CN105629970A - Robot positioning obstacle-avoiding method based on supersonic wave - Google Patents
Robot positioning obstacle-avoiding method based on supersonic wave Download PDFInfo
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Abstract
The invention discloses a method which integrates binocular visual perception environment information, precisely corrects the posture, senses the environment information of a robot with the assistance of supersonic waves, builds a map and achieves the obstacle-avoiding walking according to the map. The method achieves the position of a moving robot based on a supersonic sensor, achieves the simultaneous positioning of the supersonic wave and the robot in the monocular vision and map building more quickly, achieves the autonomous navigation and obstacle-avoiding path planning in a household environment, achieves the multi-sensing comprehensive analysis, integrates the visual information, the information of the supersonic sensor and the information of an infrared sensor, and better achieves the multi-mode obstacle-avoiding path planning and autonomous navigation movement of the mobile robot.
Description
Technical field
The present invention relates to robot autonomous localization and technical field of environmental perception, especially a kind of based on hyperacoustic robot autonomous constructing environment map and barrier-avoiding method.
Background technology
Along with development in science and technology and social progress, the time that people stay at home is fewer and feweri, therefore the demand to household services is created, but the problem due to current household services itself, most people is unwilling also to worry and is given other people to keep an eye on property and household or look after, giving the robot that can trust is a good selection, has demand just to have market; Some robots are own through experimentally entering hospital, family abroad, are engaged in part auxiliary services, it is believed that in China along with the maturation of potential market demand, more education services robot also will be had to enter into common people house. Such as home care robot, educational robot, security robot, clean robot etc., therefore home-services robot will be well worth doing. Because the development of demand, people require that robot can the autonomous ability taking corresponding measure be also more and more stronger according to the change of surrounding in motor process. The home services intelligent robot of a new generation just requires to combine numerous advanced technologies such as machinery, electronics, sensor, computer software hardware, pattern recognition, artificial intelligence, industrial design together, is typical case's electro-mechanical system. A key factor avoidance and path planning as intelligent robot are just particularly important, and it is one of the key technology in robot research field, are the robot premises that complete other advanced tasks.
The avoidance of mobile apparatus people and path planning and mobile apparatus people, by sensory perceptual system detection external environment information, obtain information map after these information are processed, and reenact out track route, and in traveling process avoiding barrier. And by many people, the ability whether possessing simultaneous localization and mapping is thought whether robot is capable of the crucial precondition of independent navigation. In circumstances not known, it will be more complicated that the independent navigation of home-services robot realizes. Map building, location and path planning are three key elements of mobile robot autonomous navigation. When environment is unknown, the relation of map building and location similarly is the problem first having egg still first to have chicken.
Simultaneous localization and mapping is basic problem and the study hotspot in Mobile Robotics Navigation field, and under original state, environmental map is non-existent, therefore cannot demarcate the position of robot in map. On the other hand, not grasping initial pose, the establishment of map will not have datum mark yet. Just because of such reason, circumstances not known moves down the location of mobile robot and will realize in the way of simultaneous localization and mapping with map building. Namely mobile apparatus people is along with the exploration to environment, progressively expands the range of the map of self storage real-time being demarcated in newly created map by positional information. This technology is commonly referred to as location simultaneously and generates (SLAM, Simultaneouslocalizationandmapping) with map.
In SLAM system, comprise two kinds of information: i.e. the current pose of mobile apparatus people and the environmental map exploring region. Solve it is said that in general, SLAM system converts the inherent uncertainty that mobile apparatus people's pose is estimated to probability problem. Namely pass through to ask for robot pose to realize with the method combining Posterior probability distribution of environmental map. Assume the state Gaussian distributed of system, then SLAM can adopt Kalman filter to realize. Its covariance matrix contains uncertain information, and these information represent posture information and the cartographic information of mobile apparatus people.
