CN108021132A - Paths planning method - Google Patents
Paths planning method Download PDFInfo
- Publication number
- CN108021132A CN108021132A CN201711222922.7A CN201711222922A CN108021132A CN 108021132 A CN108021132 A CN 108021132A CN 201711222922 A CN201711222922 A CN 201711222922A CN 108021132 A CN108021132 A CN 108021132A
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- Prior art keywords
- information
- robot
- gathered
- paths planning
- planning method
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Classifications
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- 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
- G05D1/0231—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means
- G05D1/0238—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means using obstacle or wall sensors
- G05D1/024—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means using obstacle or wall sensors in combination with a laser
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- 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
- G05D1/0212—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory
- G05D1/0221—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory involving a learning process
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- 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
- G05D1/0231—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means
- G05D1/0242—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means using non-visible light signals, e.g. IR or UV signals
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- 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
- G05D1/0231—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means
- G05D1/0246—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means using a video camera in combination with image processing means
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- 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
- G05D1/0276—Control of position or course in two dimensions specially adapted to land vehicles using signals provided by a source external to the vehicle
Abstract
The present invention relates to path planning field, open paths planning method, the paths planning method includes：Step 1, the peripheral information of robot is gathered in real time by multisensor；Step 2, place of arrival information is carried out to the planning in path according to the peripheral information, robot present position information and robot gathered；Step 3, robot is travelled according to the path planned.The path planning that the paths planning method overcomes existing mobile robot of the prior art is high to environmental requirement, it is also desirable to the problem of auxiliary equipment, realizes the path planning without auxiliary equipment.
Description
Technical field
The present invention relates to path planning field, and in particular, to paths planning method.
Background technology
Path planning refers to, in the environment with barrier, according to certain evaluation criterion, finds one from starting shape
State is to the collisionless path of dbjective state.Path planning employs Knowledge based engineering genetic algorithm in this algorithm, it is contained certainly
The thought for so selecting and evolving, has very strong robustness.
The path planning mode of existing mobile robot is very much, such as inertia planning, magnetic planning, view planning, satellite planning
Deng.These modes are respectively suitable for a variety of environment, including indoor and outdoors environment.But it is high to environmental requirement, also need
Auxiliary equipment is wanted, in order to overcome the problem of above-mentioned, there is an urgent need for design a kind of paths planning method without auxiliary equipment.
The content of the invention
The object of the present invention is to provide a kind of paths planning method, v
To achieve these goals, the present invention provides a kind of paths planning method, which includes：
Step 1, the peripheral information of robot is gathered in real time by multisensor；
Step 2, place of arrival is believed according to the peripheral information, robot present position information and robot that are gathered
Breath carries out the planning in path；
Step 3, robot is travelled according to the path planned.
Preferably, in step 1, gathering the method for the peripheral information of robot in real time by multisensor includes：
Gathered by monopod video camera, sonar sensor, infrared sensor and laser sensor and believed around robot
Breath.
Preferably, in step 2, to being pre-processed by monopod video camera acquired image information, wherein, pre- place
The method of reason includes：
Acquired image is subjected to gray processing, and carries out the smoothing processing of image.
Preferably, in step 2, to passing through monopod video camera, sonar sensor, infrared sensor and laser sensor
The information gathered carries out information fusion, obtains peripheral information.
Preferably, in step 2, according to the peripheral information, robot present position information and robot gathered i.e.
Place of arrival information is carried out to the method for the planning in path to be included：
Sensing robot present position information and peripheral information in real time.
Preferably, Image Edge-Detection and image segmentation are carried out successively to pretreated image information, to obtain machine
The peripheral information of people.
Preferably, the method for the information progress information fusion to being gathered includes any one of in the following manner：Weighting is flat
Equal method and Kalman filtering method.
Through the above technical solutions, the present invention has relatively low probabilistic related sensor, answering for map structuring is reduced or remitted
Polygamy, obtains the description to barrier by distance measuring sensor in the unknown sector planning of environment, is carried with reference to visual sensor
The environmental information of the abundant redundancy supplied so that perception of the robot to environment is more accurate and efficient, and robot interior
Odometer then effectively provides the real-time posture information of robot, by correcting, corrects position deviation and the promotion of robot
The acquisition of precise position information, improves the precision of positioning.
Other features and advantages of the present invention will be described in detail in subsequent specific embodiment part.
Brief description of the drawings
Attached drawing is for providing a further understanding of the present invention, and a part for constitution instruction, with following tool
Body embodiment is used to explain the present invention together, but is not construed as limiting the invention.In the accompanying drawings：
Fig. 1 is the flow chart for illustrating a kind of paths planning method of the present invention.
Embodiment
The embodiment of the present invention is described in detail below in conjunction with attached drawing.It should be appreciated that this place is retouched
The embodiment stated is merely to illustrate and explain the present invention, and is not intended to limit the invention.
