Method and device for determining motion parameters of autonomous mobile device

Abstract

The present invention provides a method and device for determining motion parameters of an autonomous mobile device. The method comprises: an anti-fall sensor detects the current ground distance between the chassis of the autonomous mobile device and the current ground, and sends the current ground distance to a processor; the processor determines a correction coefficient corresponding to the current ground distance; the processor obtains the output of an optical flow sensor; the processor determines the motion parameters corresponding to the current ground distance according to the correction coefficient, the calibration coefficient and the output of the optical flow sensor, thereby improving the accuracy of the calculated motion parameters.

Description

[0001] This application is a divisional application of the invention application "Method and device for determining motion parameters of autonomous mobile equipment" with application number 202011628057.8 filed on December 30, 2020. Technical Field

[0002] The present invention relates to the field of robots, and in particular to a method and device for determining motion parameters of an autonomous mobile device. Background Art

[0003] Motion parameters such as velocity and displacement can be used for dead reckoning to achieve positioning of autonomous mobile devices. The above motion parameters are calculated based on the output of the optical flow sensor.

[0004] In the prior art, the optical flow sensor is fixedly mounted on the autonomous mobile device. After obtaining the output of the optical flow sensor, the motion parameters are directly calculated using the corresponding formula based on the output. However, when the autonomous mobile device moves on the ground in the working area, the ground material in the working area may change. For example, it may be on the hard floor one second and move to the soft carpet the next second. The change in the ground material may cause the ground distance between the chassis of the autonomous mobile device and the ground to change, which will cause the motion parameters calculated using the above method to be inaccurate. Summary of the invention

[0005] The present invention provides a method and device for determining motion parameters of an autonomous mobile device, so as to improve the accuracy of the calculated motion parameters.

[0006] In a first aspect, the present invention provides a method for determining motion parameters, which is applied to an autonomous mobile device, the autonomous mobile device comprising an optical flow sensor, an anti-fall sensor, a motion unit and a processor, the method comprising:

[0007] The anti-fall sensor detects a current ground distance between the chassis of the autonomous mobile device and the current ground, and sends the current ground distance to the processor;

[0008] The processor determines a correction coefficient corresponding to the current ground distance; the processor obtains an output of the optical flow sensor; the processor determines a motion parameter corresponding to the current ground distance according to the correction coefficient, the calibration coefficient and the output of the optical flow sensor;

[0009] The calibration coefficient refers to the corresponding relationship between the output of the optical flow sensor and the actual motion parameter when the autonomous mobile device moves at the calibrated ground distance; the correction coefficient is used to correct the calibration coefficient when the current ground distance is different from the calibrated ground distance to obtain the motion parameter corresponding to the current ground distance; the motion parameter includes displacement and / or speed.

[0010] Optionally, the processor determines a correction coefficient corresponding to the current ground distance; and the processor determines a motion parameter corresponding to the current ground distance according to the correction coefficient, the calibration coefficient, and the output of the optical flow sensor, including:

[0011] The processor multiplies the correction coefficient, the output of the optical flow sensor, and the calibration coefficient to obtain a motion parameter corresponding to the current ground distance.

[0012] Optionally, the actual motion parameter is an actual displacement;

[0013] The calibration coefficient is obtained by the following steps:

[0014] Acquire the actual displacement of the autonomous mobile device and the output of the optical flow sensor when the autonomous mobile device moves at the calibrated ground distance; the actual displacement is the displacement actually measured by the length measuring tool;

[0015] The ratio of the actual displacement to the output of the optical flow sensor is used as the calibration coefficient.

[0016] Optionally, the processor determines a correction coefficient corresponding to the current ground distance, including:

[0017] The processor searches or calculates the correction coefficient through a pre-stored mapping relationship, wherein the mapping relationship is a correspondence between a plurality of ground distances to be measured and the correction coefficient.

[0018] Optionally, the mapping relationship is obtained by the following steps:

[0019] For a plurality of ground distances to be measured, obtaining the actual displacement of the optical flow sensor and the output of the optical flow sensor when the optical flow sensor moves at the plurality of ground distances to be measured;

[0020] When the optical flow sensor moves at each of the bottom distances to be measured, the ratio between the actual displacement of the optical flow sensor and the output of the optical flow sensor is used as the corresponding coefficient of the bottom distance to be measured;

[0021] The ratio of the corresponding coefficient of the bottom distance to be measured to the calibration coefficient is used as the correction coefficient corresponding to the bottom distance to be measured, and the mapping relationship is formed by multiple bottom distances to be measured and the corresponding correction coefficients.

[0022] Optionally, before the processor determines the correction coefficient corresponding to the current ground distance, the process further includes:

[0023] The processor determines whether the frequency of change of the ground distance within a preset time period exceeds a preset value;

[0024] If so, perform alarm processing.

[0025] In a second aspect, the present invention provides a method for determining motion parameters of an autonomous mobile device, comprising:

[0026] For a plurality of ground distances to be measured, obtaining actual motion parameters of the optical flow sensor and outputs of the optical flow sensor when the optical flow sensor moves at the plurality of ground distances to be measured;

[0027] When the optical flow sensor moves at each of the bottom distances to be measured, the ratio between the actual motion parameter of the optical flow sensor and the output of the optical flow sensor is used as the corresponding coefficient of the bottom distance to be measured;

[0028] The ratio of the corresponding coefficient of the bottom distance to be measured to the calibration coefficient is used as the correction coefficient corresponding to the bottom distance to be measured.