The Patents of existing mobile apparatus people's simultaneous localization and mapping with view-based access control model is concentrated mainly on the subsystem in each special field and realizes, the patent close with the research contents of the present invention has " a kind of method realizing mobile apparatus people's simultaneous localization and mapping " [1] that China authorized in 2012, the method utilizes dead reckoning sensing data and road sign observation data for mobile apparatus people under circumstances not known, realize the autonomous location of mobile apparatus people by means of the Strong tracking filter technology improved, and construct environmental map simultaneously. this invention utilizes " strong tracking filfer ", self-adaptative adjustment Kalman gain, introduce a kind of new Multiple fading factor, ensure the symmetry of covariance matrix, reduce the computation complexity solving Kalman gain, for while status and map structuring problem in observation discontinuous problem, it is proposed that a kind of new algorithm flow, and give the computational methods of a kind of new Multiple fading factor. the patent of invention " location of a kind of intelligent robot and Map building method " [2] authorized for 2012 discloses location and the environmental modeling method of a kind of intelligent mobile robot, it is initially formed correction iterative extended Kalman filter algorithm and determines iterations, then set up motion model and the observation model of mobile apparatus people, initialize the state of mobile apparatus people, calculating position Jacobian matrix and control input Jacobian matrix to calculate, observe Jacobian matrix etc., finally by solving kalman gain matrix, update state estimation equation and covariance matrix, and repeat above section step. this invention to position with the most widely used expanded Kalman filtration algorithm in environmental modeling field as core while mobile apparatus people, by this algorithm is improved, the performance making algorithm is greatly improved, it is possible to better meet the application in SLAM. the patent of invention " based on the closed loop detection method of picture appearance in monocular vision SLAM " authorized for 2012, this invention includes: utilizes self-contained monocular cam to gather current scene image in mobile apparatus people's advance process, and extracts the visual dictionary feature of current scene image, image is carried out pretreatment, utilize the similarity to weigh between image of the inner product between image weights vector, the present image bigger with former frame history image similarity is rejected, utilize Bayesian filter method to constantly update closed loop and assume that the posterior probability of state carries out closed loop detection, it is judged that whether current scene image closed loop occurs, image is utilized against search method, the closed loop testing result obtained in upper step to be verified. further, this invention, in building visual dictionary process, utilizes TSC value as the evaluation criterion of cluster result, cluster classification number dynamically to be adjusted. the patent of invention " realizing device and the robot of indoor service robot simultaneous localization and mapping " [4] authorized for 2010 discloses a kind of indoor service robot that realizes and positions the device with map building and the indoor service robot with this device simultaneously, this device includes external sensor, internal sensor and message processing module, moved in external environment condition by described robot, record described external sensor and the measurement data of described internal sensor, environment is carried out feature extraction, the prediction of recursive form and update algorithm is utilized to draw pose and the characteristics map of described robot, when meeting characteristic matching, realize the renewal to corresponding described pose and characteristics map.The patent of invention " alignment system of a kind of household service robot and localization method " [5] authorized for 2013 relates to alignment system and the localization method of a kind of household service robot, at least three infrared transmitter is installed in a region, the household service robot central controller by self, infrared induction coordinate setting module, binocular visual positioning module, sonar auxiliary positioning module and Infrared Detectors carry out traveling operation and can automatic obstacle-avoiding in carrying out operation.
[1] a kind of method realizing mobile apparatus people's simultaneous localization and mapping, publication number: CN102402225A, inventor: Wen Feng, former chief, Chai Xiaojie
[2] location of a kind of intelligent robot and Map building method, publication number: CN102706342A, inventor: Zhang Yi, Luo Yuan, Xie Ying, Xu Xiaodong, Tang Xianlun, Li Min, Cai Jun, Hu Zhangfang
[3] based on the closed loop detection method of picture appearance, publication number: CN102831446A, inventor: Liang Zhiwei, Chen Yanyan, Zhu Songhao, Xu Guozheng in monocular vision SLAM
[4] device and the robot of indoor service robot simultaneous localization and mapping, publication number: CN101920498A, inventor: Qian Dongqi etc. are realized.
