CN107943038A - A kind of mobile robot embedded laser SLAM method and system - Google Patents
A kind of mobile robot embedded laser SLAM method and system Download PDFInfo
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- 238000006073 displacement reaction Methods 0.000 claims description 6
- 238000006243 chemical reaction Methods 0.000 claims description 5
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0257—Control of position or course in two dimensions specially adapted to land vehicles using a radar
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0268—Control of position or course in two dimensions specially adapted to land vehicles using internal positioning means
- G05D1/0274—Control of position or course in two dimensions specially adapted to land vehicles using internal positioning means using mapping information stored in a memory device
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Abstract
This application discloses a kind of mobile robot embedded laser SLAM method and system, including:Robot operating system is built in embedded board in mobile robot;PC is connected remotely to by embedded board by wireless network, input order starts robot operating system, robotically-driven circuit board and laser radar;By laser radar, embedded board, Inertial Measurement Unit, direct current generator and magnetism encoder, sensing data is obtained;The establishment of map is carried out by the SLAM algorithms in sensing data combination embedded board, and is uploaded to PC;The map created by PC observation, and map is preserved.Since the application has built robot operating system in embedded board, after network connection, SLAM algorithms can be allow directly to run wherein, and then reduce the cost of mobile robot, system flexibility is improved, while makes the realization of SLAM more stable, directly perceived.
Description
Technical field
The present invention relates to mobile robot technology field, more particularly to a kind of mobile robot embedded laser SLAM side
Method and system.
Background technology
In recent years, mobile robot technology with the continuous development of scientific technology, constantly widens the application field of robot,
Society is also constantly being lifted for the demand of mobile robot, and mobile robot gradually incorporates industry, family expenses, commercialization, doctor
Role in the daily lifes such as treatment, service, security, the functional requirement to mobile robot are also continuously increased, and technical indicator is therewith
Lifting.
Immediately positioning and structure map (simultaneous localization and mapping, SLAM) technology are
Mobile robot realizes the key of independent navigation, in circumstances not known, surrounding is detected by sensor, constructs environment
Map, positions robot, so as to navigate with reference to the real-time map that sensor generates.In the research process of SLAM
In, the problem of sensor is unstable, is increasingly apparent, and researcher has found that visual sensor is easily affected by the ambient, and
And it is computationally intensive, but if during using PC (PC) as computation processor, equivalent to improving hardware configuration, and only taking up
The function of PC very small parts, causes function waste and cost increase.
In addition, robot operating system (Robot Operating System, ROS) is that robot software's operation is flat
Platform, predecessor is by Stanford University artificial intelligence study institute (Stanford Artificial Intelligence
Laboratory) researched and developed.Since SLAM can not directly be run in ROS, and when realizing algorithm by PC, do not deliver efficiently
Computer resource, produces the wasting of resources, while reduces the flexibility of mobile-robot system.
The content of the invention
In view of this, it is an object of the invention to provide a kind of mobile robot embedded laser SLAM method and system,
The cost of mobile robot can be reduced, improves system flexibility, while makes the realization of SLAM more stable, directly perceived.Its is specific
Scheme is as follows:
A kind of mobile robot embedded laser SLAM methods, including:
Robot operating system is built in embedded board in the mobile robot;
PC is connected remotely to by the embedded board by wireless network, input order starts the machine
People's operating system, the robotically-driven circuit board in the mobile robot, and the laser installed in the mobile robot
Radar;
By the laser radar, the embedded board, the inertia measurement list in the robotically-driven circuit board
Member, and the direct current generator and magnetism encoder being connected with the robotically-driven circuit board, obtain sensing data;
The wound of map is carried out with reference to the SLAM algorithms in the embedded board by the sensing data of acquisition
Build, and be uploaded to the PC;
The map created by PC observation, and the map is preserved.