The present invention provides a kind of paths planning method, which includes：
Step 1, the peripheral information of robot is gathered in real time by multisensor；
Step 2, place of arrival is believed according to the peripheral information, robot present position information and robot that are gathered
Breath carries out the planning in path；
Step 3, robot is travelled according to the path planned.
Through the above technical solutions, the present invention has relatively low probabilistic related sensor, answering for map structuring is reduced or remitted
Polygamy, obtains the description to barrier by distance measuring sensor in the unknown sector planning of environment, is carried with reference to visual sensor
The environmental information of the abundant redundancy supplied so that perception of the robot to environment is more accurate and efficient, and robot interior
Odometer then effectively provides the real-time posture information of robot, by correcting, corrects position deviation and the promotion of robot
The acquisition of precise position information, improves the precision of positioning.In addition, present invention employs robot present position information and machine
Device people is the mode for being combined two information of place of arrival information, and the peripheral information of robot is acquired in real time, and
Path planning is carried out in real time, can greatly be travelled beneficial to the planning of robot.
In addition, also it is emphasized that the application employs a kind of new mode, robot appoints right nothing under the path of planning
In the case that method travels, nearest route compared with route is planned, and so on.It may finally realize the arrival of shortest path.
In a kind of embodiment of the present invention, in step 1, the week of robot is gathered in real time by multisensor
Enclosing the method for information can include：
Gathered by monopod video camera, sonar sensor, infrared sensor and laser sensor and believed around robot
Breath.
Fully understanding for environmental information can be achieved using multiple sensors (internal sensor/external sensor), easy to machine
Device people makes correct decision-making.Due to some undesirable features (such as sensor detection " blind area ") of sensor, information processing is not
When or selection sensor between matching effect it is undesirable, the reasons such as Multi-sensor Fusion is poor, it is more accurate to hardly result in
Reflect the cartographic model of true environment information.
In a kind of embodiment of the present invention, in step 2, to being believed by monopod video camera acquired image
Breath is pre-processed, wherein, the method for pretreatment can include：
In order to realize the pretreatment of image information, acquired image is subjected to gray processing, and carries out the smooth place of image
Reason.
In this kind of embodiment, in step 2, to by monopod video camera, sonar sensor, infrared sensor and
The information that laser sensor is gathered carries out information fusion, obtains peripheral information.
The present invention a kind of embodiment in, in step 2, according to gathered peripheral information, institute of robot
Place's positional information and robot are that the method for the planning that place of arrival information is carried out path can include：
Sensing robot present position information and peripheral information in real time.
In a kind of embodiment of the present invention, Image Edge-Detection is carried out successively to pretreated image information
Split with image, to obtain the peripheral information of robot.
In a kind of embodiment of the present invention, the method for information fusion is carried out to the information gathered to be included
Any one of in the following manner：Weighted mean method and Kalman filtering method.
It can analyze image information by Kalman filtering blending algorithm, realize the self-positioning of mobile robot herein.
The fuzzy logic algorithm for the very big advantage having in uncertain expression, combined aspects, production are utilized in further path planning
Raw more reliable, more accurately information, and reliable decision-making is made according to these information, so that appropriate path is obtained, enhancing letter
The complementarity of breath, improves the robustness, flexibility and fault-tolerance of system.
The preferred embodiment of the present invention is described in detail above in association with attached drawing, still, the present invention is not limited to above-mentioned reality
The detail in mode is applied, in the range of the technology design of the present invention, a variety of letters can be carried out to technical scheme
Monotropic type, these simple variants belong to protection scope of the present invention.
It is further to note that each particular technique feature described in above-mentioned embodiment, in not lance
In the case of shield, can be combined by any suitable means, in order to avoid unnecessary repetition, the present invention to it is various can
The combination of energy no longer separately illustrates.
In addition, various embodiments of the present invention can be combined randomly, as long as it is without prejudice to originally
The thought of invention, it should equally be considered as content disclosed in this invention.
Claims (7)
1. a kind of paths planning method, it is characterised in that the paths planning method includes：
Step 1, the peripheral information of robot is gathered in real time by multisensor；
Step 2, according to the peripheral information, robot present position information and robot gathered i.e. by place of arrival information into
The planning in walking along the street footpath；
Step 3, robot is travelled according to the path planned.
2. paths planning method according to claim 1, it is characterised in that in step 1, adopted in real time by multisensor
Collecting the method for the peripheral information of robot includes：
The peripheral information of robot is gathered by monopod video camera, sonar sensor, infrared sensor and laser sensor.
3. paths planning method according to claim 1, it is characterised in that in step 2, to passing through monopod video camera institute
The image information of collection is pre-processed, wherein, the method for pretreatment includes：
Acquired image is subjected to gray processing, and carries out the smoothing processing of image.
4. paths planning method according to claim 2, it is characterised in that in step 2, to by monopod video camera,
The information that sonar sensor, infrared sensor and laser sensor are gathered carries out information fusion, obtains peripheral information.