[5] alignment system of a kind of household service robot and localization method, publication number: CN103170980A, inventor: Qu Dong liter, Liu Yanwu, Zhu Ziqing, Li Changfeng
[6] Face detection based on multi-feature fusion and head pose recognition methods, publication number: CN1601549A, inventor: Tan Tieniu, Wei Yucheng, Zhou Chao
At present, the SLAM technology of comparatively conventional mobile apparatus people realizes including the big class of FastSLAM and vSLAM two. Both realizes all using optimization method to reduce computation complexity, makes mobile apparatus people SLAM be possibly realized. Wherein, FastSLAM system generally uses laser range finder or sonar realizes, and vSLAM then uses vision sensor to realize. FastSLAM is owing to employing the sensor such as laser, sonar, and the environmental information that some are special, as line segment, turning etc. do not identify its Special Significance. Just there is, in the work creating map, the shortcoming that quantity of information is less than normal in this. VSLAM then largely solves this problem, and reason is that vSLAM uses vision sensor, and the image of acquisition contains the information of relative abundance so that the information of some Special Significance is identified. But vSLAM there is also some problems, mainly visual information is excessively complicated, and computation complexity is of a relatively high, is difficulty with real-time when vision sensor obtains big image in different resolution; And often very big for the map information data amount under a certain position and posture of mobile apparatus people, when exploring environment and being very big, the storage of cartographic information also will face the challenge.
Summary of the invention
The technical problem to be solved in the present invention: for above-mentioned SLAM technology Problems existing, provide a kind of fusion binocular vision perception environmental information, precisely correct pose state auxiliary ultrasonic real-time perception robot environment's information, set up map and the method for avoidance walking according to the map.
Technical solution of the present invention:
A kind of based on hyperacoustic robot localization barrier-avoiding method, comprise the following steps:
Step 1, sets the size of working environment, specifies the region of robot work, the initial starting point of robot and the direction of robot, whole working environment is divided into X*Y grid, sets up an array for storing in X*Y rectangular grid either with or without barrier, array element is imported txt;
Step 2, mobile apparatus people's perception environment, specifically include: the initial point of the known regulation of a, robot dead ahead to, each ultrasound wave direction can be obtained; B is worth according to hyperacoustic time, by the direction of the known barrier of polar conversion and robot and distance; C to return value with ultrasound wave in the same direction by the value that binocular camera obtains and compares, and obtains the distance that robot is relatively accurate with barrier; D is known just to be set or current robot position in map, calculates and obtains the barrier position at map; In e traveling process, by encoder backoff values, obtain the current location of robot; F repeats a, b, step c, can obtain the barrier of ultrasonic listening position on figure during current location; G repeats e; Known robot working environment is finally converted to data and is stored in txt by h;
Step 3, recall map, and by ultrasound wave and photographic head perception robot present position, map judges in advance, whether can arrive the specific item punctuate that robot is current, the specific item punctuate that can arrive with special color mark, and continue to judge from the specific item punctuate that can arrive, can the next specific item punctuate of the specific item punctuate arrived arrive, can then labelling, until not having the specific item punctuate that can arrive or the certain area arriving impact point, completing avoidance end mark, starting robot has target avoidance duty;
Step 4, robot carries out there is target avoidance according to each targetpath point on planning circuit:
When a1 robot is in initial starting point, directly derives the data in txt, show current working environment map;
The data that b1 obtains according to binocular camera shooting header structure, the moment refreshes the current location of robot, it is ensured that the accuracy of the position of robot own is not affected by the accumulation of error;
C1 judges the distance of impact point and robot itself, arrives certain limit, then control module and chassis control module sends stopping traveling instruction, arrive impact point scope, otherwise carry out below step
If during the clear of d1 front, by calculating it is known that impact point and the angle difference of robot itself, as difference is little, then control module and chassis control module is sent corresponding instruction, advance and return; As difference is big, then control module and chassis control module is sent corresponding instruction, be turn left or turn right and return;
If there is barrier left and right clear in e1 front, then judging that impact point is in the direction of advance of robot, control module and chassis control module is sent corresponding instruction, turning left in the left side, turns right and return in the right;
If f1 front has that about barrier, two side one side's clear one sides have obstacle, controlling module and chassis control module is sent corresponding instruction, left side clear is turned left, and the right clear is turned right and returns;
If g1 front has when having barrier about barrier, by ultrasound wave backoff values below, it is judged that whether rear has barrier, has: control module and chassis control module is sent corresponding instruction, stop and returning; Nothing: control module and chassis control module is sent corresponding instruction, then control module and chassis control module sent corresponding instruction, is turn left or turn right and return;
H1 repeats b1 and judges;
In steps of 5, if the barrier that ultrasound examination does not have in map, then freedom of entry avoidance state, it is worth with according to hyperacoustic time, control module and chassis controller is sent order, make robot hide response accordingly, and to again the circuit of current goal point being planned.