Preferably, in above-mentioned mobile robot embedded laser SLAM methods provided in an embodiment of the present invention, institute is passed through
State laser radar, the embedded board, the Inertial Measurement Unit in the robotically-driven circuit board, and with the machine
The direct current generator and magnetism encoder of device people drive circuit board connection, obtain sensing data, specifically include:
Gather the topography and geomorphology situation of the indoor and outdoor surroundings where the mobile robot in real time by the laser radar,
Carry out the extraction of data;
The odometer being made up of direct current generator and magnetism encoder is to the indoor and outdoor surroundings where the mobile robot
Positioning and displacement, carry out the extraction of data;
Collected by the Inertial Measurement Unit in the robotically-driven circuit board and the embedded board described sharp
Optical radar and the odometer extraction data go forward side by side row information fusion, obtain sensing data.
Preferably, in above-mentioned mobile robot embedded laser SLAM methods provided in an embodiment of the present invention, by obtaining
The sensing data taken carries out the establishment of map with reference to the SLAM algorithms in the embedded board, specifically includes:
The closest approach iteration SLAM in mobile robot program-ming Toolbox function library is transplanted in the embedded board
Algorithm;
The sensor number using the robot operating system by the closest approach iteration SLAM algorithms to acquisition
According to being handled;
Leave out image displaying part in the robot operating system, adjustment matching way matches for grid map, generation
Grating map, and the track added in the robot operating system is shown.
Preferably, in above-mentioned mobile robot embedded laser SLAM methods provided in an embodiment of the present invention, institute is used
State robot operating system to handle the sensing data of acquisition by the closest approach iteration SLAM algorithms, specifically
Including:
The sensor number using the robot operating system by the closest approach iteration SLAM algorithms to acquisition
According to being scanned and matching, the motion change matrix of the mobile robot is solved;The motion change matrix includes rotation
Matrix and translation matrix;
Meanwhile real time kinematics track, self poisoning and the environment distribution of robot are calculated, carry out reflecting for grating map
Penetrate.
Preferably, in above-mentioned mobile robot embedded laser SLAM methods provided in an embodiment of the present invention, generating
During grating map, specifically further include:
The sensing data is verified using the embedded board;
When the data of odometer extraction show that the displacement of the mobile robot is less than given threshold, edge uses one
The grating map of secondary generation.
Preferably, in above-mentioned mobile robot embedded laser SLAM methods provided in an embodiment of the present invention, described
The robot operating system is installed in people's computer;
The internetwork connection mode of the PC and the embedded board uses the robot operating system
Slave method;
The embedded board is as slave;The PC is as host;The sensing data passes through described
Host is shown.
Preferably, in above-mentioned mobile robot embedded laser SLAM methods provided in an embodiment of the present invention, institute is passed through
The map that PC observation creates is stated, is specifically included:
Combine to carry using RVIZ image display interfaces on robot operating system platform in the PC and comment
Estimate the map that instrument is observed establishment.
Preferably, in above-mentioned mobile robot embedded laser SLAM methods provided in an embodiment of the present invention, to described
Map is preserved, and is specifically included:
The map is preserved using the map conserving appliance installed in the robot operating system, simultaneously for
The threshold value of three kinds of colors of black-white-gray is adjusted respectively in the map preserved.
Preferably, in above-mentioned mobile robot embedded laser SLAM methods provided in an embodiment of the present invention, the shifting
The DC power supply of mobile robot is directly connected to the robotically-driven plate;
Voltage conversion is carried out by the robotically-driven plate, the embedded board, direct current generator and magnetoelectricity are encoded
Device is powered;
The laser radar is powered by the embedded board.