[0029] Optionally, the actual motion parameter is an actual displacement; when the optical flow sensor is moved at each bottom distance to be measured, the ratio between the actual motion parameter of the optical flow sensor and the output of the optical flow sensor is used as the corresponding coefficient of the bottom distance to be measured, including: when the optical flow sensor is moved at each bottom distance to be measured, the ratio between the actual displacement of the optical flow sensor and the output of the optical flow sensor is used as the corresponding coefficient of the bottom distance to be measured.

[0030] In a third aspect, the present invention provides a method for determining motion parameters of an autonomous mobile device, comprising: the autonomous mobile device comprises an optical flow sensor, an anti-fall sensor, a motion unit and a processor, and the method comprises:

[0031] The anti-fall sensor detects the change in the ground distance between the chassis of the autonomous mobile device and the ground; the anti-fall sensor controls the optical flow sensor to extend and retract up and down according to the change in the ground distance, so that the optical-to-ground distance between the optical flow sensor and the ground is constant;

[0032] The processor obtains the output of the optical flow sensor, and determines the motion parameters of the autonomous mobile device according to the output of the optical flow sensor and a calibration coefficient, wherein the calibration coefficient refers to the corresponding relationship between the output of the optical flow sensor and the actual displacement when the autonomous mobile device moves at a calibrated ground distance; the motion parameters include displacement and / or speed.

[0033] Optionally, the processor determines the motion parameters of the autonomous mobile device according to the output of the optical flow sensor and the calibration coefficient, including:

[0034] The processor multiplies the output of the optical flow sensor and the calibration coefficient to obtain the motion parameter of the autonomous mobile device.

[0035] In a fourth aspect, the present invention provides a method for determining a ground type of an autonomous mobile device, wherein the autonomous mobile device includes an anti-fall sensor, a motion unit, and a processor, and the method includes:

[0036] The anti-fall sensor detects a current ground distance between the chassis of the autonomous mobile device and the current ground, and sends the current ground distance to the processor;

[0037] The processor determines the ground type of the current ground according to the current ground distance.

[0038] Optionally, the method further includes:

[0039] The processor determines an operation mode executed by the autonomous mobile device according to a ground type of the current ground.

[0040] Optionally, the ground type includes at least one hard ground and at least one soft ground; the bottom hard ground distance between the chassis of the autonomous mobile device and the hard ground is greater than the bottom soft ground distance between the chassis of the autonomous mobile device and the soft ground;

[0041] The operation modes include: at least one hard ground mode and at least one soft ground mode;

[0042] The processor determines the operation mode executed by the autonomous mobile device according to the ground type of the current ground, including:

[0043] If the ground type of the current ground is any one of the at least one hard ground, the autonomous mobile device is determined to execute a corresponding hard ground mode; if the ground type of the current ground is any one of the at least one soft ground, the autonomous mobile device is determined to execute a corresponding soft ground mode.

[0044] In a fifth aspect, the present invention provides an autonomous mobile device, comprising: an optical flow sensor, an anti-fall sensor, a motion unit and a processor; the optical flow sensor, the anti-fall sensor and the motion unit are respectively connected to the processor;

[0045] The anti-fall sensor is used to detect the current ground distance between the chassis of the autonomous mobile device and the current ground;

[0046] The processor is used to determine a correction coefficient corresponding to the current ground distance, obtain the output of the optical flow sensor; and determine a motion parameter corresponding to the current ground distance based on the correction coefficient, the calibration coefficient and the output of the optical flow sensor.

[0047] In a sixth aspect, the present invention provides an autonomous mobile device, comprising: an optical flow sensor, an anti-fall sensor, a motion unit and a processor, wherein the optical flow sensor, the anti-fall sensor and the motion unit are respectively connected to the processor, and the optical flow sensor is connected to the anti-fall sensor;

[0048] The anti-fall sensor is used to detect the change in the ground distance between the chassis of the autonomous mobile device and the ground, and according to the change in the ground distance, control the optical flow sensor to extend and retract up and down so that the optical-to-ground distance between the optical flow sensor and the ground is constant;

[0049] The processor is used to obtain the output of the optical flow sensor, and determine the motion parameters of the autonomous mobile device according to the output of the optical flow sensor and a calibration coefficient, wherein the calibration coefficient refers to the corresponding relationship between the output of the optical flow sensor and the actual motion parameters when the autonomous mobile device moves at a calibrated ground distance; the motion parameters include displacement and / or speed.

[0050] In a seventh aspect, the present invention provides an autonomous mobile device, comprising: an anti-fall sensor, a motion unit and a processor; the anti-fall sensor and the motion unit are respectively connected to the processor;

[0051] The anti-fall sensor is used to detect the current ground distance between the chassis of the autonomous mobile device and the current ground;

[0052] The processor is used to determine the ground type of the current ground according to the current ground distance.

