CN105487535A - Mobile robot indoor environment exploration system and control method based on ROS - Google Patents
Mobile robot indoor environment exploration system and control method based on ROS Download PDFInfo
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Abstract
The invention discloses a mobile robot indoor environment exploration system and control method based on a ROS (Robot Operating System). The system is based on the ROS, and can realize independent exploration and positioning on indoor environment by a robot. The system mainly uses an iRobot differential drive chassis and UTM 30LX laser radar. An upper computer can obtain position positioning information of the robot and an indoor environment exploration path track in real time, and through data matching of the laser radar, a global map formed by connecting local maps is obtained. The invention provides a more intelligent unknown environment exploration system, provides great convenience and safety guarantee for disaster environment rescue, realizes information interaction of indoor environment perception, and has very good convenience and practicality.
Description
Technical field
What the present invention relates to is a kind of control method about mobile robot, specifically based on ROS(robot operating system, and RobotOperatingSystem), explore the control method of indoor environment.
Background technology
In recent years, robot field is developed rapidly, and such as disaster detecting robot, household service robot, accompany and attend to robot, military robot etc. are all widely used.Mobile robot, as the autonomous intelligent body of a kind of height, has locomitivity and powerful facilities for observation flexibly, utilizes the figure function of building of robot to replace the deeply dangerous circumstances not known of personnel to explore, has become the effective means of rescue work.Although current various rescue robots can complete various task, rescue robot major part relies on straighforward operation, cannot depart from manual control and move in the complex space of the unknown.And in disaster environment, cave in, environment space that flue dust is full of is unpredictable, simultaneously operating personnel are strong to the exploration recognition capability of disaster scene by video camera, and to a great extent by the impact of operating personnel's experience.Need a kind of intelligent mobile robot that can carry out autonomous exploration to disaster environment badly.
Meanwhile, robot, also towards complicated, universalization and the development of working environment uncertainization, proposes higher requirement to the reusability of code, modularization.The operating systems such as existing Player, MOOS, CARMEN, YARP, Orocos, Microsoft RoboticsStudio cannot meet the demand of practical application.ROS(RobotOperatingSystem) be that one is increased income robot operating system, the function being similar to operating system can be provided, there is provided hardware abstraction, bottom layer driving, Message Transmission for robot application system and assure reason, and some auxiliary development instruments, such as set up, write and run the program that multi-machine communication system is integrated.The design object of ROS operating system is exactly the reusability in order to improve code, so adopt a kind of distributed process framework, makes calling program have the independence of height and low coupling.
Consider above-mentioned factor, the present invention introduces the design of ROS robot operating system and constructs a kind of mobile robot platform, and hardware have employed iRobot differential driving chassis and information acquisition unit, data processing unit, motion control unit and remote monitoring unit 4 modules.Utilize ROS distributed process framework advantage, control is convenient explores indoor environment rapidly, obtains the two-dimensional map of indoor environment information, reaches and more effectively carries out robot disaster relief.
Summary of the invention
The present invention devises mobile robot's indoor environment searching system based on ROS and control method.
The technical solution used in the present invention is: the first stage, repacking and the application configuration based on ROS of robot; Subordinate phase, the environment information acquisition of laser radar is spliced with map and is mated; Phase III, build the radio communication between robot and host computer; Fourth stage, by arranging path planning algorithm, makes robot autonomous traveling, and explores indoor circumstances not known.
Described a kind of mobile robot's indoor environment searching system based on ROS and control method, realized by following steps.
Step one: the iRobotCreate produced with iRobot company of the U.S., for mobile robot platform, carries out reequiping and expands.
Step 2: adopt the navigation stack (Navigation) of ROS to realize the concrete framework of navigational system, by arranging TF system for coordinate transformation, Costmap occupies the basic configuration that grating map completes navigation stack.
Step 3: obtain cartographic information by laser radar, by laser radar data discretize.
Step 4: the laser radar information of acquisition is carried out scan matching.
Step 5: utilize the wireless telecommunications between Zigbee protocol structure robot and host computer, realizes host computer and obtains robotary and monitor in real time the X-Y scheme that laser radar obtains.