The embodiment of the present invention additionally provides a kind of mobile robot embedded laser SLAM systems, including:
System building module, for building robot manipulation system in the embedded board in the mobile robot
System;
Network connecting module, it is defeated for PC to be connected remotely to the embedded board by wireless network
Enter order and start the robot operating system, the robotically-driven circuit board in the mobile robot, and the movement
The laser radar installed in robot;
Data acquisition module, for passing through the laser radar, the embedded board, the robotically-driven circuit
Inertial Measurement Unit in plate, and the direct current generator and magnetism encoder being connected with the robotically-driven circuit board, obtain
Sensing data;
Map building module, for the sensing data by acquisition with reference to the SLAM in the embedded board
Algorithm carries out the establishment of map, and is uploaded to the PC;
Map preserving module, carries out for the map created by PC observation, and to the map
Preserve
A kind of mobile robot embedded laser SLAM method and system provided by the present invention, including:In mobile machine
Robot operating system is built in embedded board in people;PC is connected remotely to by wireless network embedded
Development board, input, which is ordered, starts robot operating system, the robotically-driven circuit board in mobile robot, and mobile machine
The laser radar installed on people;By laser radar, embedded board, the inertia measurement list in robotically-driven circuit board
Member, and the direct current generator and magnetism encoder being connected with robotically-driven circuit board, obtain sensing data;Pass through acquisition
SLAM algorithms in sensing data combination embedded board carry out the establishment of map, and are uploaded to PC;By a
The map that the observation of people's computer creates, and map is preserved.Since the application has built robot in embedded board
Operating system, after network connection, can be such that SLAM algorithms directly run wherein, so reduce mobile robot into
This, improves system flexibility, while makes the realization of SLAM more stable, directly perceived.
Brief description of the drawings
In order to illustrate more clearly about the embodiment of the present invention or technical scheme of the prior art, below will be to embodiment or existing
There is attached drawing needed in technology description to be briefly described, it should be apparent that, drawings in the following description are only this
The embodiment of invention, for those of ordinary skill in the art, without creative efforts, can also basis
The attached drawing of offer obtains other attached drawings.
Fig. 1 is mobile robot embedded laser SLAM method flow diagrams provided in an embodiment of the present invention;
Fig. 2 is the relation schematic diagram for each node issued in robot operating system provided in an embodiment of the present invention.
Embodiment
Below in conjunction with the attached drawing in the embodiment of the present invention, the technical solution in the embodiment of the present invention is carried out clear, complete
Site preparation describes, it is clear that described embodiment is only part of the embodiment of the present invention, instead of all the embodiments.It is based on
Embodiment in the present invention, those of ordinary skill in the art are obtained every other without making creative work
Embodiment, belongs to the scope of protection of the invention.
The present invention provides a kind of mobile robot embedded laser SLAM methods, as shown in Figure 1, comprising the following steps:
Robot operating system is built in S101, the embedded board in mobile robot;
S102, by wireless network be connected remotely to embedded board by PC, and input order starts robot
Operating system, the robotically-driven circuit board in mobile robot, and the laser radar installed in mobile robot;
S103, by laser radar, embedded board, the Inertial Measurement Unit in robotically-driven circuit board, and
The direct current generator and magnetism encoder being connected with robotically-driven circuit board, obtain sensing data;
S104, the establishment by the SLAM algorithms progress map in the sensing data combination embedded board of acquisition,
And it is uploaded to PC;
S105, the map created by PC observation, and map is preserved.
In above-mentioned mobile robot embedded laser SLAM methods provided in an embodiment of the present invention, first in mobile machine
Robot operating system is built in embedded board in people;Then PC is connected remotely to by wireless network embedding
Enter formula development board, input, which is ordered, starts robot operating system, the robotically-driven circuit board in mobile robot, and mobile
The laser radar installed in robot;Afterwards by laser radar, embedded board, the inertia in robotically-driven circuit board
Measuring unit, and the direct current generator and magnetism encoder being connected with robotically-driven circuit board, obtain sensing data;Then
The establishment of map is carried out by the SLAM algorithms in the sensing data combination embedded board of acquisition, and is uploaded to personal electricity
Brain;The map created finally by PC observation, and map is preserved.By above-mentioned five steps, embedded
Robot operating system has been built in development board, after network connection, SLAM algorithms can have been allow directly to run wherein, obtained
Sensing data is taken, positioning in real time and structure map, finally observation can meet robot certainly with preserving map, the map of generation
The demand of leading boat, improves system flexibility, while makes the realization of SLAM more stable, directly perceived, and cost and hardware configuration will
Ask and substantially reduce.