In steps of 5, when selecting impact point in b1 each time, if impact point is in sector planning window, the directly sub-goal using impact point as current local window; If impact point is not in sector planning window, select the track points in original route planning as the specific item punctuate in sector planning window successively, if this track points occurs in local window, then select next track points as specific item punctuate, when there being multiple track points to occur in local window, select the nearest track points not appearing in local window as specific item punctuate.
The method have the benefit that
1. the various motor functions such as the motor system of the present invention is mainly made up of two-wheel drive unit and a universal wheel, and this classical architecture can allow the robot to realize no-radius and turn to, forward-reverse left-right rotation. Robot utilizes encoder two driving wheel operating number of turns that motor controls can be passed to host computer when advancing, host computer, by calculating, draws the current location of robot; Known current location, according to the barrier of ultrasound wave angle and the detection value back to host computer, the position of the barrier that 9 ultrasonic listenings are arrived when host computer calculates current location. Because the backoff values of the distance backoff values that ultrasonic listening is arrived, encoder, a calculating institute inevitably error, the time that robot advances is more long, error is more big, the perceptual distortion of surrounding enviroment is more big, so needing to constitute binocular vision system with two monocular cams, known object in perception surrounding enviroment, it is determined that the accuracy that will lose is corrected in currently accurate position by robot, the robot location simultaneously calculated; Thus reaching into the autonomous location of service robot, allowing the robot in home environment independent navigation and completing more to assist the function of human lives, inventive algorithm is relatively easy, it is adaptable to home-services robot is to surrounding enviroment perception requirement.
2. monocular vision sensor has cheap, simple in construction, is prone to the advantages such as demarcation, has become as the sensor that service robot must be joined, and uses the SLAM problem that monocular vision solves service robot also to become the selection of researcher of service robot; Owing to ultrasonic distance measuring module is relatively cheap, and can comparatively be accurately measured the distance of barrier, coordinate motor can realize turning to range finding, flexible avoidance. Robot autonomous navigation is applied very wide; And the combination of ultrasonic wave module and vision sensor, its advantage is apparent.
3. present invention achieves the localization for Mobile Robot based on ultrasonic sensor, achieve ultrasound wave and the robot simultaneous localization and mapping under monocular vision quickly, realize the independent navigation under home environment and obstacle-avoiding route planning, achieve the comprehensive analysis of many perception, merge the information such as vision, ultrasonic sensor, infrared sensor, achieve multi-modal obstacle-avoiding route planning and the independent navigation motion of mobile apparatus people preferably.
Accompanying drawing illustrates:
Fig. 1 is obstacle avoidance algorithm flow chart of the present invention.
Fig. 2 is Path selection schematic diagram in local window.