[0053] In an eighth aspect, the present invention provides a non-temporary computer-readable storage medium, which, when instructions in the storage medium are executed by a processor of an autonomous mobile device, enables the autonomous mobile device to execute the method of the first aspect, the second aspect, the third aspect or the fourth aspect.

[0054] The method and device for determining motion parameters of an autonomous mobile device provided by the present invention provide two ideas for improving the accuracy of motion parameters. The first idea is to detect the current ground distance between the chassis of the autonomous mobile device and the ground, determine the corresponding correction coefficient according to the current ground distance, and finally calculate the motion parameters by the output of the optical flow sensor, the correction coefficient and the calibration coefficient. The design of the correction coefficient makes the calculated motion parameters closer to the actual motion parameters. The second idea is to detect the change in the ground distance between the chassis of the autonomous mobile device and the ground, and control the optical flow sensor to extend and retract up and down according to the change in the ground distance, so that the optical-to-ground distance between the optical flow sensor and the ground is constant, so that the motion parameters calculated by the output of the optical flow sensor are closer to the actual motion parameters. The method for determining the ground type of an autonomous mobile device provided by the present invention determines the ground type of the current ground according to the ground distance, provides more environmental information for the autonomous mobile device, and enables the autonomous mobile device to realize more functions in combination with the actual operating environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] Figure 1A A schematic structural diagram of an autonomous mobile device 10 provided by the present invention;

[0056] Figure 1B A schematic structural diagram of an autonomous mobile device 10 provided by the present invention;

[0057] Figure 1C A schematic structural diagram of an autonomous mobile device 10 provided by the present invention;

[0058] Figure 1D A schematic structural diagram of an autonomous mobile device 10 provided by the present invention;

[0059] Figure 1E A schematic structural diagram of an autonomous mobile device 10 provided by the present invention;

[0060] Figure 1F A schematic structural diagram of an autonomous mobile device 10 provided by the present invention;

[0061] Figure 1G A schematic diagram of the structure of the optical flow sensor 102 provided by the present invention;

[0062] Figure 2 is a side view of a schematic diagram of an autonomous mobile device 10 on hard ground;

[0063] Figure 3 is a side view of a schematic diagram of an autonomous mobile device 10 on soft ground;

[0064] Figure 4 A schematic diagram of the relationship between the ground distance and the output of the optical flow sensor provided by the present invention;

[0065] Figure 5 A schematic diagram of a flow chart of the first embodiment of the present invention;

[0066] Figure 6 Schematic diagram of the relationship between the ground distance and the correction coefficient provided by the present invention

[0067] Figure 7 A schematic structural diagram of an autonomous mobile device 10 provided by the present invention;

[0068] Figure 8 A schematic diagram of the flow chart of the second embodiment of the present invention;

[0069] Fig.9A A schematic diagram of the process of the third embodiment of the present invention;

[0070] Fig. 9B A schematic diagram of the distance-to-ground correspondence relationship of an embodiment provided by the present invention;

[0071] Fig. 9C A schematic diagram of the distance-to-ground correspondence relationship of an embodiment provided by the present invention.

[0072] Description of reference numerals:

[0073] 10-autonomous mobile device; 101-processor; 102-optical flow sensor; 103-anti-fall sensor; 104-drive unit; 105-IMU; 106-camera; 107-microphone; 108-speaker; 109-storage unit; 110-communication module; 111-motion unit; 112-universal wheel; 113-wheel set; 114-side brush; 115-cleaning unit; 116-distance sensor. DETAILED DESCRIPTION

[0074] In order to make the purpose, technical solutions and advantages of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0075] Figure 1A FIG. 1 is a schematic diagram of the structure of an autonomous mobile device 10 provided in one embodiment of the present invention. Figure 1AAs shown, the autonomous mobile device 10 provided by the present invention includes: a processor 101 and an optical flow sensor 102 connected to the processor 101, an anti-fall sensor 103, a drive unit 104, a motion unit 111 connected to the drive unit 104, and an inertial measurement unit (IMU) 105. In some embodiments, a camera 106, a microphone 107, a speaker 108, a storage unit 109, and a communication module 110 may also be included.

[0076] The functions of each component are described below:

[0077] The anti-drop sensor 103 can be used to detect the ground distance between the chassis of the autonomous mobile device 10 and the ground, and send the ground distance to the processor 101. The ground distance refers to the distance between the chassis of the autonomous mobile device 10 and the ground below it, and the ground distance can be a vertical distance or a distance diagonally downward. The ground distance can also be approximately equal to the distance between the optical flow sensor 102 installed at the bottom of the autonomous mobile device 10 and arranged toward the ground and the ground below it, or can be approximately equal to the distance between the anti-drop sensor 103 installed at the bottom of the autonomous mobile device 10 and arranged toward the ground and the ground below it. The "below" mentioned above can be directly below or diagonally below. The anti-drop sensor 103 of the present invention can be any device or equipment with a distance measurement function, as long as it is installed at the bottom of the autonomous mobile device and arranged toward the ground, and is used to detect the ground distance between the chassis of the autonomous mobile device 10 and the ground, it belongs to the anti-drop sensor 103 of the present invention.

