CN106774310B - A kind of robot navigation method - Google Patents
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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
- G05D1/0231—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
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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
- G05D1/0231—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
- G05D1/0251—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 extracting 3D information from a plurality of images taken from different locations, e.g. stereo vision
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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
The present invention provides a kind of robot navigation method, the navigation grating map is imported the operating system of the robot by the navigation grating map that the air navigation aid includes the following steps: a, establishes the robot work region；B, the target endpoint that the initial position to the robot and the robot advance positions, and planning robot's travel path, the robot advances by the path；C, there is obstacle in the path described in the step b, obtain the robot real-time pose information, real-time route planning is carried out to the robot travel path according to the location information of the real-time pose information and the target endpoint, wherein incoming direction changes cost in the actual cost for calculating robot current location cost function, calculates the cost of robot current location different directions；D, the cost of robot current location different directions is searched for, the smallest direction of cost is selected to advance.
Description
Technical field
The present invention relates to robot navigation's technical field, in particular to a kind of robot navigation method.
Background technique
With the development of science and technology, the application field of robot is increasingly extensive, and robot is typical electromechanical integration
Digitizing equipment, technical value added are very high.Robot as advanced manufacturing industry support technology and informationized society it is emerging
Industry plays increasingly important role to future production and social development.
The exploitation that China's machine had also carried out recombination assembly system and its relevant technologies based on robot in recent years is ground
Study carefully and reinforce the research of Multi-sensor Fusion and decision, control integrated technique and application.The key technology of machine is carried out
In-depth study has been carried forward vigorously into device people's industrialization process.The research of robot was concentrated mainly on industrial robot in recent years
With the aspect of intelligent robot two, research refines again in terms of intelligent robot are as follows: (1) remote control plus locally autonomous system constitute and
Control strategy research, the navigation and Study of location of (2) intelligent mobile robot, specially in structural environment or non-structural ring
Navigation and localization method research, the method that environmental model is established according to sensing data in border；The inference method of fuzzy logic is used
In the research of Mobile Robotics Navigation.
Existing robot navigation method generally using constructing navigation map in robot operating system, robot according to
Navigation map planning path, so that destination is advanced to along the path of planning, but this navigation mode goes out in progress path
When existing obstacle, it cannot be resolved, robot is not smart enough.At the same time, road is planned using A star algorithm in existing technology
Diameter is in the hope of shorter travel path, but when being obstacle, again planning path can not achieve due to robot from
Body changes direction bring error, to can not achieve more reasonable path planning.
Therefore, it is necessary to a kind of robots that can be effectively reduced since direction changes bring error, realize that robot encounters barrier
The robot navigation method of shortest path is more reasonably planned when hindering.
Summary of the invention
The purpose of the present invention is to provide a kind of robot navigation method, the air navigation aid includes the following steps: a, builds
The navigation grating map is imported the operation system of the robot by the navigation grating map for founding the robot work region
System；
B, the target endpoint that the initial position to the robot and the robot advance positions, planning robot
Travel path, the robot advance by the path；
C, there is obstacle in the path described in the step b, the robot real-time pose information is obtained, according to the real-time position
The location information of appearance information and the target endpoint carries out real-time route planning to the robot travel path, wherein
In the real-time route planning process, draw in the actual cost for calculating robot current location cost function
Enter direction and change cost, calculates the cost of robot current location different directions；
D, the cost for searching for robot current location different directions, before the smallest direction of Robot Selection cost
Into.
Preferably, the robot cost function is defined as:
F (i)=g (i)+h (i), wherein
G (i) is the actual cost that robot starting point is paid to current location i, and h (i) is heuristic function, i.e. current location is arrived
The estimation of the minimum cost of target endpoint.
Preferably, the actual cost meets: g (i)=d (i)+m (i), wherein d (i) is that direction changes cost, m (i)
For straight line traveling cost.
Preferably, the heuristic function meets: h (i)=abs (Xi-Xk)+abs (Yi-Yk)；Wherein, robot is current
Position coordinates are (Xi, Yi)；The coordinate of robot target terminal is (Xk, Yk).
Preferably, the heuristic function meets: h (i)=max ((Xi-Xk), abs (Yi-Yk))；Wherein, robot works as
Front position coordinate is (Xi, Yi)；The coordinate of robot target terminal is (Xk, Yk).
Preferably, the heuristic function meets: h (i)=sqrt ((Xi-Xk)∧2+abs (Yi-Yk)∧2)；Wherein, machine
Device people's current position coordinates are (Xi, Yi)；The coordinate of robot target terminal is (Xk, Yk).
