WO2018187944A1 - 基于地图预测的机器人运动控制方法 - Google Patents

基于地图预测的机器人运动控制方法 Download PDF

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Publication number
WO2018187944A1
WO2018187944A1 PCT/CN2017/080137 CN2017080137W WO2018187944A1 WO 2018187944 A1 WO2018187944 A1 WO 2018187944A1 CN 2017080137 W CN2017080137 W CN 2017080137W WO 2018187944 A1 WO2018187944 A1 WO 2018187944A1
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Prior art keywords
robot
obstacle
map
motion
wall surface
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PCT/CN2017/080137
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English (en)
French (fr)
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肖刚军
赖钦伟
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珠海市一微半导体有限公司
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Priority to US16/604,576 priority Critical patent/US11144064B2/en
Priority to JP2019555955A priority patent/JP6946459B2/ja
Priority to KR1020197032232A priority patent/KR102260529B1/ko
Priority to PCT/CN2017/080137 priority patent/WO2018187944A1/zh
Priority to EP17905205.5A priority patent/EP3611589B1/en
Publication of WO2018187944A1 publication Critical patent/WO2018187944A1/zh

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    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
    • G05D1/02—Control of position or course in two dimensions
    • G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
    • G05D1/0231—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means
    • G05D1/0238—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means using obstacle or wall sensors
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
    • G05D1/02—Control of position or course in two dimensions
    • G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
    • G05D1/0227—Control of position or course in two dimensions specially adapted to land vehicles using mechanical sensing means, e.g. for sensing treated area
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
    • G05D1/02—Control of position or course in two dimensions
    • G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
    • G05D1/0212—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory
    • G05D1/0214—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory in accordance with safety or protection criteria, e.g. avoiding hazardous areas
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
    • G05D1/02—Control of position or course in two dimensions
    • G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
    • G05D1/0231—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means
    • G05D1/0238—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means using obstacle or wall sensors
    • G05D1/024—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means using obstacle or wall sensors in combination with a laser
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
    • G05D1/02—Control of position or course in two dimensions
    • G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
    • G05D1/0231—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means
    • G05D1/0242—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means using non-visible light signals, e.g. IR or UV signals
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
    • G05D1/02—Control of position or course in two dimensions
    • G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
    • G05D1/0255—Control of position or course in two dimensions specially adapted to land vehicles using acoustic signals, e.g. ultra-sonic singals
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
    • G05D1/02—Control of position or course in two dimensions
    • G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
    • G05D1/0268—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
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
    • B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
    • B25J11/00—Manipulators not otherwise provided for
    • B25J11/008—Manipulators for service tasks