It should be noted that mobile robot used in the present invention can use the mobile robot of two-wheel drive small
Car, hardware configuration can mainly include anti-pulley, universal wheel, DC power supply, direct current generator, and magnetism encoder is robotically-driven
Circuit board, embedded board, laser radar.Wherein, direct current generator and magnetism encoder, form the mileage of mobile robot
Meter, the reading of SLAM algorithm combination encoders can position robot;Robotically-driven circuit board, including stm32
(32 8-digit microcontrollers of STMicroelectronics), voltage conversion circuit, Inertial Measurement Unit (Inertial
Measurement unit, IMU) and special functional module, driven for direct current generator, while be directly connected to DC power supply,
Multiple and different output power supply interfaces are provided for mobile robot;Embedded board, by 64 four core ARM (Acorn RISC
Machine) microprocessor, a variety of peripheral interface circuits and wireless network circuit composition, the structure is by SLAM algorithms to receiving
To sensing data handled.
In the specific implementation, voltage conversion is carried out by robotically-driven plate, to embedded board, direct current generator and magnetoelectricity
Encoder is powered;Laser radar is powered by embedded board.
Further, in the specific implementation, in above-mentioned mobile robot embedded laser provided in an embodiment of the present invention
In SLAM methods, step S103 is by laser radar, embedded board, the inertia measurement list in robotically-driven circuit board
Member, and the direct current generator and magnetism encoder being connected with robotically-driven circuit board, obtain sensing data, can specifically wrap
Include following steps:
Step 1: the topography and geomorphology situation of the indoor and outdoor surroundings where gathering mobile robot in real time by laser radar,
Carry out the extraction of data;
Step 2: the odometer being made up of direct current generator and magnetism encoder is to the indoor outer shroud where mobile robot
The positioning and displacement in border, carry out the extraction of data;
Step 3: laser radar is collected by the Inertial Measurement Unit in robotically-driven circuit board and embedded board
With odometer extraction data go forward side by side row information fusion, obtain sensing data.
It should be noted that step 1 and step 2 in no particular order order, do not limit herein.
Further, in the specific implementation, in above-mentioned mobile robot embedded laser provided in an embodiment of the present invention
In SLAM methods, the SLAM algorithms in the sensing data combination embedded board that step S104 passes through acquisition carry out map
Create, specifically may comprise steps of:
First, the closest approach iteration SLAM in mobile robot program-ming Toolbox function library is transplanted in embedded board
Algorithm;
Then, using robot operating system by closest approach iteration SLAM algorithms to the sensing data of acquisition at
Reason;
Finally, image displaying part is left out in robot operating system, adjustment matching way matches for grid map, generation
Grating map, and the track added in robot operating system is shown.
In above-mentioned steps, SLAM algorithms use transplanting mobile robot program-ming Toolbox (Mobile Robot
Programming Toolkit, MRPT) closest approach iteration (Iterative Closest Point, ICP) in function library
SLAM algorithms, advantage are quick, accurate, and ICP-SLAM algorithms are improved and optimized, it is embedded to be transplanted to mobile robot
In development board (such as Raspberry Pi three generations), SLAM is finally realized, reduces the central processing unit (Central of algorithm operation
Processing Unit, CPU) occupancy, the speed of service of algorithm is improved, mobile robot is greatly reduced and realizes SLAM
Hardware configuration wants the cost of summation device.Also, on the basis of accurate rate is ensured, by by existing origin cloud atlas match party
Formula is modified as grid map matching, removes ICP-SLAM real-time displays interface, reduces demand of the algorithm to CPU calculation amounts, shortens
Algorithm operation is time-consuming.
It should be noted that robot operating system can establish node manager, checked from order line client specific
The message data that theme is constantly issued, the effective reusability for lifting code.Robot operating system includes various development tools
Program and library, can allow the process real-time display of SLAM and more directly perceived, and robot operating system supports multilingual
Design, such as C++, Python, Java etc..
Fig. 2 shows the relation schematic diagram for each node issued in robot operating system, and specifically, mobile robot opens
When dynamic, the robotically-driven circuit board of bottom, nodename turtlebot3_ can be started first in robot operating system
Core, which can carry out the data of encoder format conversion, and numerical nomenclature is issued for odom, by mrpt_
Icp_slam_live_2d nodes are responsible for reception, and the data of laser radar are then to be responsible for collection simultaneously by rplidarNode nodes
Issued with the theme of entitled scan, reception, the fortune of SLAM algorithms are equally responsible for by mrpt_icp_slam_live_2d nodes
Row by mentioned earlier be responsible for by mrpt_icp_slam_live_2d nodes, which receives the number for coming self-encoding encoder and laser radar
According to afterwards, ICP-SLAM algorithms are run, construct the real time kinematics grating map of mobile robot, and add complete movement rail
Mark.