Step 6: synchronous location is carried out to robot and builds figure.
Step 7: the path planning algorithm that robot is set.
Step 8: robot independently travels, explores indoor circumstances not known simultaneously.
Below each step is specifically described.
The iRobotCreate mobile robot platform of described step one, remains motion controller and power-supply management system, eliminates dust-absorbing function, and extend sensor.Constructed mobile-robot system is made up of four parts, comprises information acquisition unit, data processing unit, motion control unit and remote monitoring unit.Its block diagram of system as shown in Figure 1.Wherein, control core is the industrial computer based on ATOM atom N270 central processing unit.
The basic thought of the navigation stack of the ROS of described step 2 is: obtain odometer and laser radar data, and output speed order is to robot chassis simultaneously, and navigation stack configuration as shown in Figure 2.TF system for coordinate transformation as shown in Figure 3, TF system definition two coordinate systems: the initial point of a coordinate system is positioned at the center chassis of robot, and another coordinate system is positioned at the center of laser radar.The coordinate system being positioned at chassis is defined as base_link, because navigation stack needs the rotation center this TF coordinate system being placed as mobile robot.The coordinate system being positioned at laser radar is defined as base_laser.Costmap occupies grating map and obtains by completing laser radar data sliding-model control.
Described step 3 map obtain stage, the first size of definition unit grid.This yardstick will determine the degree of discretize.The basic thought of discretize is: from robot current place coordinate, spread to surrounding with the size of element grid, make to be paved with dummy grid in plane, then laser radar range front end is fallen in corresponding grid, represent all range finding front end datas fallen in this grid by the occupation probability value of grid.This algorithm is realized by bilinear filter.
Described step 4 complete laser radar data discretize after, also just obtain local occupy grating map.Then by surface sweeping matching stage, scan matching is carried out to laser radar data, namely by local map, mobile robot's pose is estimated, local environment map is fused to global context map.
The ZigBee communication agreement of described step 5 is host computer and the communication between car and robot.Comprise the concrete direct of travel, running route etc. of robot; Comprise robot speed's setting, start/stop; The environment two-dimensional map that the laser radar data information comprising acquisition is formed.
The synchronous location of described step 6 with build figure and independently build nomography based on HectorSLAM.Hector is that increasing income of ROS robot operating system is navigated and build picture library, and its system architecture as shown in Figure 4.
The path planning algorithm of described step 7 is dijkstra's algorithm, and Dijkstra is the breadth-first search improved, and the process flow diagram of dijkstra's algorithm as shown in Figure 5.
The heuristic algorithm of described step 8 combines two kinds of now conventional strategies.A kind of is move to the front end nearest from robot to carry out map acquisition fast, expansion zone of ignorance.The another kind of size simultaneously considering front end in existing map, the place that leading portion is longer, like this by expanding larger zone of ignorance here.This patent is heavily weighted two tactful weightings.
Beneficial effect of the present invention: mobile robot's indoor environment searching system and control method, based on ROS system, utilize ROS to improve the advantage of the reusability of code, can travel through whole indoor zone of ignorance fast and explore.The two-dimensional environment figure of zone of ignorance scanning is built and reaches host computer by ZigBee wireless protocols, achieves detection and the monitoring in whole circumstances not known region.
Accompanying drawing explanation
Fig. 1 is mobile-robot system framework map.
Fig. 2 is the navigation stack system architecture figure of ROS.
Fig. 3 is TF system for coordinate transformation figure.
Fig. 4 is mobile robot's basic platform TF illustraton of model.
Fig. 5 is the bilinear filter of lattice map.
Fig. 6 occupies grating map discretize.
Fig. 7 is HectorSLAM system architecture figure.
Fig. 8 is Hectormapping system architecture diagram.
Fig. 9 is dijkstra's algorithm process flow diagram.
Figure 10 is dijkstra's algorithm exemplary plot.
Embodiment
Below in conjunction with accompanying drawing, the present invention is further described.
Be made up of soft and hardware two parts based on mobile robot's indoor environment searching system of ROS and control method.