Definitions

  • the invention belongs to the field of artificial intelligence technology, and particularly relates to related technologies of auxiliary robots such as home life.
  • the more common way is to obtain the distance information from the wall through the distance sensor or the infrared sensor to realize the wall along the wall.
  • the distance sensor can accurately know the distance between the walls, which is a good choice, but the cost is relatively high, and there are also false detections on the uneven wall surface, so more robots use infrared sensors.
  • the infrared sensor is easily affected by the color and unevenness of the wall surface, and it is not dependent on the infrared sensor, and it does not get very good results.
  • the invention aims to combine the external sensor and the internal map information of the robot to make an estimated calculation of the wall surface, and let the robot walk according to the estimated wall surface.
  • the object of the invention is achieved by the following technical solutions:
  • a robot motion control method based on map prediction is based on a robot body, a left and right motion wheel, a main control module, a front end collision detection sensor, a left obstacle detection sensor and a right obstacle detection sensor, and the main control
  • the module has a map management function and a robot positioning function; and the control method includes:
  • step (1) Control the robot to walk toward the wall on the map.
  • the robot collides with the first touch point of the obstacle determine whether the distance between the obstacle and the wall on the map is less than the set distance A, and the current encounter
  • the obstacle position determines a straight line L1 at the same angle as the wall on the map for the reference point, and the straight Line L1 is set to predict the wall surface, and the control robot executes the edge along the predicted wall surface; otherwise, it proceeds to step (2);
  • step (2) controlling the robot to perform detection of the second touch point of the first touch point on the obstacle, and if there is a second touch point, determining a straight line L2 according to the two touch points, and the line is L2 is set to predict the wall surface, and the control robot executes the edge along the predicted wall surface; otherwise, it returns to step (1);
  • the obstacle detecting sensor on the side of the predicted wall is detected by the robot at every set time T to detect whether the obstacle exists on the side, and when the obstacle signal is not detected continuously At this time, the control robot takes an arc-shaped route toward the inside of the predicted wall and returns to step (1).
  • the interval is the length of the body of the body.
  • the step (2) is replaced by the step (2a): controlling the robot to perform at least two distance detections on the obstacle, and if at least two distances are detected, the obstacle is detected.
  • a straight line L2 is determined according to the two obstacle points obtained by the two distance detections, and the straight line L2 is set as the predicted wall surface, and the control robot executes the edge along the predicted wall surface; otherwise, returns to step (1).
  • step (2) is replaced by the step (2b): controlling the robot to detect the at least two touch points of the obstacle execution interval, if there is the second touch point, A straight line L2 is determined according to the comprehensive orientation of all the touch points, and the straight line L2 is set as the predicted wall surface, and the control robot executes the edge along the predicted wall surface; otherwise, returns to step (1).
  • the second touch point is detected by: controlling the robot to retreat the set distance B from the first touch point, controlling the robot to turn the set angle Q, and controlling the robot to the obstacle side Take the arc route and look for the second touch point.
  • the set distance B is one quarter of the body of the body, and the set angle Q is 90 degrees.
  • the specific method for the control robot to take an arc route toward the obstacle side is: the control robot is located The action wheel on the far side of the obstacle travels four times faster than the action wheel on the near side.
  • the initial length of the straight line L2 is ten times that of the body of the body.
  • the predetermined time T is taken to take the time when the robot takes two times the length of the body.
  • the continuous detection of the obstacle signal means that the obstacle signal is not detected for two set times T.
  • the specific method for the control robot to take an arc-shaped route toward the inner side of the predicted wall surface is: the control robot is located at a speed of four times as long as the action wheel on the opposite side of the motion wheel on the far side of the predicted wall surface.
  • the utility model provides a robot motion control method based on map prediction, which has the beneficial effects that: according to the manner of map prediction, various wall surfaces can be adapted, including different colors and different shapes, and the running time can be reduced; During the operation process, the map prediction accuracy is continuously corrected to achieve excellent wall-to-wall behavior.
  • FIG. 1 is a schematic diagram of a structure of a robot based on a map motion control method based on map prediction according to an embodiment of the present invention.