Preferably, the robot real-time pose information passes through the kinect depth camera that is set in the robot
It is obtained with infrared sensor.
Preferably, the kinect depth camera and infrared sensor are obtained by scanning the travel path of the robot
Take the robot real-time pose information and complaint message.
Preferably, the Gmapping algorithm that is constructed by of the navigation grating map is generated or is manually drawn.
Preferably, the cost of robot current location different directions is searched in the step d by traversal search method.
A kind of robot navigation method provided by the invention keeps robot as few as possible by adjusting actual cost function
Change direction on the basis of reach target endpoint, effectively shorten the travel path of robot.Meanwhile robot of the present invention is led
The robot on differential mechanism chassis is effectively reduced since direction changes bring error in boat method, realizes that robot encounters barrier
Shortest path is more reasonably planned when hindering.
It should be appreciated that aforementioned description substantially and subsequent detailed description are exemplary illustration and explanation, it should not
As the limitation to the claimed content of the present invention.
Detailed description of the invention
With reference to the attached drawing of accompanying, the more purposes of the present invention, function and advantage are by the as follows of embodiment through the invention
Description is illustrated, in which:
Fig. 1 diagrammatically illustrates robot schematic diagram of the present invention；
Fig. 2 shows the flow diagrams of air navigation aid of the present invention；
Fig. 3 shows present invention navigation grating map schematic diagram；
Fig. 4 shows the path schematic diagram of robot initial position of the present invention and target endpoint planning；
Fig. 5 shows robot initial position of the present invention and the path of target endpoint planning and the schematic diagram of obstacle occurs；
Fig. 6 shows the schematic diagram of real-time route planning of the present invention；
Fig. 7 shows real-time route planning cost of the present invention and calculates schematic diagram；
Fig. 8 shows another embodiment of the present invention path planning cost and calculates schematic diagram.
Specific embodiment
By reference to exemplary embodiment, the purpose of the present invention and function and the side for realizing these purposes and function
Method will be illustrated.However, the present invention is not limited to exemplary embodiment as disclosed below；Can by different form come
It is realized.The essence of specification is only to aid in those skilled in the relevant arts' Integrated Understanding detail of the invention.
Hereinafter, the embodiment of the present invention will be described with reference to the drawings.In the accompanying drawings, identical appended drawing reference represents identical
Or similar component or same or like step.
Embodiment one:
Detailed description is provided to robot navigation method of the present invention by specific embodiment with reference to the accompanying drawing, is
Clear description robot navigation method of the invention, is first illustrated robot.Robot of the present invention
Differential mechanism chassis robot, robot schematic diagram of the present invention as shown in Figure 1 are selected, robot 100 selects the machine on differential mechanism chassis
Device people is equipped with camera and infrared sensor in robot front end, for the travel path of scanning machine people 100, detects machine
Whether 100 travel path of people has obstacle in region a.100 differential mechanism chassis of robot includes differential mechanism traveling wheel 101 and poor
Fast device gear shaft 102 adjusts the direction of robot by differential mechanism chassis.It should be understood that robot interior tool of the present invention
Have operating system, the operating system include memory module, information of road surface acquisition module, analysis module, road surface planning module with
And control module, wherein
Memory module, for storing navigation grating map, when starting robot, analysis module reads navigation grating map；
Information of road surface acquisition module, for during robot ambulation, acquisition camera and infrared sensor to shoot road surface
Information；
Analysis module, the position of the locating navigation grating map of analysis navigation grating map and robot current location；
Path planning module plans robot ambulation path and robot encounters when starting robot ambulation
Path is planned again when obstacle；
Control module, control Robot planning path are advanced.
Robot navigation method provided by the invention utilizes institute in the navigation grating map for establishing robot work region
It states navigation grating map and carries out path planning, shortest path is selected to advance.Specifically, air navigation aid of the present invention as shown in Figure 2
Flow diagram, robot navigation method includes the following steps:
S101, the navigation grating map for establishing the robot work region, will be described in navigation grating map importing
The operating system of robot；
S102, planning robot carry out path, the target that the initial position and the robot to the robot are advanced
Terminal is positioned, planning robot's travel path, and the robot advances by the path, it should be noted that here
Path planning is shortest path planning of the robot starting point to robot target terminal, thinks the path of working region without any
Obstacle is planned using A star algorithm.
S103, when the path advance process occurs and encounters obstacle in step s 102 for robot, obtain the robot
Real-time pose information, according to the location information of the real-time pose information and the target endpoint to the robot travel path
Real-time route planning is carried out, wherein
In the real-time route planning process, draw in the actual cost for calculating robot current location cost function
Enter direction and change cost, calculates the cost of robot current location different directions.