Further, in the specific implementation, in above-mentioned mobile robot embedded laser provided in an embodiment of the present invention
In SLAM methods, using robot operating system by closest approach iteration SLAM algorithms to the sensing data of acquisition at
Reason, can specifically include:
By closest approach iteration SLAM algorithms the sensing data of acquisition is scanned using robot operating system and
Matching, solves the motion change matrix of mobile robot;Motion change matrix includes spin matrix and translation matrix;Meanwhile
Real time kinematics track, self poisoning and the environment distribution of robot are calculated, carries out the mapping of grating map.
Specifically, by the continuous iteration of adjacent two frames grating map data, the ICP- that is run in embedded board
The data that SLAM algorithms gather laser radar are matched with environment, and are tested to the reading of magnetism encoder, no
It is scanned and matches disconnectedly, it can be deduced that the motion change matrix of mobile robot, including spin matrix and translation matrix;It is logical
Surrounding environment combination sensing data can be carried out the mapping of grating map by crossing ICP-SLAM algorithms, constantly incrementally be carried out real
Shi Dingwei and synchronous structure map.
In the specific implementation, in above-mentioned mobile robot embedded laser SLAM methods provided in an embodiment of the present invention,
In order to further reduce the occupation rate of CPU, during grating map is generated, specifically further include:Use embedded board
Sensing data is verified;When the data of odometer extraction show that the displacement of mobile robot is less than given threshold, edge
With the grating map of last time generation.
In the specific implementation, in above-mentioned mobile robot embedded laser SLAM methods provided in an embodiment of the present invention,
In order to further improve the speed of service, robot operating system can be installed in PC and embedded board;It is a
The internetwork connection mode of people's computer and embedded board uses the slave method of robot operating system;Embedded board
As slave;PC is as host;Sensing data is shown by host.In addition, PC can use
Safety shell protocol (Secure Shell, the ssh) function of being installed in linux system carries out login embedded system, by this
Function carries out the control of robot using order line terminal.
Further, in the specific implementation, in above-mentioned mobile robot embedded laser provided in an embodiment of the present invention
In SLAM methods, in order to not only meet present robot research trend, but also the layout of actual environment is more intuitively reflected, led to
The map that PC observation creates is crossed, can specifically be included:Used on robot operating system platform in PC
RVIZ image display interfaces combine and carry the map that assessment tool is observed establishment.
Further, in the specific implementation, in above-mentioned mobile robot embedded laser provided in an embodiment of the present invention
In SLAM methods, in order to make map generation more directly perceived, when being preserved to map, it can specifically include:Use robot
The map conserving appliance installed in operating system preserves map, simultaneously for three kinds of colors of black-white-gray in the map of preservation
Threshold value be adjusted respectively.
Based on same inventive concept, the embodiment of the present invention additionally provides a kind of mobile robot embedded laser SLAM systems
System, should since the principle that the system solves the problems, such as is similar to a kind of foregoing mobile robot embedded laser SLAM methods
The implementation of system may refer to the implementation of mobile robot embedded laser SLAM methods, and overlaps will not be repeated.
In the specific implementation, mobile robot embedded laser SLAM systems provided in an embodiment of the present invention, specifically include:
System building module, for building robot operating system in the embedded board in mobile robot;
Network connecting module, for PC to be connected remotely to embedded board, input life by wireless network
Make and start robot operating system, the robotically-driven circuit board in mobile robot, and what is installed in mobile robot are swashed
Optical radar;
Data acquisition module, for by laser radar, embedded board, the inertia in robotically-driven circuit board is surveyed
Unit, and the direct current generator and magnetism encoder being connected with robotically-driven circuit board are measured, obtains sensing data;
Map building module, carries out for the SLAM algorithms in the sensing data combination embedded board by acquisition
The establishment of map, and it is uploaded to PC;
Map preserving module, for the map created by PC observation, and preserves map.