Detailed description of the invention:
A kind of for home-services robot, there is environment sensing, simultaneous localization and mapping, obstacle-avoiding route planning autonomous mobile robot, including:
(1) telecontrol equipment moved for robot, has autonomous function, it is possible to work under various modes, including follow the mode, patrol pattern and Deviant Behavior tupe; Telecontrol equipment is made up of 2 DC servo motors, 1 universal wheel, 1 motor drives and control circuit is constituted; Wherein, 2 direct current generators are connected with described device by described direct current motor drive circuit, and universal wheel is independently mounted at the dead ahead of home-services robot base.
(2) sensing device, the one or more following information of perception in the environment of average family: the visual information of perception surrounding, the obstacle detected around track route; Environmental perception device includes two monocular cams and 9 ultrasonic sensors, and for the multi-sense emerging system of environment sensing and simultaneous localization and mapping, above-mentioned ultrasonic sensor, vision sensor are connected with the PC main frame as host computer. Monocular cam is installed on robot head, and can be rotated (pitching with wave control) by servos control, and steering wheel is connected with head control.
(3) based on hyperacoustic SLAM technology, by frequently using monocular cam to extract data, robot location is corrected, the barrier that the corresponding ultrasonic listening of regeneration goes out, it is ensured that the ambient image of acquisition has rotational invariance.
(4) based on the working environment of home-services robot, computation complexity can be reduced under the premise substantially not reducing reliability significantly, reach to improve the purpose of correction robot location.
(5) when condition change is inviolent, monocular cam extracts the repetitive rate that robot location is corrected keeping higher by data; Improve correction robot location's frequency, make the barrier that ultrasonic listening goes out keep higher similarity;
(6) control device, control device, chassis control device and master control set including head; The multiple perceptual signal that described sensing device is received carries out comprehensive analysis processing, and the execution device sending instruction control described completes corresponding work; Chassis controller, head control are connected with the host computer as master controller respectively, host computer is mounted with based on core algorithms such as hyperacoustic simultaneous localization and mapping, obstacle-avoiding route plannings, main control unit by serial ports to chassis controller transmitting control commands, control motor and carry out corresponding actions, and obstacle signal is processed.
(7) perform device, receive signal and the instruction input of Intellisense device, complete the tasks such as the obstacle-avoiding route planning of robot, independent navigation.
Based on hyperacoustic home-services robot SLAMAlgorithm basic step is as shown in Figure 1:
(1) size of working environment is set; Specify the region of robot work, and the initial starting point of robot (x, y) and the direction of robot. Making robot create map convenient and swift, the method specifically building figure is as follows:
A) first whole working environment being divided into X*Y little grid, X, the size of Y is determined according to working environment;
B) array is set up, either with or without barrier in X*Y little rectangle of storage;
C), when the environment before work inputs (when robot first time explores environment), when often finding barrier, the rectangle at barrier place------, array element is set to 1, is otherwise 0;
D) wherein 0 representative does not have barrier, and 1 representative has barrier, and array element is imported txt, and the used time exports to array. Array just represents barrier; Equally also constitute the datumization map of working environment;
(2) manual operation robot, at workspace awareness environment; Method particularly includes:
A) initial point of known regulation, robot dead ahead to, each ultrasound wave direction can be obtained;
B) it is worth according to hyperacoustic time, by the direction of the known barrier of polar conversion and robot and distance;
C) value obtained by binocular camera to return value with ultrasound wave in the same direction and is compared, and obtains robot and the relatively accurate distance of barrier
D) known just set or current robot position in map, calculate and obtain the barrier position at map;
E), in traveling process, by encoder backoff values, the current location of robot is obtained;
F) repeat (a, b, c) step, the barrier of ultrasonic listening position on figure during current location can be obtained;
G) e is repeated;
H) finally known robot working environment is converted to data and is stored in txt;
I) can manpower comparing to actual environment, data in txt are revised;
After obtaining environmental map, according to robot current location and aiming spot on map, cook up the course of the overall situation, carry out avoidance and move, include target avoidance and free avoidance:
(3) free avoidance: the barrier that mobile apparatus people safely and effectively can avoid in advancing according to the status information of the barrier gathered advances towards target direction. Only with two step of a, b in (2), it is worth with according to hyperacoustic time, controls module and chassis controller is sent order, make robot hide (advance, turn left, turn right, retreat, stop) response accordingly.