S104, the cost for searching for robot current location different directions, the smallest side of Robot Selection cost
It marches forward.
Below with reference to specific embodiment, robot navigation's process of the present invention is described further.
Firstly, the present embodiment establishes the navigation of robot work region according to robot navigation method provided by the invention
Grating map, present invention navigation grating map schematic diagram as shown in Figure 3, according to the knot of robot work region B in the present embodiment
It is configured shape, working region B is depicted as to the navigation grating map of multiple grids 301, it is preferable that pass through in the present embodiment
Gmapping algorithm generates the navigation grating map, the ratio for keeping the grid opposed robots working region of navigation grating map most
Example is reasonable as far as possible.
In some embodiments, the mode manually drawn can choose for navigation grating map, similarly, should makes to lead
The ratio that the grid opposed robots working region of boat grating map is most is reasonable as far as possible.
The navigation grating map of foundation is imported into robot operating system, the storage mould of the operating system is stored in
In block.The path schematic diagram of robot initial position of the present invention as shown in Figure 4 and target endpoint planning；Start robot, analysis
The target endpoint 402 that module advances to the initial position 401 of robot and robot positions, the path planning of operating system
Module carries out path rule according to the target endpoint 402 that the initial position 401 of robot and robot advance in the B of working region
It draws, it should be appreciated that the path 403 of planning is that robot initial position 401 is advanced the most short of target endpoint 402 to robot
Path, since robot initial position 401 is larger at a distance from target endpoint 402 in the present embodiment, can ignore robot from
Body angular error, it is preferable that using A star algorithm to path planning.
There is the schematic diagram of obstacle in robot initial position of the present invention as shown in Figure 5 and the path of target endpoint planning；Machine
Device people is not regarded as there is obstacle on the path 403 of its planning, therefore, robot is total in working region B planning path 403
It is the shortest path for planning initial position 401 to robot travel terminus 402, when there is obstacle on the path of robot planning
When 404, robot is not learnt.Robot still advances forward according to the path of planning 403, is advancing simultaneously, robot passes through
Camera and infrared sensor shoot information of road surface, detect road barrier information.Preferably, the present embodiment camera is selected
Kinect depth camera.
When there is not obstacle on path 403, robot is carried out according to the path 403 of planning to target endpoint 402.
When obstacle 404 occurs in path 403, robot needs real-time route to plan.Robot real-time route is planned
It is described below.
The schematic diagram that real-time route of the present invention is planned as shown in Figure 6, when robot from initial position 401 according to working region
During the path 403 planned in B is carried out to target endpoint 402, when obstacle 401 occurs in path 403, robot passes through camera shooting
Head and infrared sensor take obstacle 404 in scanning area.
Robot passes through the locating navigation of the analysis module analysis navigation grating map of operating system and robot current location
The position of grating map, by path planning module again planning path.For example, robot according to path 403 to move ahead
It sails to current location 401a, robot marches to target endpoint 402 according to the path 405 planned again.
Due to there are robot direction bring actual cost be greater than straight line cost the case where, the present invention on real-time road
Incoming direction change cost carrys out planning path again in diameter planning process.As shown in fig. 6, there is robot again after planning path
Current location 401a adjusts pose to another current pose 401b, advances later according to the path 405 planned again, to make to advise
The path drawn is most short.
Below with reference to specific schematic example, illustrate the process of robot planning path again, as shown in Figure 7 the present invention
Real-time route plans that cost calculates schematic diagram, it is necessary first to which explanation, cost function are for estimating robot any position
To the cost of target endpoint, next direction of advance of the least direction of Robot Selection cost as path.In the present embodiment, with
For the grid of navigation grating map 5 × 5, the cost function of robot current location i is defined as:
F (i)=g (i)+h (i) wherein,
G (i) is the actual cost that robot starting point is paid to current location i, and h (i) is heuristic function, i.e. current location is arrived
The estimation of the minimum cost of target endpoint.
In the present embodiment, heuristic function meets: h (i)=abs (Xi-Xk)+abs (Yi-Yk)；Wherein, robot is current
Position coordinates are (Xi, Yi)；The coordinate of robot target terminal is (Xk, Yk).
In some embodiments, heuristic function meets: h (i)=max ((Xi-Xk), abs (Yi-Yk))；Wherein, machine
People's current position coordinates are (Xi, Yi)；The coordinate of robot target terminal is (Xk, Yk).