Hardware components comprises: iRobot differential driving chassis and information acquisition unit, data processing unit, motion control unit and remote monitoring unit 4 modules.Software section comprises: ROS navigation stack, HectorSLAM independently build nomography, host computer interface and program, path planning algorithm.
Concrete implementation step is as follows.
Step one: the iRobotCreate produced with iRobot company of the U.S., for mobile robot platform, carries out reequiping and expands.
The maximum feature of iRobotCreate mobile robot platform to be programmed, according to the communication protocol that official provides, can the motion on control Create chassis and the reading of code-disc data, and this robot chassis has the features such as stable, cruising time is long.This patent is reequiped on the basis of original robot, builds the mobile robot adapting to required function, is made up of, comprises information acquisition unit, data processing unit, motion control unit and remote monitoring unit four parts.Data acquisition unit is mainly laser radar, and system reserves relevant interface.In motion control unit, the built-in photoelectric encoder in Create robot chassis, for the angle that register system wheel turns over, thus calculates the pose of robot.
Step 2: adopt the navigation stack (Navigation) of ROS to realize the concrete framework of navigational system, by arranging TF system for coordinate transformation, Costmap occupies the basic configuration that grating map completes navigation stack.
Stack is the set of function bag, and stack is also the principal mode of ROS software metric tools simultaneously.Stack has Manifest file, and its name is Stack.xml, is used for identifying the Dependency Specification of version information and function bag collection.ROS navigation stack needs to use TF system for coordinate transformation to issue the coordinate transform tree of robot.And the skew in changes in coordinates tree and system between different coordinates.As shown in Figure 3, mobile robot platform has the chassis of movement and the laser radar be positioned at above chassis.In this robot, TF system definition two coordinate systems: the initial point of a coordinate system is positioned at the center chassis of robot, and another coordinate system is positioned at the center of laser radar.The coordinate system being positioned at chassis is defined as base_link, because navigation stack needs the rotation center this TF coordinate system being placed as mobile robot.The coordinate system being positioned at laser radar is defined as base_laser.The TF that the iRobotCreate chassis of native system uses converts by arrow logo.
Mobile robot obtains directly to carry out SLAM operation from the range information of laser radar collection, because these data represent based on laser radar center, namely these data are under base_laser coordinate system.In order to these data can be used, need the coordinate transform carrying out data, namely transform to base_link from base_laser.In basic model as shown in Figure 3, known laser radar records and is located at 0.3m place, its dead ahead and has barrier, and laser radar is installed on front, chassis 0.1m, 0.2m place, top.Thus the coordinate conversion relation that can obtain from base_link to base_laser, base_link coordinate system translation (x:0.1m, y:0.0m, z:0.2m).So just can obtain the distance of barrier to robot chassis.As shown in Figure 4, suppose that base_link is father node, because all the sensors is all installed based on chassis.Therefore, the transformation matrix between base_link and base_laser is (x:0.1m, y:0.0m, z:0.2m).After setting up TF system, needing to create the node for issuing information converting, then creating the node listening to information converting.The TF system of ROS can manage easily.
Step 3: obtain cartographic information by laser radar, by laser radar data discretize.
In fact map obtains the stage is exactly that laser radar data is described environment, and this stage is also the stage of continuous print environment range information being carried out discretize.Then these discrete data are mated, local environment map is fused to global context map.
The stage is obtained at map, first will the size of definition unit grid.Element grid is less, and discretize degree is lower; On the contrary, element grid is larger, and dispersion degree is higher.The basic thought of discretize is: from robot current place coordinate, spread to surrounding with the size of element grid, make to be paved with dummy grid in plane, then laser radar range front end is fallen in corresponding grid, represent all range finding front end datas fallen in this grid by the occupation probability value of grid.This algorithm is realized by bilinear filter, as shown in Figure 5, and figure mid point P
mit is the grating map point of interpolation.Because himself discrete character of grating map limits the precision that map can reach, so require first just can obtain its map datum by interpolation calculation, the point by sub-grid cell is transformed into grating map by bilinear interpolation.Fig. 6 is the effect of occupying grating map discretize.