[0078] Common anti-fall sensors include infrared tubes, time of flight (TOF) distance measuring sensors or ultrasonic distance measuring sensors. The basic structure of the anti-fall sensor usually includes at least one transmitting end and at least one receiving end. The transmitting end is used to emit detection light / sound waves. The detection light can be, for example, infrared or laser, and the detection sound wave can be, for example, ultrasonic wave. The detection light / sound wave is irradiated to the ground at a certain distance from the anti-fall sensor 103 and then reflected. The reflected light / sound wave is received by the receiving end, and the ground distance between the chassis of the autonomous mobile device 10 and the ground can be calculated based on the detection light / sound wave and the reflected light / sound wave. The difference between the infrared pair tube and TOF when used as the anti-fall sensor 103 is that the infrared pair tube determines whether there is a sudden bulge or depression on the ground according to whether its receiving end receives the reflected light or the intensity of the reflected light received by its receiving end; if its receiving end does not receive the reflected light or the intensity of the reflected light received is less than a certain light intensity threshold, it means that the ground distance between the chassis of the autonomous mobile device 10 and the ground exceeds the set range. At this time, after the processor 101 receives the ground distance sent by the anti-fall sensor 103, it will determine that there is a sudden bulge or depression on the ground. The protrusion or depression is, for example, a lamp holder or a fan holder, and the depression is, for example, a descending step, thereby notifying the autonomous mobile device 10 to issue an alarm message and / or perform an evasive operation, and the evasive operation may be, for example, deceleration, stopping, and / or turning, etc. For the infrared pair tube, the ground distance can also be obtained by changing the setting angle of the transmitting end and the receiving end, such as changing the setting angle of the transmitting end and / or the receiving end, detecting the reflected light reflected by the ground to be measured at different angles, and then the ground distance can be calculated by analytical geometry according to the angle between the transmitting end and the receiving end when the reflected light is detected. TOF first obtains the time t between the moment when the transmitter sends out the detection light and the moment when the receiver receives the reflected detection light. This time t is called the flight time of the detection light. Then, the ground distance is calculated according to the distance speed time formula l=c×t. If the ground distance measured in a certain period of time is significantly smaller than the ground distance measured in other periods of time, it means that the ground passed by the autonomous mobile device 10 in this period of time has obvious convexity. If the ground distance measured in a certain period of time is significantly larger than the ground distance measured in other periods of time, it means that the ground passed by the autonomous mobile device 10 in this period of time has obvious concaveness. At this time, after the processor 101 receives the ground distance sent by the anti-fall sensor 103, it will determine that there is a sudden convexity or concave on the ground at this time, and then notify the autonomous mobile device 10 to issue an alarm message and / or perform an evasive operation. The distance measurement principle of the ultrasonic rangefinder is similar to that of TOF, except that the speed is not the speed of light c but the speed of sound v. The ground distance is still calculated using the distance speed time formula l=v×t.

[0079] The processor 101 can be used to receive the ground distance sent by the anti-fall sensor 103, and determine whether the ground distance reaches the fall warning value. If it reaches the warning value, it is considered that the autonomous mobile device 10 is at risk of falling, such as on a recessed step, or there is a risk of the wheels being suspended in the air due to being lifted, such as on a raised lamp holder. At this time, the route of the autonomous mobile device 10 can be changed in time to prevent the autonomous mobile device 10 from falling and being damaged or being suspended in the air and unable to escape.

[0080] The autonomous mobile device 10 may include multiple processors 101. The processor 101 of the autonomous mobile device 10 may be located on the autonomous mobile device 10, or on a server, a cloud, or a mobile terminal (such as a mobile phone, a computer, etc.); if there are multiple processors 101, the multiple processors 101 may be multi-core integrated or constructed in a distributed storage device manner. Figure 1A FIG. 1 is a schematic diagram of an autonomous mobile device 10 including a processor 101 .

[0081] The driving unit 104 can be used to drive the motion unit 111 to operate under the control of the processor 101. The operation of the motion unit 111 can drive the autonomous mobile device 10 to move. In some embodiments, the motion unit 111 may include a universal wheel arranged at the front of the bottom of the autonomous mobile device 10 and driving wheels symmetrically arranged on both sides of the central axis of the bottom of the autonomous mobile device 10. The driving wheel is also called a wheel set, wherein the wheel set is used to control the moving direction of the autonomous mobile device 10 and drive the autonomous mobile device 10 to move. The universal wheel is a follower wheel and together with the wheel set constitutes a stable structure supported by three points. This embodiment does not limit the form and setting position of the motion unit. For example, the motion unit may also adopt multiple wheels with a layout different from that of the above-mentioned embodiment, and / or include a crawler motion mechanism or a bipedal / multi-legged walking mechanism symmetrically arranged at the bottom of the autonomous mobile device 10.