In further embodiments, heuristic function meets: h (i)=sqrt ((Xi-Xk)∧2+abs (Yi-Yk)∧2)；Its
In, robot current position coordinates are (Xi, Yi)；The coordinate of robot target terminal is (Xk, Yk).
The case where nyctitropic cost is much larger than along the cost currently advanced, robot of the present invention are changed for robot
Air navigation aid incoming direction in actual cost changes cost, thus the shortest carry out path of planning robot.
The actual cost meets: g (i)=d (i)+m (i), wherein d (i) is that direction changes cost, and m (i) is linear rows
Into cost.As shown in figure 5, the grid of the current position of robot is M (3,3) in the two-dimensional coordinate of navigation grating map；
Robot is moved to grid (3,4) from grid M (3,3), does not change direction, and direction changes cost d (i)=0；
Robot is moved to grid (2,4) or (4,4) from grid M (3,3), and direction changes 45 degree, and direction changes cost d
(i)=5；
Robot is moved to grid (2,3) or (4,3) from grid M (3,3), and direction changes 90 degree, and direction changes cost d
(i)=10；
Robot is moved to grid (2,2) or (4,2) from grid M (3,3), and direction changes 135 degree, and direction changes cost d
(i)=15；
Robot is moved to grid (3,2) from grid M (3,3), and direction changes 180 degree, and direction changes cost d (i)=20.
For straight line traveling cost:
Robot is moved to grid (3,4) or (2,3) or (3,2) or (4,3) from grid M (3,3), and moving distance is one
Grid, straight line traveling cost m (i)=10；
Robot is moved to grid (2,4) or (4,4) or (2,2) from grid M (3,3) or (4,2), moving distance are
1.414 grids, straight line traveling cost m (i)=14.
In embodiment, the actual cost g (i) that robot is moved to neighbouring grid from grid (3,3) is respectively as follows:
A: robot is from the actual cost that grid M (3,3) is moved to grid (3,4)
G (i)=15；
B: robot is from the actual cost that grid M (3,3) is moved to grid (2,4)
G (i)=24；
C: robot is from the actual cost that grid M (3,3) is moved to grid (2,3)
G (i)=25；
D: robot is from the actual cost that grid M (3,3) is moved to grid (2,2)
G (i)=34；
E: robot is from the actual cost that grid M (3,3) is moved to grid (3,2)
G (i)=30；
F: robot is from the actual cost that grid M (3,3) is moved to grid (4,2)
G (i)=34；
G: robot is from the actual cost that grid M (3,3) is moved to grid (4,3)
G (i)=25；
H: robot is from the actual cost that grid M (3,3) is moved to grid (4,4)
G (i)=24.
The robot navigation method that above-described embodiment provides according to the present invention, it is contemplated that robot direction bring practical generation
Valence is greater than straight line cost, and the actual cost that robot proceeds to neighbouring grid from current grid M (3,3) is different, searching machine people
The cost of current location different directions selects the smallest direction of cost to advance.It should be understood that the robot present bit of search
The cost set should include actual cost g (i) and heuristic function h (i), and the value of final relatively cost function f (i) is selected most short
Travel path.
Explanation is needed further exist for, the present invention is when robot is carried out to next grid, if direction changes, In
On the basis of changing direction, current location cost is calculated again through cost function f (i), plans travel path again.Citing
For, in the present embodiment, if robot, which marches to grid (2,4) direction from grid M (3,3), has occurred and that change, then next
Walking into when, based on robot is with the direction of place grid (2,4), again through cost function f (i) carry out cost calculating.
Embodiment two:
The present embodiment and the difference of embodiment one are that real-time route planning cost calculating process increases direction and changes cost
Quantity.
Another embodiment of the present invention path planning cost as shown in Figure 8 calculates schematic diagram, in another embodiment, calculate with
The grid of robot current location is that M (3,3) are moved to and the non-conterminous outside grid of robot current location grid M (3,3)
Actual cost, to increase the quantity that direction when calculating actual cost changes cost, to more reasonably indicate true
Cost size.Such as in the present embodiment, robot from the grid of current location be M (3,3) be successively moved to grid (3,5), (2,
5)、(1,5)、(1,4)、(1,3)、(1,2)、(1,1)、(2,1)、(3,1)、(4,1)、(5,1)、(5,2)、(5,3)、(5,4)、
(5,5),(4,5).Change deflection angle value every time and increase by 22.5 degree, increases the actual cost quantity calculated, more reasonably
Indicate true cost size.