  • FIG. 2 is a method for predicting a wall surface having a reference wall for an internal map in a robot motion control method based on map prediction according to an embodiment of the present invention.
  • FIG. 3 is a schematic diagram of a method for predicting a wall surface without an internal map in a robot motion control method based on map prediction according to an embodiment of the present invention.
  • FIG. 4 is a schematic diagram of a method for predicting a corner of a corner in a robot motion control method based on map prediction according to an embodiment of the present invention.
  • FIG. 5 is a schematic diagram of a comparison between a map prediction method and a normal signal following method for a robot motion control method based on map prediction according to an embodiment of the present invention.
  • the embodiment provides a robot motion control method based on map prediction, and the robot based on the method is active in a space having a wall surface 6 .
  • the robot includes a body 1, action wheels 2 and 3, a main control module 4, a collision detecting sensor 5, and obstacle detecting sensors 7 and 8.
  • the collision detecting sensor 5 is disposed at the front end of the body 1 for detecting a collision, and may be a physical collision detecting unit or Non-contact detection unit such as ultrasonic or laser.
  • the obstacle detecting sensors 7 and 8 are respectively disposed on both sides of the body 1 for detecting obstacles on both sides of the body, and may be distance sensors based on ultrasonic waves or lasers, or sensors such as infrared rays.
  • the main control module 4 is used to process various information, including information collected by each sensor and information on map establishment, storage, and use, while controlling the actions of the action wheels 2 and 3.
  • the robot motion control method based on map prediction provided by this embodiment has the following points: the prediction of the wall surface has the following situations:
  • the robot has a complete map inside.
  • the robot knows where the wall is.
  • the robot walks toward the wall with reference to the wall on the map.
  • the machine hits an obstacle 12. If the obstacle encountered and the wall surface error on the map is less than a certain distance, generally take 20cm.
  • Obtaining a predicted wall surface 14 which is a straight line based on the position of the currently encountered obstacle, and the direction of the straight line is the direction of the original map wall surface, for example, the wall marked on the original map is 0 degree, The angle of the predicted wall is also 0 degrees.
  • the internal map of the robot is incomplete, but obstacles are detected in the front and need to be processed along the wall. At this point, the robot needs multiple distance detection or collision detection to obtain the direction of the wall. The number of collisions depends on the machine sensor settings. If the collision sensor of the machine can accurately obtain the distance of the obstacle, only two points can be connected to form a straight line.
  • the touch point is generally selected as the length of the machine body. As shown in Figure 3, the robot has a touch point 22 first. The machine follows the route 25 and retreats a little distance, such as a quarter of the fuselage, then turns an angle, generally takes 90 degrees, and then the two wheels are not equal. Going forward, generally taking four times the outer wheel is the inner wheel, the machine continues to collide with the touch point 23.
  • This line is ten times the length of the fuselage, and the length is extended as the machine moves.
  • This line is the predicted wall surface 24.
  • the robot walks according to the virtual wall surface, and confirms the existence of the wall surface through the side sensor at intervals.
  • the interval time generally takes the time when the robot takes 2 times the length of the fuselage, and the wall surface is continuously corrected by this information.
  • the new route needs to be re-predicted, as shown in FIG.
  • the robot walks along the predicted route 32, and when the robot moves to the position in the figure, no signal is continuously detected, the robot Without the constant speed of the arc route 34, the outer wheel speed is generally four times the inner wheel speed, and the new route 35 is re-predicted.
  • the wall is not completely flat, there are several A pillar, similar to a general corridor design. If the robot is controlled according to the signal of the side sensor, when the robot walks to the column, there will be a short signal loss, the distance will become larger, and the driving robot will turn into the column. At this time, the route will be twisted and twisted. May hit the pillar.
  • the robot of the present invention predicts the dotted line by the map, which is a very straight line. The robot walks according to the predicted route. When the column passes, it still walks according to the route. After the column, the side sensor returns a signal indicating the wall. The face is still valid, the robot continues to follow the predetermined route, and the robot's route is always straight.
  • the map motion-based robot motion control method provided by the embodiment has the beneficial effects that: according to the map prediction manner, various wall surfaces can be adapted, including different colors and different shapes, and the running time is reduced.