(4) have target barrier-avoiding method as follows:
A), when robot is in initial starting point, directly derives the data in txt, show current working environment map;
B) data obtained according to binocular camera shooting header structure, the moment refreshes the current location of robot, it is ensured that the accuracy of the position of robot own is not affected by the accumulation of error;
C) judge the distance of impact point and robot itself, arrive certain limit, then control module and chassis control module is sent stopping traveling instruction, arrive impact point scope, otherwise carry out below step
If d) during the clear of front, by calculating it is known that impact point and the angle difference of robot itself, as difference is little, then control module and chassis control module is sent corresponding instruction, advance and return; As difference is big, then control module and chassis control module is sent corresponding instruction, be turn left or turn right and return;
E) if there is barrier left and right clear in front, then judge that impact point is in the direction of advance of robot. Controlling module and chassis control module is sent corresponding instruction, turning left in the left side, turns right and return in the right;
F) if front has that about barrier, two side one side's clear one sides have obstacle, controlling module and chassis control module is sent corresponding instruction, left side clear is turned left, and the right clear is turned right and returns;
If g) front has when having barrier about barrier, by ultrasound wave backoff values below, it is judged that whether rear has barrier, has: control module and chassis control module is sent corresponding instruction, stop and returning; Nothing: control module and chassis control module is sent corresponding instruction, then control module and chassis control module sent corresponding instruction, is turn left or turn right and return;
H) repeat b to judge;
(5) in Mobile Robot Obstacle Avoidance path planning process, it it is a local paths planning problem in each local window, with the overall situation obstacle-avoiding route planning the difference is that, it needs to be determined that the impact point (as transient target point) of local window before planning, and localized target point choose the performance that can directly affect final path planning. Hence with the track points of overall situation coarseness path planning as the specific item punctuate of local paths planning, it is possible to provide global optimization to require information for local obstacle-avoiding route planning, improve the optimization performance of system. Overall situation coarseness track points is used to include following three kinds of situations as localized target point: 1) impact point G is in sector planning window, directly using impact point as the sub-goal (transient target) of current local window as shown in Figure 2 (a) shows; Such as G not in sector planning window, select the track points in coarseness path planning as the specific item punctuate in sector planning window successively, as shown in Fig. 2 (b), if this track points occurs in local window, then select next track points as specific item punctuate. When there being multiple track points to occur in local window, as shown in Fig. 2 (c), select the nearest track points not appearing in local window as specific item punctuate.
(6) during the planning of driftlessness avoidance, the i.e. method according to free avoidance, initially with the method choice specific item punctuate in (5), judging in advance on map, whether robot can arrive current specific item punctuate, the words of energy, the specific item punctuate that can arrive with special color mark, and continue to judge from the specific item punctuate arrived, it is possible to can the next specific item punctuate of the specific item punctuate of arrival arrive, can then labelling, it is impossible to not labelling;
(7) when having target avoidance to plan, just it is based on known map, with the method having target avoidance, adopt the method choice specific item punctuate of (5), map judges in advance, whether can arrive the specific item punctuate that robot is current, the words of energy, the specific item punctuate that can arrive with special color mark, and continue to judge from the specific item punctuate that can arrive, can the next specific item punctuate of the specific item punctuate arrived arrive, can then labelling, have to labelling, until not having the certain area of the specific item punctuate that can arrive or arrival impact point to meet have target obstacle avoidance algorithm, it is successfully completed avoidance, end mark, starting robot has target avoidance duty,
(8) no matter with or without impact point obstacle-avoiding route planning, if having dynamic object or person to exist, the route that robot is walked all is not necessarily the route of planning;
This method is the obstacle-avoiding route planning function being completed service robot by the control window write of the MFC in VS2010, through experimental check, despite the presence of corresponding error, but is all suitable in claimed range in the expectation of home-services robot.