In above-mentioned mobile robot embedded laser SLAM systems provided in an embodiment of the present invention, pass through above-mentioned five moulds
The interaction of block, can reduce mobile robot and realize that SLAM hardware configurations want the cost of summation device, it is flexible to improve system
Property, while make the realization of SLAM more stable, directly perceived.
A kind of mobile robot embedded laser SLAM method and system provided in an embodiment of the present invention, including:In movement
Robot operating system is built in embedded board in robot;PC is connected remotely to by wireless network embedding
Enter formula development board, input, which is ordered, starts robot operating system, the robotically-driven circuit board in mobile robot, and mobile
The laser radar installed in robot;By laser radar, embedded board, the inertia measurement in robotically-driven circuit board
Unit, and the direct current generator and magnetism encoder being connected with robotically-driven circuit board, obtain sensing data;Pass through acquisition
Sensing data combination embedded board in SLAM algorithms carry out the establishment of map, and be uploaded to PC;Pass through
The map that PC observation creates, and map is preserved.Since the application has built machine in embedded board
People's operating system, after network connection, can be such that SLAM algorithms directly run wherein, and then reduce mobile robot
Cost, improves system flexibility, while makes the realization of SLAM more stable, directly perceived.
Finally, it is to be noted that, herein, relational terms such as first and second and the like be used merely to by
One entity or operation are distinguished with another entity or operation, without necessarily requiring or implying these entities or operation
Between there are any actual relationship or order.Moreover, term " comprising ", "comprising" or its any other variant meaning
Covering non-exclusive inclusion, so that process, method, article or equipment including a series of elements not only include that
A little key elements, but also including other elements that are not explicitly listed, or further include for this process, method, article or
The intrinsic key element of equipment.In the absence of more restrictions, the key element limited by sentence "including a ...", is not arranged
Except also there are other identical element in the process, method, article or apparatus that includes the element.
Mobile robot embedded laser SLAM method and system provided by the present invention are described in detail above,
Specific case used herein is set forth the principle of the present invention and embodiment, and the explanation of above example is simply used
Understand the method and its core concept of the present invention in help;Meanwhile for those of ordinary skill in the art, according to the present invention's
Thought, there will be changes in specific embodiments and applications, in conclusion this specification content should not be construed as
Limitation of the present invention.
Claims (10)
- A kind of 1. mobile robot embedded laser SLAM methods, it is characterised in that including:Robot operating system is built in embedded board in the mobile robot;PC is connected remotely to by the embedded board by wireless network, input order starts the robot behaviour Make system, the robotically-driven circuit board in the mobile robot, and the laser radar installed in the mobile robot;By the laser radar, the embedded board, the Inertial Measurement Unit in the robotically-driven circuit board, with And the direct current generator and magnetism encoder being connected with the robotically-driven circuit board, obtain sensing data;The establishment of map is carried out with reference to the SLAM algorithms in the embedded board by the sensing data of acquisition, and It is uploaded to the PC;The map created by PC observation, and the map is preserved.
- 2. mobile robot embedded laser SLAM methods according to claim 1, it is characterised in that pass through the laser Radar, the embedded board, the Inertial Measurement Unit in the robotically-driven circuit board, and driven with the robot The direct current generator and magnetism encoder of dynamic circuit board connection, obtain sensing data, specifically include:Gather the topography and geomorphology situation of the indoor and outdoor surroundings where the mobile robot in real time by the laser radar, carry out The extraction of data;The odometer being made up of direct current generator and magnetism encoder determines the indoor and outdoor surroundings where the mobile robot Position and displacement, carry out the extraction of data;The laser thunder is collected by the Inertial Measurement Unit in the robotically-driven circuit board and the embedded board Up to the data extracted with the odometer go forward side by side row information fusion, obtain sensing data.