[0082] The optical flow sensor 102 is installed at the bottom of the autonomous mobile device 10 and is arranged toward the ground. The optical flow sensor 102 includes at least one image sensor, such as an optical camera. The image sensor of the optical flow sensor 102 is arranged on the chassis of the autonomous mobile device 10 and at least partially arranged toward the ground, and is used to obtain an image with image texture on the ground. The image texture includes patterns, lines, lines, etc. on the ground that can be recognized by the image sensor; the image texture provides spatial arrangement information of color or intensity in the image or in a selected area of ​​the image. The image sensor of the optical flow sensor 102 captures images of the ground at a certain frequency, and the moving speed of the autonomous mobile device 10 relative to the ground is obtained by comparing the position changes of the image texture in adjacent frame images. Since the frequency of the image sensor acquiring images is usually fixed or can be set to be fixed, the output of the optical flow sensor 102 is proportional to the measured speed of the autonomous mobile device 10; the integration of the measured speed can obtain the measured displacement, so the output of the optical flow sensor 102 is also generally proportional to the measured displacement of the autonomous mobile device 10. Therefore, in the present invention, the displacement, speed and other motion parameters of the autonomous mobile device 10 are obtained at least partially based on the output of the optical flow sensor 102. In some embodiments, the optical flow sensor 102 may further include at least one light source for providing sufficient and stable illumination for the ground so that its image sensor can obtain clear and stable images.

[0083] In some other embodiments, the motion unit is also provided with an odometer for measuring the displacement of the autonomous mobile device 10. In this case, the optical flow sensor 102 and the odometer can be used simultaneously to measure the displacement of the autonomous mobile device 10. The displacement obtained by the output of the optical flow sensor 102 and the displacement measured by the odometer can be optimized to make the displacement of the autonomous mobile device 10 more accurate. The IMU 105 includes a gyroscope and an accelerometer, wherein the gyroscope is used to measure the angular velocity and angular acceleration of the autonomous mobile device 10, and the angle of the autonomous mobile device 10 can be obtained by integrating the angular velocity; the accelerometer is used to measure the acceleration of the autonomous mobile device 10, and the speed can be obtained by integrating the acceleration. The various motion parameters measured or calculated by the optical flow sensor 102, the odometer, and the IMU, such as displacement, speed, etc., can be used for mapping and positioning and navigating the autonomous mobile device 10.

[0084] In some embodiments, the camera 106 may be used to collect images around the autonomous mobile device 10, which may be used for positioning navigation and / or object recognition. The microphone 107 and the speaker 108 may be used for voice interaction with the user.

[0085] The storage unit 109 may be used to store data sent by the processor 101 and each sensor. The communication module 110 may be used to perform data exchange with a terminal and / or a server.

[0086] In one possible implementation, Figure 1A The autonomous mobile device 10 in the embodiment can be designed as Figures 1B to 1E Mopping machines and Figure 1F of sweeping machines; Figure 1B , Figure 1C , Figure 1E Bottom view of the mopping machine. Figure 1D for Figure 1C Side view of the mopping machine. Figure 1F This is a bottom view of the sweeper. Figure 1C , Figure 1D and Figure 1E As shown, the optical flow sensor 102 and the anti-fall sensor 103 are both arranged at the bottom of the autonomous mobile device 10 and facing the ground, and are both electrically connected to the processor 101 (not shown in the figure). The anti-fall sensor 103 can be arranged in front of the optical flow sensor 102 along the running direction of the autonomous mobile device 10 (the direction of the arrow in the figure). The universal wheel 112 in the motion unit 111 can be arranged in front of the bottom of the autonomous mobile device 10, and the wheel group 113 in the motion unit 111 can be arranged on both sides of the central axis of the bottom of the autonomous mobile device 10, so that the universal wheel 112 and the wheel group 113 form a three-point supported balance structure, so that the autonomous mobile device can maintain balance and stability at all times during operation. When the autonomous mobile device 10 is a cleaning robot, a side brush 114 and a cleaning unit 115 can also be arranged at its bottom. When the autonomous mobile device 10 is a mopping machine, the cleaning unit 115 can be a mop, or a mop plus a main brush. When the autonomous mobile device 10 is a sweeping machine, the cleaning unit 115 is generally a main brush. The side brush 114 is an optional component, which can be present or absent. It should be noted that: in Figure 1B-Figure 1E In the embodiment, the setting positions of the optical flow sensor 102 and the anti-fall sensor 103 are only examples, and they may also be set at other suitable positions at the bottom of the autonomous mobile device 10, which is not limited in the present invention.

[0087] For example, the optical flow sensor 102 may be Figure 1G The single-mode optical flow sensor shown may also be other existing commercially available optical flow sensors, such as the infrared / LED dual-light source optical flow sensor of the PAA5101EW-M type produced by PixArt.

[0088] Figure 2 It is a side view of the autonomous mobile device 10 on hard ground. Figure 3 FIG. 1 is a side view of the autonomous mobile device 10 on soft ground. Figure 2 As shown, when the autonomous mobile device 10 moves on a hard ground, the ground distance between the chassis of the autonomous mobile device 10 and the ground is A mm, and the hard ground can be, for example, a wooden floor or a marble floor tile. Figure 3As shown, the autonomous mobile device 10 may also move on a soft ground, which may be a carpet, for example. When the autonomous mobile device 10 moves on the carpet, the carpet at the position of the moving unit of the autonomous mobile device 10 sinks due to the softness of the carpet, such as the carpet at the wheel set, while the ground portion corresponding to the chassis of the autonomous mobile device 10 (including the portion where the anti-fall sensor 103 and the portion where the optical flow sensor 102 are installed) mostly does not sink, so that the ground distance between the chassis of the autonomous mobile device 10 and the ground is reduced to B mm, as shown in FIG. Figure 3 As shown. At this time, the ground distance change caused by the sinking of the soft ground at the wheel group will be detected by the anti-fall sensor, but the ground distance change is relatively small, usually only a few millimeters, usually not more than 3 centimeters, and the ground distance change corresponding to the processor 101 sending an alarm message and / or executing an evasive operation command to the autonomous mobile device 10 is at least greater than 5 centimeters. Therefore, the ground distance change caused by the sinking of the soft ground is usually not enough to cause the processor 101 to send an alarm message and / or execute an evasive operation command to the autonomous mobile device 10.

