectangular co-ordinate under topocentric coordinate system obtains the estimation of crusing robot current location；
S103.4: the 3-axis acceleration of Inertial Measurement Unit and three axis angular rates are integrated, and the movement for obtaining crusing robot is estimated
Meter, including position, posture, speed, and using the result of Inertial Measurement Unit integral to carrier phase real time dynamic differential GPS's
Positioning result carries out linear interpolation.
4. according to claim 1 have independently around the Intelligent Mobile Robot of barrier walking function, which is characterized in that institute
State the autonomous inspection based on feeler navigation includes: with the step of obstacle avoidance algorithm
S201: the period is executed at each, obtains the data of the laser radar, establishes part with occupying grid according to the data
Figure；
S202: a series of virtual feelers are generated；
S203: the grating map established using step S201 judges the passability of each virtual feeler；
S204: optimal feeler is chosen at a distance from destination path according to the passable distance of crusing robot and feeler and is held
Row.
5. according to claim 4 have independently around the Intelligent Mobile Robot of barrier walking function, which is characterized in that step
In rapid S201, local grid map is established with the lattice dimensions specification of 0.1m*0.1m, flute card is established with the artificial origin of inspection machine
Your coordinate system, is converted to cartesian coordinate according to laser radar range result, falls in current grid, its corresponding is occupied grid
Lattice value is set as 1, is otherwise provided as 0, and then generates part and occupy grating map.
6. according to claim 4 have independently around the Intelligent Mobile Robot of barrier walking function, which is characterized in that step
In rapid S202, the geometry form of the virtual feeler simulated hexapod feeler, it is assumed that at n group feeler, every group of feeler has m for symbiosis
Feeler, corresponding crusing robot, which has, executes route in n*m；
The linear velocity v of every group of feelerjCalculation formula such as formula (1):
Wherein, vmax=1m/s, vmin=0.2m/s, n >=1；
The radius r of every group of feelerkCalculation formula such as formula (2):
Wherein,ρ=1.15 (constant)；
The arc length l of every group of feelerkCalculation formula such as formula (3):
7. according to claim 6 have independently around the Intelligent Mobile Robot of barrier walking function, which is characterized in that m
For odd number.
8. according to claim 4 have independently around the Intelligent Mobile Robot of barrier walking function, which is characterized in that step
In rapid S203, each virtual passable judgment criteria of feeler are as follows:
If crusing robot and the most short brake for being greater than current robot at a distance from the nearest barrier in preantenna respective path
Vehicle distance, then it is assumed that this paths is passable.
9. according to claim 8 have independently around the Intelligent Mobile Robot of barrier walking function, which is characterized in that step
Suddenly the specific steps of S203 include:
S203.1: assuming that when the passable region of preantenna is classification area, speed and radius are dc, best feeler region is branch
Area is supportted, speed and radius are ds, dc<ds, the speed of crusing robot is v, it sets:
Each Support and classification area correspond to several grids in local grid map respectively；
S203.2: it will be decomposed into when preantenna by nhThe histogram that a primitive is constituted, for each grid in current class area
Lattice obtain corresponding histogram primitive number k respectively to the histogram rectangular projectioni, calculation formula such as formula (5):
L=θ rk
Wherein, rkFor when the radius of preantenna, θ is the horizontal sextant angle of grid projection line to be calculated, l is the arc length when preantenna, lk
For the arc length between grid projection line to be calculated and horizontal line；
S203.3: one is defined by nwHistogram sliding window (the n that a histogram primitive is constitutedw< nh), it is obtained in step S203.2
Sliding window is moved on histogram to terminal from the off to traverse entire histogram, and histogram in sliding window is counted with this and corresponds to number
The sum of value, if should and be greater than threshold value ns(ns>=1), then it is assumed that the corresponding position of sliding window starting point is exactly nearest apart from robot at this time
The position of barrier can then calculate at a distance from nearest barrier.
10. according to claim 4 have independently around the Intelligent Mobile Robot of barrier walking function, which is characterized in that
In step S204, first to feeler at a distance from nearest barrier, feeler be normalized at a distance from given route, so
Afterwards passable feeler give a mark using formula (6) and therefrom select one it is best:
SFeeler=SAt a distance from nearest barrier+αSAt a distance from given route (6)
Wherein, [0, ∞] α ∈.
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| CN111599031A (en) * | 2020-04-16 | 2020-08-28 | 江苏方天电力技术有限公司 | Inspection data acquisition and analysis method and system for power inspection robot |
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| CN112241171A (en) * | 2020-10-09 | 2021-01-19 | 国网江西省电力有限公司检修分公司 | Wheeled robot linear track tracking method capable of winding obstacles |
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| CN113359761A (en) * | 2021-07-02 | 2021-09-07 | 广东电网有限责任公司 | Routing planning method and device for inspection path of robot for transformer substation and storage medium |
| CN113534814A (en) * | 2021-08-04 | 2021-10-22 | 国网浙江省电力有限公司嘉兴供电公司 | Obstacle avoidance method for transformer substation operation robot |
| CN115494519A (en) * | 2022-11-04 | 2022-12-20 | 西安国智电子科技有限公司 | Navigation method and device of inspection robot, computer equipment and storage medium |
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