Certain point coordinate P on a given continuous map
m, occupy value for M (P
m), corresponding gradient is:
，
The coordinate P that four nearest can be used
00.11approximate:
。
Partial derivative can be approximated to be:
。
Step 4: the laser radar information of acquisition is carried out scan matching.
After completing laser radar data discretize, obtain local and occupy grating map.Then by the scan matching stage, scan matching is carried out to laser radar data, namely by local map, mobile robot's pose is estimated.This algorithm can not use odometer and carry out building figure, makes algorithm can be applied to the operating personnel's hand-held figure of building equipment or odometer is occurred compared with in the uneven environment of big error.
Ask mobile robot's pose
, following formula need be made minimum, that is will obtain the calibration that can make laser scanning the best:
。
Here, S
i(ζ) be Laser Radar Scanning end points S
i=(S
i,x, S
i,y)
tcoordinate in global coordinate system.They are functions of robot global coordinate system pose ζ:
。
Equation M (S
i(ζ)) coordinate S will be returned
i(ζ) map value at place.The estimated initial of certain ζ given, estimate that Δ ζ makes measuring error minimum:
。
Next algorithm processes above formula.First to M (S
i(ζ+Δ ζ)) carry out first order Taylor launch obtain:
。
This formula can by asking local derviation to obtain to Δ ζ:
。
Now, the question variation of Δ ζ is asked to become the problem of Gauss-Newton method minimizing:
。
Wherein, H is extra large gloomy matrix:
。
▽m (S
i(ζ)) for occupying the local derviation of grating map:
。
Step 5: utilize the wireless telecommunications between Zigbee protocol structure robot and host computer, realizes host computer and obtains robotary and monitor in real time the X-Y scheme that laser radar obtains.
Under same router, the main frame of configuration operation person's end and mobile robot from machine domain name mapping, thus complete the configuration that robot communicates with host computer.Now, two PCs carry out Data Data, only need to subscribe to same topic.By this wireless senser, build and hold computer to hold the operation circuit network of computer to mobile robot from operator.Operator can send pose instruction, and mobile robot receives the data transmitted by wireless network, then under the navigation stack framework of ROS, carries out posture tracking.
Step 6: synchronous location is carried out to robot and builds figure.
Hector is that increasing income of ROS robot operating system is navigated and build picture library, as shown in Figure 7.It is mainly used in, in the mobile-robot system of urban search and rescue task, giving the program architecture based on ROS and corresponding assembly.Hector modules can carry out stand-alone development and integration easily, meets the use of different configuration mobile robots and specific rescue occasion.Wherein topmost assembly is for navigating and building figure assembly (hector_slam), constructing environment map can not only by the environmental information residing for robot to operating personnel, and provide feasible region and locating information can to the path planning assembly on Navigation Database upper strata, hector_slam is only responsible for carrying out 2D and builds figure.The assembly of hector_slam comprises the hector_mapping for performing composition algorithm, for the hector_map_server that other assemblies provide map datum to serve, cartographic information is converted into the hector_geotiff of pictorial information and the hector_trajectory_server of heuristic algorithm generation track.Hector_slam only relies on laser radar data to carry out building figure and location, when road is rugged especially, inertial navigation can also be used to compensate SLAM algorithm, provide higher positioning precision.In addition, as shown in Figure 8, by hector_elevation_mapping, system can merge the Kinect depth camera of Microsoft, builds 2.5D cartographic information.The cloud data that Kinect obtains is that in 2D map, corresponding grid provides elevation information and variance thereof.Finally, hector_costmap can merge 2.5D height map and the grating map that occupies of 2D builds cost map.
Step 7: the path planning algorithm that robot is set.
Robot Path Planning Algorithm uses dijkstra's algorithm.Be specially and have the figure G of weight to operate to one, starting point is the set that S, V represent fixed points all in G, and E represents the set on limits all in G.(u, v) represents the path from summit u to vertex v, and the weight on limit is w:E → [0, ∞], then w (u, v) is the non-negative cost from summit u to vertex v, the distance namely before two summits.The cost value of one paths equal from path origin-to-destination the summation of cost value on limit of process.Dijkstra's algorithm can to find in figure G any two summits as the lowest-cost paths of s, t, i.e. shortest path.The process flow diagram of dijkstra's algorithm as shown in Figure 9.Figure 10 gives the example of dijkstra's algorithm.Algorithm concrete steps are as follows.