[0089] In actual applications, it is found that when the distance between the optical flow sensor 102 installed at the bottom of the autonomous mobile device 10 and the ground changes, even if the autonomous mobile device 10 runs at a constant speed, the output of the optical flow sensor 102 will also change, such as Figure 4 As shown, for example, when the autonomous mobile device 10 is running on a hard floor of a wooden floor, the ground distance is 70 mm, and the output of the optical flow sensor 102 when running at a certain speed is 1650. When the autonomous mobile device 10 is running on a soft floor of a long-haired carpet, the ground distance is 50 mm, and the output of the optical flow sensor 102 when running at the same speed is 2600.

[0090] Assuming that calibration or calibration is performed on a soft ground, that is, when the ground distance is 50 mm, the output of the optical flow sensor 102 is proportional to the actual motion parameters of the autonomous mobile device 10, then when the autonomous mobile device 10 moves to a hard ground with a ground distance of 70 mm, the error will be as high as 40%.

[0091] Assuming that calibration or calibration is performed on a hard ground, that is, when the ground distance is 70 mm, the output of the optical flow sensor 102 is proportional to the actual motion parameters of the autonomous mobile device 10, then when the autonomous mobile device 10 moves to a soft ground with a ground distance of 50 mm, the error will be as high as 60%.

[0092] The actual motion parameter may be an actual speed or an actual displacement.

[0093] It can be seen that the autonomous mobile device 10 running on different ground materials will cause a large error between the measured speed / measured displacement calculated from the output of the optical flow sensor 102 and the actual speed / actual displacement of the autonomous mobile device 10, resulting in inaccurate speed / displacement of the autonomous mobile device 10 measured using the optical flow sensor 102. At present, companies in the industry have not paid attention to this problem, nor have they proposed a feasible solution to this problem.

[0094] In order to solve the above-mentioned problem of large measurement speed / measurement displacement errors of the autonomous mobile device 10 when running at different ground distances, the present invention provides two ideas. The first idea: detect the current ground distance between the chassis of the autonomous mobile device 10 and the ground, determine the corresponding correction coefficient based on the current ground distance, and finally calculate the motion parameters from the output of the optical flow sensor 102, the correction coefficient and the calibration coefficient. The correction coefficient is designed so that the calculated motion parameters are closer to the actual motion parameters. The second idea: detect the change in the ground distance between the chassis of the autonomous mobile device 10 and the ground, and control the optical flow sensor 102 to extend and retract up and down according to the change in the ground distance, so that the optical-to-ground distance between the optical flow sensor 102 and the ground is constant, so that the motion parameters calculated from the output of the optical flow sensor 102 are closer to the actual motion parameters.

[0095] Regarding the first approach, Figure 5 This is a flow chart of the first embodiment of the present invention. Figure 5 As shown, the motion parameter determination method provided by the present invention includes:

[0096] S501 : The anti-fall sensor 103 detects the current ground distance between the chassis of the autonomous mobile device 10 and the current ground.

[0097] Specifically, an infrared tube or TOF can be used to detect the current ground distance between the chassis of the autonomous mobile device 10 and the ground. The detection principle of the infrared tube or TOF is described in the above functional description of the anti-fall sensor 103, and the present invention will not be repeated here.

[0098] S502: The processor 101 determines a correction coefficient corresponding to the current ground distance.

[0099] The following introduces the meaning and acquisition method of the calibration coefficient, as well as the meaning and acquisition method of the correction coefficient.

[0100] First, let’s introduce the meaning and acquisition method of the calibration coefficient:

[0101] The calibration coefficient refers to the corresponding relationship between the output of the optical flow sensor 102 and the actual motion parameter when the autonomous mobile device 10 moves at a calibrated ground distance.

[0102] The above-mentioned actual motion parameter can be an actual displacement, and the calibration coefficient can be obtained by the following method:

[0103] When the autonomous mobile device 10 moves at a calibrated ground distance, the actual displacement of the autonomous mobile device 10 and the output of the optical flow sensor 102 are obtained, and the ratio of the actual displacement to the output of the optical flow sensor 102 is used as the calibration coefficient.