- 3. mobile robot embedded laser SLAM methods according to claim 2, it is characterised in that pass through the institute of acquisition The establishment that sensing data carries out map with reference to the SLAM algorithms in the embedded board is stated, is specifically included:The closest approach iteration SLAM algorithms in mobile robot program-ming Toolbox function library are transplanted in the embedded board;Using the robot operating system by the closest approach iteration SLAM algorithms to the sensing data of acquisition into Row processing;Leave out image displaying part in the robot operating system, adjustment matching way matches for grid map, generates grid Map, and the track added in the robot operating system is shown.
- 4. mobile robot embedded laser SLAM methods according to claim 3, it is characterised in that use the machine People's operating system is handled the sensing data of acquisition by the closest approach iteration SLAM algorithms, is specifically included:Using the robot operating system by the closest approach iteration SLAM algorithms to the sensing data of acquisition into Row scanning and matching, solve the motion change matrix of the mobile robot;The motion change matrix includes spin matrix And translation matrix;Meanwhile real time kinematics track, self poisoning and the environment distribution of robot are calculated, carry out the mapping of grating map.
- 5. mobile robot embedded laser SLAM methods according to claim 4, it is characterised in that in generation grid During figure, specifically further include:The sensing data is verified using the embedded board;When the data of odometer extraction show that the displacement of the mobile robot is less than given threshold, last life is continued to use Into grating map.
- 6. according to claim 1-5 any one of them mobile robot embedded laser SLAM methods, it is characterised in that described The robot operating system is installed in PC;The internetwork connection mode of the PC and the embedded board uses the principal and subordinate of the robot operating system Machine method;The embedded board is as slave;The PC is as host;The sensing data passes through the host Shown.
- 7. mobile robot embedded laser SLAM methods according to claim 6, it is characterised in that pass through the individual The map that computer observation creates, specifically includes:Combined on robot operating system platform in the PC using RVIZ image display interfaces and carry assessment work Tool is observed the map of establishment.
- 8. mobile robot embedded laser SLAM methods according to claim 7, it is characterised in that to the map into Row preserves, and specifically includes:The map is preserved using the map conserving appliance installed in the robot operating system, simultaneously for preservation The map in the threshold values of three kinds of colors of black-white-gray be adjusted respectively.
- 9. mobile robot embedded laser SLAM methods according to claim 8, it is characterised in that the mobile machine The DC power supply of people is directly connected to the robotically-driven plate;Voltage conversion is carried out by the robotically-driven plate, to the embedded board, direct current generator and magnetism encoder into Row power supply;The laser radar is powered by the embedded board.
- A kind of 10. mobile robot embedded laser SLAM systems, it is characterised in that including:System building module, for building robot operating system in the embedded board in the mobile robot;Network connecting module, for PC to be connected remotely to the embedded board, input life by wireless network Make and start the robot operating system, the robotically-driven circuit board in the mobile robot, and the mobile machine The laser radar installed on people;Data acquisition module, for by the laser radar, the embedded board, in the robotically-driven circuit board Inertial Measurement Unit, and the direct current generator and magnetism encoder being connected with the robotically-driven circuit board, obtains sensing Device data;Map building module, for the sensing data by acquisition with reference to the SLAM algorithms in the embedded board The establishment of map is carried out, and is uploaded to the PC;Map preserving module, for the map created by PC observation, and preserves the map.