Step1: as shown in Figure 10, when algorithm starts, opens in list and only has starting point S, O={S}, and n
best=S, travels through the adjacent node of S node, and S is added closedown list, then, and and O={2,4,1,5}, C={S}.Corresponding cost function from starting point to current point is respectively, f (2)=1, f (4)=1, f (1)=2, f (5)=4.The point position 2 and 4 that cost function is minimum, appoints and gets one, make n
best=2, and now backward pointer all points to starting point S.
Step2: the adjacent node of node 2 is traveled through, now O={4,1,5}, C={S, 2}, and the adjacent node of node 2 only has S, and S is in closedown list, and algorithm continues to carry out downwards.
Step3: to current O={4, the minimum node 4 of the cost function in 1,5} carries out adjacent node traversal, n
best=4; Equally, move on to closedown list, O={1,5}, C={S, 2,4} by 4 from unlatching list, the adjacent node of 4 has S, 3,5, and wherein S is in closedown list, does not process it, and adds 3 in unlatching list.Have 5 owing to opening in list, and f (4)+c (4,5)=1+2=3 is less than f (5)=4 above, need to upgrade the cost function opening in list 5, then f (5)=3, and the backward pointer of 5 points to 4.
Step4: now open list and be respectively O={5,3}, C={S, 2,4}, n with closedown list
best=5.Process node 5, the adjacent node of 5 has 3, wherein 4 and S closedown list in, do not process, only surplus terminal G, therefore puts into unlatching list terminal G, O={G, 3}, C={S, 2,4,5}.
Step5: the minimum node of current cost function is n
best=G, f (G)=f (5)+c (5, G)=5.The backward pointer of respective nodes is taken out, also just have found a shortest path S → 4 → 5 → G from starting point S to terminal G.
Step 8: robot independently travels, explores indoor circumstances not known simultaneously.
Based on the basis that the environmental map of HectorSLAM builds, robot carries out autonomous traveling and builds figure.Mobile robot is when exploration zone of ignorance, and what need to carry out environment builds figure, also needs setting to build rule map simultaneously, makes can obtain maximum environmental map within the relatively short time.
The heuristic algorithm that native system uses combines two kinds of now conventional strategies.Move to the front end nearest from robot and can carry out map acquisition fast, expansion zone of ignorance.Consider the size of front end in existing map simultaneously.The place that front end is longer, often means by expanding larger zone of ignorance here.Weight is gone to be weighted to two strategies.Mobile robot gets the principle that wherein can obtain maximum map the soonest and carries out map structuring, until explore complete by all exploration front ends.
Claims (2)
1. based on a ROS(robot operating system, RobotOperatingSystem) mobile robot's indoor environment searching system and control method, comprise host computer, the iRobot robot of repacking, UTM30LX laser radar; By adopting the navigation stack of ROS and independently building nomography based on HectorSLAM, realize mobile robot to the autonomous exploration of indoor environment and build environment two-dimensional map.
2. a kind of mobile robot's indoor environment searching system based on ROS according to claim 1 and control method, is characterized in that: comprise following steps:
Step 1, the iRobotCreate that produces with iRobot company of the U.S., for mobile robot platform, carry out reequip and expand;
Step 2, adopt the navigation stack (Navigation) of ROS to realize the concrete framework of navigational system, by arranging TF system for coordinate transformation, Costmap occupies the basic configuration that grating map completes navigation stack;
Step 3, by laser radar obtain cartographic information and carry out image information process coupling;
Step 4, host computer obtain robotary and monitor in real time the two-dimensional environment cartographic information that laser radar obtains;
Step 5, the Hector storehouse in ROS is utilized to carry out synchronous location to robot and build figure;
Step 6, the Dijkstra path planning algorithm of robot is set;
Step 7, robot independently travel, and explore indoor circumstances not known simultaneously.
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