[0104] It should be noted that the above-mentioned actual displacement is the displacement actually measured by the length measuring tool, and the length measuring tool can be, for example, a ruler or a rangefinder, such as a laser radar, an ultrasonic rangefinder, etc. Of course, the corresponding relationship between the output of the optical flow sensor 102 and the actual speed when the autonomous mobile device 10 moves at a calibrated ground distance can also be defined as a calibration coefficient: at this time, the actual speed is obtained by a code disk (or encoder); or the actual speed is obtained by integrating the acceleration measured by the accelerometer; or the actual displacement is measured by a ruler or a rangefinder and the time for the autonomous mobile device to move the actual displacement is recorded, and then the actual speed is calculated based on the actual displacement and the time consumed to run the actual displacement; then the ratio of the output of the optical flow sensor of the actual displacement to the running time is calculated, and the corresponding relationship between it and the above-mentioned actual speed is the calibration coefficient in this case. The present invention does not limit the method of obtaining the actual displacement or the actual speed.

[0105] For the sake of clarity and convenience, the actual displacement is used as the actual motion parameter for illustration below, that is, the calibration coefficient is defined as the corresponding relationship between the output of the optical flow sensor 102 and the actual displacement when the autonomous mobile device 10 moves at a calibrated ground distance.

[0106] Before the autonomous mobile device 10 leaves the factory, it is often necessary to calibrate its optical flow sensor 102 so that the output of the optical flow sensor 102 can reflect the displacement of the autonomous mobile device under normal use scenarios. The following is an example of how to obtain the calibration coefficient:

[0107] Assume that after the autonomous mobile device 10 is assembled, it is placed on a common ground before leaving the factory. At this time, the distance between its chassis and the common ground, that is, the calibrated ground distance is 70 mm, or the autonomous mobile device 10 is placed on a common ground before leaving the factory, and the distance between the chassis of the autonomous mobile device 10 and the ground is calibrated to 70 mm; then the autonomous mobile device 10 is started, and the autonomous mobile device 10 moves in a scene with a ground distance of 70 mm, and a measuring tool such as a ruler is used to measure the actual displacement of the autonomous mobile device 10, and the ratio of the actual displacement measured by the ruler to the output of the autonomous mobile device 10 is used as the calibration coefficient. For example: when the actual displacement of the autonomous mobile device 10 measured by the ruler is 16500 mm, and the output of the optical flow sensor of the autonomous mobile device 10 is 1650 mm, then the calibration coefficient = 16500 mm / 1650 mm = 10.

[0108] It should be noted that: if the autonomous mobile device 10 is mostly run on a hard ground in actual applications, that is, the commonly used ground is a hard ground, when calibrating its optical flow sensor 102, it can be placed on a hard ground for calibration, such as a wooden floor or a tiled floor; if the autonomous mobile device 10 is mostly run on a soft ground in actual applications, that is, the commonly used ground is a soft ground, when calibrating its optical flow sensor 102, it can be placed on a soft ground for calibration, such as a carpet.

[0109] The above is the meaning and acquisition method of the calibration coefficient.

[0110] The following describes the meaning and acquisition method of the correction coefficient:

[0111] The correction coefficient is used to correct the calibration coefficient when the current ground distance is different from the calibrated ground distance, so as to obtain the motion parameter corresponding to the current ground distance.

[0112] The correction factor can be obtained as follows:

[0113] The processor 101 obtains the correction coefficient by searching or calculating the pre-stored mapping relationship, where the mapping relationship is a correspondence between a plurality of ground distances to be measured and the correction coefficient.

[0114] The following describes how to obtain the mapping relationship:

[0115] For multiple ground distances to be measured, the actual displacement of the optical flow sensor 102 and the output of the optical flow sensor 102 are obtained when the optical flow sensor 102 moves at the multiple ground distances to be measured; the ratio between the actual displacement of the optical flow sensor 102 and the output of the optical flow sensor 102 when the optical flow sensor 102 moves at each ground distance to be measured is used as the corresponding coefficient of the ground distance to be measured; the correction coefficient corresponding to the ground distance to be measured is determined by the ratio of the corresponding coefficient of the ground distance to be measured and the calibration coefficient. The ground distance to be measured refers to the distance between the optical flow sensor 102 and the ground to be measured, or the distance between the chassis of the autonomous mobile device 10 equipped with the optical flow sensor 102 and the ground to be measured. When the optical flow sensor 102 is installed at the bottom of the autonomous mobile device 10, there is a fixed distance difference between its lens and the chassis of the autonomous mobile device 10. For example, when the optical flow sensor 102 is installed at the bottom of the autonomous mobile device 10 and is recessed upward from the chassis by about 3 cm, the distance between the optical flow sensor 102 and the ground to be measured (calculated as the distance between the lens of the optical flow sensor 102 and the ground to be measured) is longer than the distance between the chassis of the autonomous mobile device 10 and the ground to be measured by a fixed distance difference of about 3 cm. Therefore, the above two definitions of "ground distance to be measured" differ by the fixed distance difference, but this does not hinder the understanding and implementation of the present invention. Those skilled in the art should understand that the distance between the optical flow sensor 102 and the ground to be measured and the distance between the autonomous mobile device 10 and the ground to be measured are easily converted. For the convenience of description, unless otherwise specified, the present invention uses the distance between the chassis of the autonomous mobile device 10 and the ground to be measured as the definition of the ground distance to be measured.