Claims (2)
1. one kind based on hyperacoustic robot localization barrier-avoiding method, it is characterised in that comprise the following steps:
Step 1, sets the size of working environment, specifies the region of robot work, the initial starting point of robot and the direction of robot, whole working environment is divided into X*Y grid, sets up an array for storing in X*Y rectangular grid either with or without barrier, array element is imported txt;
Step 2, mobile apparatus people's perception environment, specifically include: the initial point of the known regulation of a, robot dead ahead to, each ultrasound wave direction can be obtained; B is worth according to hyperacoustic time, by the direction of the known barrier of polar conversion and robot and distance; C to return value with ultrasound wave in the same direction by the value that binocular camera obtains and compares, and obtains the distance that robot is relatively accurate with barrier; D is known just to be set or current robot position in map, calculates and obtains the barrier position at map; In e traveling process, by encoder backoff values, obtain the current location of robot; F repeats a, b, step c, can obtain the barrier of ultrasonic listening position on figure during current location; G repeats e; Known robot working environment is finally converted to data and is stored in txt by h;
Step 3, recall map, and by ultrasound wave and photographic head perception robot present position, map judges in advance, whether can arrive the specific item punctuate that robot is current, the specific item punctuate that can arrive with special color mark, and continue to judge from the specific item punctuate that can arrive, can the next specific item punctuate of the specific item punctuate arrived arrive, can then labelling, until not having the specific item punctuate that can arrive or the certain area arriving impact point, completing avoidance end mark, starting robot has target avoidance duty;
Step 4, robot carries out there is target avoidance according to each targetpath point on planning circuit:
When a1 robot is in initial starting point, directly derives the data in txt, show current working environment map;
The data that b1 obtains according to binocular camera shooting header structure, the moment refreshes the current location of robot, it is ensured that the accuracy of the position of robot own is not affected by the accumulation of error;
C1 judges the distance of impact point and robot itself, arrives certain limit, then control module and chassis control module sends stopping traveling instruction, arrive impact point scope, otherwise carry out below step
If during the clear of d1 front, by calculating it is known that impact point and the angle difference of robot itself, as difference is little, then control module and chassis control module is sent corresponding instruction, advance and return; As difference is big, then control module and chassis control module is sent corresponding instruction, be turn left or turn right and return;
If there is barrier left and right clear in e1 front, then judging that impact point is in the direction of advance of robot, control module and chassis control module is sent corresponding instruction, turning left in the left side, turns right and return in the right;
If f1 front has that about barrier, two side one side's clear one sides have obstacle, controlling module and chassis control module is sent corresponding instruction, left side clear is turned left, and the right clear is turned right and returns;
If g1 front has when having barrier about barrier, by ultrasound wave backoff values below, it is judged that whether rear has barrier, has: control module and chassis control module is sent corresponding instruction, stop and returning; Nothing: control module and chassis control module is sent corresponding instruction, then control module and chassis control module sent corresponding instruction, is turn left or turn right and return;
H1 repeats b1 and judges;
According to claim 1 based on hyperacoustic robot localization barrier-avoiding method, it is characterized in that: in steps of 5, if the barrier that ultrasound examination does not have in map, then freedom of entry avoidance state, it is worth with according to hyperacoustic time, control module and chassis controller is sent order, make robot hide response accordingly, and to again the circuit of current goal point being planned.
2. according to claim 1 based on hyperacoustic robot localization barrier-avoiding method, it is characterized in that: in steps of 5, when selecting impact point in b1 each time, if impact point is in sector planning window, the directly sub-goal using impact point as current local window; If impact point is not in sector planning window, select the track points in original route planning as the specific item punctuate in sector planning window successively, if this track points occurs in local window, then select next track points as specific item punctuate, when there being multiple track points to occur in local window, select the nearest track points not appearing in local window as specific item punctuate.
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