Above-described embodiment says cost calculating in robot navigation method of the present invention and real-time route planning process
Bright, robot navigation method, incoming direction change cost and adjust actual cost function through the invention, make robot few as far as possible
Change reaches target endpoint on the basis of direction, can be effectively reduced the robot on various differential mechanism chassis since direction changes
Bring error.
Embodiment one and embodiment two apply robot navigation method of the present invention, are establishing two dimensional navigation grating map, lead to
It crosses incoming direction and changes cost to the planning of robot traveling process real-time route.It will be apparent to a skilled person that another
In some embodiments, using robot navigation method provided by the invention, three-dimensional navigation grating map is established, incoming direction changes
Cost carries out real-time route planning to airflight robot (such as unmanned plane), to realize cost most while obstacle avoidance
It advances in small path.
In conjunction with the explanation and practice of the invention disclosed here, the other embodiment of the present invention is for those skilled in the art
It all will be readily apparent and understand.Illustrate and embodiment is regarded only as being exemplary, true scope of the invention and purport are equal
It is defined in the claims.
Claims (8)
1. a kind of robot navigation method, the air navigation aid includes the following steps: a, establishes the robot work region
Navigate grating map, and the navigation grid is imported to the operating system of the robot；
B, the target endpoint that the initial position to the robot and the robot advance positions, and planning robot advances
Path, the robot advance by the path；
It is characterized in that, the air navigation aid further include:
C, there is obstacle in the path described in the step b, obtains the robot real-time pose information, is believed according to the real-time pose
The location information of breath and the target endpoint carries out real-time route planning to the robot travel path, wherein
In the real-time route planning process, incoming direction changes cost in the actual cost of calculating robot's cost function,
Calculate the cost of robot current location different directions；
The robot cost function is defined as:
F (i)=g (i)+h (i), wherein
G (i) is the actual cost that robot starting point is paid to current location i, and h (i) is heuristic function, i.e. current location to target
The estimation of the minimum cost of terminal；
The actual cost meets: g (i)=d (i)+m (i), wherein d (i) is that direction changes cost, and m (i) is that straight line is advanced generation
Valence；
Direction changes cost d (i) and is moved to peripheral grid from the grid of current location for robot, changes nyctitropic cost, directly
Line traveling cost m (i) is moved to peripheral grid, the cost that traveling linear distance generates from the grid of current location for robot；
D, the cost of robot current location different directions is searched for, the smallest direction of Robot Selection cost is advanced；
When robot is carried out to next grid, if direction changes, on the basis of changing direction, again through cost
Function f (i) calculates current location cost, plans travel path again.
2. air navigation aid according to claim 1, which is characterized in that the heuristic function meets: h (i)=abs (Xi-
Xk)+abs (Yi-Yk)；Wherein, robot current position coordinates are (Xi, Yi)；The coordinate of robot target terminal be (Xk,
Yk)。
3. air navigation aid according to claim 1, which is characterized in that the heuristic function meets: h (i)=max ((Xi-
Xk), abs (Yi-Yk))；Wherein, robot current position coordinates are (Xi, Yi)；The coordinate of robot target terminal be (Xk,
Yk)。
4. air navigation aid according to claim 1, which is characterized in that the heuristic function meets: h (i)=sqrt
((Xi-Xk)∧2+abs (Yi-Yk)∧2)；Wherein, robot current position coordinates are (Xi, Yi)；Robot target terminal
Coordinate is (Xk, Yk).
5. air navigation aid according to claim 1, which is characterized in that the robot real-time pose information is by being set to
Kinect depth camera and infrared sensor in the robot obtain.
6. air navigation aid according to claim 5, which is characterized in that the kinect depth camera and infrared sensor are logical
The travel path for over-scanning the robot obtains the robot real-time pose information and complaint message.
7. air navigation aid according to claim 1, which is characterized in that the navigation grating map is constructed by
Gmapping algorithm generates or artificial drafting.
8. air navigation aid according to claim 1, which is characterized in that search for institute by traversal search method in the step d
State the cost of robot current location different directions.
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| CN107478232B (en) * | 2017-09-18 | 2020-02-21 | 珠海市一微半导体有限公司 | Searching method for robot navigation path |
| CN109709945B (en) * | 2017-10-26 | 2022-04-15 | 深圳市优必选科技有限公司 | Path planning method and device based on obstacle classification and robot |
| CN107608364A (en) * | 2017-11-01 | 2018-01-19 | 广州供电局有限公司 | A kind of intelligent robot for undercarriage on data center's physical equipment |
| CN108363393B (en) | 2018-02-05 | 2019-09-27 | 腾讯科技（深圳）有限公司 | A kind of smart motion equipment and its air navigation aid and storage medium |
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