Abstract

一种基于地图预测的机器人运动控制方法，主要结合外部传感器和机器人内部地图信息，做出墙面的预估计算，让机器人按照预估的墙面进行行走。该方法提供的基于地图预测的机器人运动控制方法，基于地图预测的方式，可以适应各种不同的墙面，包括不同的颜色、不同的形状，减少运行的时间；还可以在运行过程中不断修正地图预测准确度，实现优良的沿墙行为。

Description

基于地图预测的机器人运动控制方法 〖技术领域〗
本发明属于人工智能技术领域，尤其涉及家用生活等辅助机器人的相关技术。
〖背景技术〗
随着技术发展和人们对舒适生活的追求，自主行动机器人越来越多进入到人们生活当中，如陪伴机器人、扫地机器人等。沿墙(沿边)行为是很多类型的机器人需要做的行为，通过沿墙，可以实现角落的覆盖或者迷宫的脱困。所述沿墙中的墙或墙面不应该被单纯地理解为建筑物的墙面，应该还包括因家具等摆设后限制的边界，更应该理解为机器人通常情况下可活动范围的一个边界。
目前比较多的方式是通过距离传感器或者是红外传感器，获取与墙面的距离信息，来实现墙面的沿墙。距离传感器可以精确知道墙面的距离，是一个不错的选择，但是成本比较高，对于凹凸不平的墙面也存在误检测，所以比较多的机器人使用红外传感器。红外传感器容易受到墙面的颜色、凹凸不平等因素的影响，单纯依赖于红外传感器，并不能得到非常好的效果。
〖发明内容〗
本发明旨在结合外部传感器和机器人内部地图信息，做出墙面的预估计算，让机器人按照预估的墙面进行行走。本发明的目的由以下技术方案实现：
一种基于地图预测的机器人运动控制方法，该方法基于的机器人包括机体、左右行动轮、主控模块、前端碰撞检测传感器、左侧障碍物检测传感器和右侧障碍物检测传感器，所述主控模块具有地图管理功能及机器人定位功能；其特征在于，所述控制方法包括：
(1)控制机器人朝向地图上的墙面行走，当机器人碰撞到障碍物第一触碰点时，判断障碍物与地图上的墙面的距离是否小于设定距离A，是则以当前碰到的障碍物位置为基准点确定一条与地图上的墙面相同角度的直线L1，并将该直 线L1设定为预测墙面，控制机器人按照预测墙面执行沿边；否则进入步骤(2)；
(2)控制机器人对障碍物执行间隔所述第一触碰点的第二触碰点的检测，如果存在第二触碰点，则根据两个触碰点确定一条直线L2，并将该直线L2设定为预测墙面，控制机器人按照预测墙面执行沿边；否则返回步骤(1)；
其中，控制机器人按照预测墙面执行沿边的过程中，每隔设定时间T通过机器人位于预测墙面一侧的障碍物检测传感器检测该侧的障碍物是否存在，当持续没有检测到障碍物信号时，控制机器人向预测墙面内侧走弧形路线，并返回步骤(1)。
作为具体的技术方案，所述间隔为机体机身的长度。
作为具体的技术方案，所述步骤(2)由步骤(2a)替代，步骤(2a)：控制机器人对障碍物执行间隔的至少两次距离检测，如果间隔的至少两次距离检测均检测到障碍物点，则根据两次距离检测获取的两个障碍物点确定一条直线L2，并将该直线L2设定为预测墙面，控制机器人按照预测墙面执行沿边；否则返回步骤(1)。
作为具体的技术方案，所述步骤(2)由步骤(2b)替代，步骤(2b)：控制机器人对障碍物执行间隔的至少两个触碰点的检测，如果存在第二触碰点，则根据所有触碰点的综合走向确定一条直线L2，并将该直线L2设定为预测墙面，控制机器人按照预测墙面执行沿边；否则返回步骤(1)。
作为具体的技术方案，所述第二触碰点的检测，具体方法为：控制机器人从所述第一触碰点后退设定距离B，控制机器人转设定角度Q，控制机器人向障碍物侧走弧形路线，寻找第二触碰点。
作为具体的技术方案，所述设定距离B为机体机身的四分之一，设定角度Q为90度，所述控制机器人向障碍物侧走弧形路线的具体方法为：控制机器人位于障碍物远侧的行动轮相对近侧的行动轮以四倍的速度行走。
作为具体的技术方案，所述直线L2的初始长度是机体机身的十倍。
作为具体的技术方案，所述每隔设定时间T取机器人走机身长度2倍距离的时间。
作为具体的技术方案，所述持续没有检测到障碍物信号是指两个设定时间T没有检测到障碍物信号。
作为具体的技术方案，所述控制机器人向预测墙面内侧走弧形路线的具体方法为：控制机器人位于预测墙面远侧的行动轮相对近侧的行动轮以四倍的速度行走。