5. paths planning method according to claim 1, it is characterised in that in step 2, believe according to around being gathered
Breath, robot present position information and robot are that the method for the planning that place of arrival information is carried out path includes：
Sensing robot present position information and peripheral information in real time.
6. paths planning method according to claim 4, it is characterised in that carried out successively to pretreated image information
Image Edge-Detection and image segmentation, to obtain the peripheral information of robot.
7. paths planning method according to claim 1, it is characterised in that information fusion is carried out to the information gathered
Method includes any one of in the following manner：Weighted mean method and Kalman filtering method.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201711222922.7A CN108021132A (en) | 2017-11-29 | 2017-11-29 | Paths planning method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201711222922.7A CN108021132A (en) | 2017-11-29 | 2017-11-29 | Paths planning method |
Publications (1)
| Publication Number | Publication Date |
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| CN108021132A true CN108021132A (en) | 2018-05-11 |
Family
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| Application Number | Title | Priority Date | Filing Date |
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| CN201711222922.7A Pending CN108021132A (en) | 2017-11-29 | 2017-11-29 | Paths planning method |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110515381A (en) * | 2019-08-22 | 2019-11-29 | 浙江迈睿机器人有限公司 | Multi-sensor Fusion algorithm for positioning robot |
Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101975951A (en) * | 2010-06-09 | 2011-02-16 | 北京理工大学 | Field environment barrier detection method fusing distance and image information |
| JP5187758B2 (en) * | 2008-12-26 | 2013-04-24 | 株式会社Ｉｈｉエアロスペース | Unmanned mobile system |
| CN103400392A (en) * | 2013-08-19 | 2013-11-20 | 山东鲁能智能技术有限公司 | Binocular vision navigation system and method based on inspection robot in transformer substation |
| CN104036279A (en) * | 2014-06-12 | 2014-09-10 | 北京联合大学 | Intelligent vehicle running control method and system |
| CN104166400A (en) * | 2014-07-11 | 2014-11-26 | 杭州精久科技有限公司 | Multi-sensor fusion-based visual navigation AGV system |
| CN104267721A (en) * | 2014-08-29 | 2015-01-07 | 陈业军 | Unmanned driving system of intelligent automobile |
| CN106444780A (en) * | 2016-11-10 | 2017-02-22 | 速感科技（北京）有限公司 | Robot autonomous navigation method and system based on vision positioning algorithm |
| CN106652515A (en) * | 2015-11-03 | 2017-05-10 | 中国电信股份有限公司 | Vehicle automatic control method, vehicle automatic control device, and vehicle automatic control system |
| CN107161141A (en) * | 2017-03-08 | 2017-09-15 | 深圳市速腾聚创科技有限公司 | Pilotless automobile system and automobile |
-
2017
- 2017-11-29 CN CN201711222922.7A patent/CN108021132A/en active Pending
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP5187758B2 (en) * | 2008-12-26 | 2013-04-24 | 株式会社Ｉｈｉエアロスペース | Unmanned mobile system |
| CN101975951A (en) * | 2010-06-09 | 2011-02-16 | 北京理工大学 | Field environment barrier detection method fusing distance and image information |
| CN103400392A (en) * | 2013-08-19 | 2013-11-20 | 山东鲁能智能技术有限公司 | Binocular vision navigation system and method based on inspection robot in transformer substation |
| CN104036279A (en) * | 2014-06-12 | 2014-09-10 | 北京联合大学 | Intelligent vehicle running control method and system |
| CN104166400A (en) * | 2014-07-11 | 2014-11-26 | 杭州精久科技有限公司 | Multi-sensor fusion-based visual navigation AGV system |
| CN104267721A (en) * | 2014-08-29 | 2015-01-07 | 陈业军 | Unmanned driving system of intelligent automobile |
| CN106652515A (en) * | 2015-11-03 | 2017-05-10 | 中国电信股份有限公司 | Vehicle automatic control method, vehicle automatic control device, and vehicle automatic control system |
| CN106444780A (en) * | 2016-11-10 | 2017-02-22 | 速感科技（北京）有限公司 | Robot autonomous navigation method and system based on vision positioning algorithm |
| CN107161141A (en) * | 2017-03-08 | 2017-09-15 | 深圳市速腾聚创科技有限公司 | Pilotless automobile system and automobile |
Non-Patent Citations (5)
| Title |
|---|
| 张茂于: "《产业专利分析报告 第58册 自动驾驶》", 30 June 2017 * |
| 杨帆: "《数字图像处理与分析》", 31 May 2015 * |
| 段中兴: "《物联网传感技术》", 30 April 2014 * |
| 江晶: "《运动传感器目标跟踪技术》", 30 April 2017 * |
| 贺瑜飞: "小波分析和边缘检测在快速车牌定位中的应用", 《科技创新导报》 * |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110515381A (en) * | 2019-08-22 | 2019-11-29 | 浙江迈睿机器人有限公司 | Multi-sensor Fusion algorithm for positioning robot |
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Application publication date: 20180511 |