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Cited By (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN108549388A (en) * | 2018-05-24 | 2018-09-18 | 苏州智伟达机器人科技有限公司 | A kind of method for planning path for mobile robot based on improvement A star strategies |
CN109001752A (en) * | 2018-05-18 | 2018-12-14 | 威海晶合数字矿山技术有限公司 | A kind of three-dimensional measurement modeling and its method |
CN109079736A (en) * | 2018-08-02 | 2018-12-25 | 广东工业大学 | A kind of control method and system of the mobile robot platform based on ROS |
CN110207705A (en) * | 2019-05-27 | 2019-09-06 | 五邑大学 | A kind of indoor navigation vehicle based on laser SLAM |
CN110531766A (en) * | 2019-08-27 | 2019-12-03 | 熵智科技(深圳)有限公司 | Based on the known continuous laser SLAM composition localization method for occupying grating map |
CN113340295A (en) * | 2021-06-16 | 2021-09-03 | 广东工业大学 | Unmanned ship near-shore real-time positioning and mapping method with multiple ranging sensors |
Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
WO2016162568A1 (en) * | 2015-04-10 | 2016-10-13 | The European Atomic Energy Community (Euratom), Represented By The European Commission | Method and device for real-time mapping and localization |
CN106114095A (en) * | 2016-06-27 | 2016-11-16 | 中国石油大学(华东) | A kind of amphibious sniffing robot |
CN106406338A (en) * | 2016-04-14 | 2017-02-15 | 中山大学 | Omnidirectional mobile robot autonomous navigation apparatus and method based on laser range finder |
CN106842230A (en) * | 2017-01-13 | 2017-06-13 | 深圳前海勇艺达机器人有限公司 | Mobile Robotics Navigation method and system |
CN107063264A (en) * | 2017-04-13 | 2017-08-18 | 杭州申昊科技股份有限公司 | A kind of robot map creating method suitable for extensive substation |
-
2017
- 2017-11-28 CN CN201711215477.1A patent/CN107943038A/en active Pending
Patent Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
WO2016162568A1 (en) * | 2015-04-10 | 2016-10-13 | The European Atomic Energy Community (Euratom), Represented By The European Commission | Method and device for real-time mapping and localization |
CN106406338A (en) * | 2016-04-14 | 2017-02-15 | 中山大学 | Omnidirectional mobile robot autonomous navigation apparatus and method based on laser range finder |
CN106114095A (en) * | 2016-06-27 | 2016-11-16 | 中国石油大学(华东) | A kind of amphibious sniffing robot |
CN106842230A (en) * | 2017-01-13 | 2017-06-13 | 深圳前海勇艺达机器人有限公司 | Mobile Robotics Navigation method and system |
CN107063264A (en) * | 2017-04-13 | 2017-08-18 | 杭州申昊科技股份有限公司 | A kind of robot map creating method suitable for extensive substation |
Non-Patent Citations (5)
Title |
---|
李建勇,刘雪梅,李雪霞,杜博阳: "基于ROS的开源移动机器人***设计", 《机电设计》 * |
李玉: "基于3D激光点云的无人车城市环境SLAM问题研究", 《中国优秀硕士学位论文全文数据库 信息科技辑》 * |
林连秀,叶芸,姚剑敏,郭太良: "基于ORB-SLAM 的移动机器人嵌入式实现与优化", 《微型机与应用》 * |
白亮亮 等: "分布式移动机器人控制***设计与实现", 《机械设计与制造》 * |
郑富瑜,何苗 等: "基于ROS的ICP-SLAM在嵌入式移动机器人上的实现与优化", 《计算机应用研究》 * |
Cited By (8)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN109001752A (en) * | 2018-05-18 | 2018-12-14 | 威海晶合数字矿山技术有限公司 | A kind of three-dimensional measurement modeling and its method |
CN108549388A (en) * | 2018-05-24 | 2018-09-18 | 苏州智伟达机器人科技有限公司 | A kind of method for planning path for mobile robot based on improvement A star strategies |
CN109079736A (en) * | 2018-08-02 | 2018-12-25 | 广东工业大学 | A kind of control method and system of the mobile robot platform based on ROS |
CN109079736B (en) * | 2018-08-02 | 2022-02-22 | 广东工业大学 | ROS-based mobile robot platform control method and system |
CN110207705A (en) * | 2019-05-27 | 2019-09-06 | 五邑大学 | A kind of indoor navigation vehicle based on laser SLAM |
CN110531766A (en) * | 2019-08-27 | 2019-12-03 | 熵智科技(深圳)有限公司 | Based on the known continuous laser SLAM composition localization method for occupying grating map |
CN110531766B (en) * | 2019-08-27 | 2022-06-28 | 熵智科技(深圳)有限公司 | Continuous laser SLAM (Simultaneous laser mapping) composition positioning method based on known occupied grid map |
CN113340295A (en) * | 2021-06-16 | 2021-09-03 | 广东工业大学 | Unmanned ship near-shore real-time positioning and mapping method with multiple ranging sensors |
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