本发明提供的基于地图预测的机器人运动控制方法，其有益效果在于：基于地图预测的方式，可以适应各种不同的墙面，包括不同的颜色，不同的形状，减少运行的时间；还可以在运行过程中不断修正地图预测准确度，实现优良的沿墙行为。
〖附图说明〗
图1为本发明实施例提供的基于地图预测的机器人运动控制方法所基于的机器人的构成示意图。
图2为本发明实施例提供的基于地图预测的机器人运动控制方法中对于内部地图有参考墙面的预测墙面方法。
图3为本发明实施例提供的基于地图预测的机器人运动控制方法中对于无内部地图的预测墙面方法。
图4为本发明实施例提供的基于地图预测的机器人运动控制方法中对于转角的预测墙面方法。
图5为本发明实施例提供的基于地图预测的机器人运动控制方法下地图预测和普通信号跟随方法对比的示意图。
〖具体实施方式〗
下面结合附图对本发明的具体实施方式作进一步说明：
如图1所示，本实施例提供一种基于地图预测的机器人运动控制方法，该方法所基于的机器人在具有墙面6的空间内活动。机器人包括机体1、行动轮2和3、主控模块4、碰撞检测传感器5、障碍物检测传感器7和8。碰撞检测传感器5设置于机体1前端，用于检测碰撞，可以是物理的碰撞检测单元或者是 超声波、激光等非接触式检测单元。障碍物检测传感器7和8分别设置于机体1两侧，用于检测机体两侧的障碍物，可以是基于超声波或者激光等的距离传感器，或者是红外等传感器。主控模块4用于处理各种信息，包括各传感器采集的信息以及地图建立、保存、使用的信息，同时控制行动轮2和3的动作。
本实施例提供的基于地图预测的机器人运动控制方法，其要点是对墙面的预测，有以下几种情况：
(1)机器人内部已经有完整的地图，机器人自己知道墙面在哪里，则机器人参照地图上的墙面朝墙面行走，如图2所示，地图内部有了一个墙面13，但是由于误差的原因，机器人实际的位置和墙面还存在一点距离，此时，机器撞到了一个障碍物12，如果碰到的障碍物和地图上的墙面误差小于一定的距离，一般取20cm，就可以获得预测墙面14，这个墙面是根据当前碰到的障碍物位置为基准点的一条直线，直线的方向是原来地图墙面的方向，例如原来地图上标记的墙面是0度，则获得的预测墙面的角度也是0度。
(2)机器人内部地图不完整，但是前面检测到了障碍物，同时需要做沿墙处理。此时，机器人需要多次的距离检测或者碰撞检测，获取墙面的走向。碰撞的次数，取决于机器传感器设置，如果机器的碰撞传感器能够比较准确的获取障碍物的距离，则只需要两个点就可以连成一条直线，触碰点一般选取为机器机身的长度。如图3所示，机器人先有了触碰点22，机器按照路线25，先后退一点距离，如四分之一的机身，然后转一个角度，一般取90度，然后两个轮子不等速往前走，一般取外轮是内轮的四倍，机器继续碰撞到触碰点23。通过这两个触碰点，就可以连成一条直线，这条直线的长度初始长度是机身的十倍，长度随着机器的走动而延长，这条直线就是预测墙面24。机器人按照这个虚拟的墙面走向进行行走，隔一段时间通过侧面传感器确认墙面的存在，间隔的时间一般取机器人走机身长度2倍距离的时间，并且通过这个信息不断的修正预测墙面。
在上述两种方式中，当机器按照预测的路线行走了一个预定的距离，中间一直没有检测到信号时，需要重新预测新的路线，如图4所示。机器人沿着预测到的路线32行走，机器人走到图中的位置时，持续没有检测到信号，机器人 不等速走弧形路线34，一般取外轮子速度是内轮子速度的四倍，重新预测到新的路线35。
作为一个实例，如图5(其中51为地图上的墙面，52为现有技术机器人基于信号走的路线，53为本方法基于地图预测走的路线)，墙面不是完全平整，中间有几个柱子，类似于一般的走廊设计。如果是完全按照侧面传感器的信号进行机器人的控制，那么机器人走到柱子时，会有短暂的信号丢失，距离变大，驱动机器人往柱子里面拐，此时走的路线就会一扭一扭的，可能碰上柱子。而本发明的机器人通过地图预测是虚线部分，它是一个很笔直的线，机器人按照预测的路线进行行走，当过柱子时，还是按照路线进行行走，经过柱子，侧面传感器返回了信号，表示墙面依旧有效，则机器人继续按照预定路线行走，机器人的路线一直是笔直的。
本实施例提供的基于地图预测的机器人运动控制方法，其有益效果在于：基于地图预测的方式，可以适应各种不同的墙面，包括不同的颜色，不同的形状，减少运行的时间。
以上实施例仅为充分公开而非限制本发明，凡基于本发明的创作主旨、未经创造性劳动的等效技术特征的替换，应当视为本申请揭露的范围。

Claims (10)

  1. 一种基于地图预测的机器人运动控制方法，该方法基于的机器人包括机体、左右行动轮、主控模块、前端碰撞检测传感器、左侧障碍物检测传感器和右侧障碍物检测传感器，所述主控模块具有地图管理功能及机器人定位功能；其特征在于，所述控制方法包括：
    (1)控制机器人朝向地图上的墙面行走，当机器人碰撞到障碍物第一触碰点时，判断障碍物与地图上的墙面的距离是否小于设定距离A，是则以当前碰到的障碍物位置为基准点确定一条与地图上的墙面相同角度的直线L1，并将该直线L1设定为预测墙面，控制机器人按照预测墙面执行沿边；否则进入步骤(2)；
    (2)控制机器人对障碍物执行间隔所述第一触碰点的第二触碰点的检测，如果存在第二触碰点，则根据两个触碰点确定一条直线L2，并将该直线L2设定为预测墙面，控制机器人按照预测墙面执行沿边；否则返回步骤(1)；
    其中，控制机器人按照预测墙面执行沿边的过程中，每隔设定时间T通过机器人位于预测墙面一侧的障碍物检测传感器检测该侧的障碍物是否存在，当持续没有检测到障碍物信号时，控制机器人向预测墙面内侧走弧形路线，并返回步骤(1)。
  2. 根据权利要求1所述的基于地图预测的机器人运动控制方法，其特征在于，所述间隔为机体机身的长度。
  3. 根据权利要求1所述的基于地图预测的机器人运动控制方法，其特征在于，所述步骤(2)由步骤(2a)替代，步骤(2a)：控制机器人对障碍物执行间隔的至少两次距离检测，如果间隔的至少两次距离检测均检测到障碍物点，则根据两次距离检测获取的两个障碍物点确定一条直线L2，并将该直线L2设定为预测墙面，控制机器人按照预测墙面执行沿边；否则返回步骤(1)。
  4. 根据权利要求1所述的基于地图预测的机器人运动控制方法，其特征在于，所述步骤(2)由步骤(2b)替代，步骤(2b)：控制机器人对障碍物执行间隔的至少两个触碰点的检测，如果存在第二触碰点，则根据所有触碰点的综合走向确定一条直线L2，并将该直线L2设定为预测墙面，控制机器人按照预测墙面执行沿边；否则返回步骤(1)。
  5. 根据权利要求1所述的基于地图预测的机器人运动控制方法，其特征在 于，所述第二触碰点的检测，具体方法为：控制机器人从所述第一触碰点后退设定距离B，控制机器人转设定角度Q，控制机器人向障碍物侧走弧形路线，寻找第二触碰点。
  6. 根据权利要求5所述的基于地图预测的机器人运动控制方法，其特征在于，所述设定距离B为机体机身的四分之一，设定角度Q为90度，所述控制机器人向障碍物侧走弧形路线的具体方法为：控制机器人位于障碍物远侧的行动轮相对近侧的行动轮以四倍的速度行走。
  7. 根据权利要求1所述的基于地图预测的机器人运动控制方法，其特征在于，所述直线L2的初始长度是机体机身的十倍。
  8. 根据权利要求1所述的基于地图预测的机器人运动控制方法，其特征在于，所述每隔设定时间T取机器人走机身长度2倍距离的时间。
  9. 根据权利要求8所述的基于地图预测的机器人运动控制方法，其特征在于，所述持续没有检测到障碍物信号是指两个设定时间T没有检测到障碍物信号。
  10. 根据权利要求1所述的基于地图预测的机器人运动控制方法，其特征在于，所述控制机器人向预测墙面内侧走弧形路线的具体方法为：控制机器人位于预测墙面远侧的行动轮相对近侧的行动轮以四倍的速度行走。
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