[0116] Here are some examples:

[0117] Assume that the calibrated ground distance is 70mm, the calibration coefficient obtained by the above method is 10, and the ground distance to be measured is 50mm. The distance between the optical flow sensor 102 and the ground is adjusted to 50mm, so that the autonomous mobile device 10 moves in a scene with a ground distance of 50mm. At this time, a ruler is used to measure the actual displacement of the autonomous mobile device 10, and the ratio of the actual displacement measured by the ruler and the output of the optical flow sensor 102 is used as the corresponding coefficient of 50mm. For example: when the actual displacement measured by the ruler is 16500mm, the output of the autonomous mobile device 10 is 2600mm, then the corresponding coefficient when the ground distance to be measured is 50mm = 16500mm / 2600mm≈6.346. The ratio of the corresponding coefficient when the ground distance to be measured is 50mm and the calibration coefficient, 6.346 / 10=0.6346, can be used as the correction coefficient corresponding to the ground distance to be measured of 50mm. For all ground distances to be measured, the above calculation is performed, and the correction coefficients corresponding to all ground distances to be measured can be obtained. The functional relationship or corresponding curve between each measured bottom ground distance and its corresponding correction coefficient, that is, the mapping relationship.

[0118] Of course, the reciprocal of the ratio 6.346 / 10 in the above example, 10 / 6.346≈1.577, is also the ratio between the actual displacement of the optical flow sensor 102 and the output of the optical flow sensor 102, and therefore can also be used as a correction coefficient corresponding to the ground distance. However, at this time, the functional relationship of the motion parameter measured by the correction coefficient, the calibration coefficient, and the output of the optical flow sensor needs to be adjusted accordingly, such as multiplying the calibration coefficient by the output of the optical flow sensor by the correction coefficient to obtain a measured displacement close to the actual displacement. Those skilled in the art can understand and implement the above adjustment without creative work under the enlightenment of the above embodiments.

[0119] In one possible implementation, if Figure 6 The mapping relationship of the curve shown in FIG. 1 can be obtained from the processor 101 after receiving the current ground distance sent by the anti-fall sensor. Figure 6 For example, the calibration coefficient corresponding to the current ground distance of the autonomous mobile device 10 is 70 mm, and the calibration coefficient is 10. When the autonomous mobile device 10 is running on a certain ground, the anti-fall sensor detects that the current ground distance is 50 mm, and feeds back the ground distance 50 mm to the processor. The processor calculates the calibration coefficient according to the current ground distance. Figure 6 The correction coefficient of the ordinate corresponding to the measured ground distance = 50mm, which is the same as the current ground distance, is found from the horizontal coordinate in the mapping relationship. It is 0.6346. Multiply it by the calibration coefficient 10 and the output of the optical flow sensor to obtain the measured displacement value of 16499.6mm at the current ground distance of 50mm. This measured displacement value is very close to the actual displacement of 16500mm.

[0120] In another possible implementation, the mapping relationship obtained by the above method may be a formula. For example, the formula may be Formula 1:

[0121] y=0.0013·x2-0.1364·x+4.2201 (Formula 1)

[0122] Where y represents the correction coefficient and x represents the ground distance.

[0123] After receiving the current ground distance sent by the anti-fall sensor, the processor 101 substitutes the current ground distance as x into Formula 1 to obtain a correction coefficient y corresponding to the current ground distance.

[0124] It should be noted that Formula 1 can be a theoretically derived formula or a formula based on Figure 6 For example, if x=50 is substituted into the above fitting formula 1, y=0.65 is obtained, which is consistent with the curve fitting formula Figure 6The resulting correction factor of 6.346 is very close.

[0125] S503 : The processor 101 obtains the output of the optical flow sensor 102 .

[0126] The optical flow sensor 102 may periodically report the output to the processor 101, or report the output to the processor 101 in real time, or the processor 101 may send a reporting instruction to the optical flow sensor 102, and after receiving the reporting instruction, the optical flow sensor 102 reports the output to the processor 101. The present invention is not limited to this.

[0127] S504, the processor 101 determines the motion parameter corresponding to the current ground distance according to the correction coefficient, the calibration coefficient and the output of the optical flow sensor 102. The motion parameter corresponding to the current ground distance is close to the actual measured motion parameter, which is very close to the actual measured motion parameter and can be used to replace the actual measured motion parameter for calculation so that the autonomous mobile device can be more accurately positioned and mapped.

[0128] The processor 101 may multiply the correction coefficient, the output of the optical flow sensor, and the calibration coefficient to obtain a motion parameter corresponding to the current ground distance.

[0129] In one possible implementation, the processor 101 may multiply the correction coefficient and the calibration coefficient to obtain a corresponding coefficient of the current ground distance, and then multiply the corresponding coefficient of the current ground distance and the output of the optical flow sensor 102 to obtain a motion parameter corresponding to the current ground distance.

[0130] In another possible implementation, the processor 101 may multiply the calibration coefficient and the output of the optical flow sensor 102 to obtain an initial motion parameter, and then multiply the correction coefficient and the initial motion parameter to obtain a motion parameter corresponding to the current ground distance.

[0131] In order to prevent the above calculation from being repeated when the autonomous mobile device 10 operates abnormally, resulting in waste of computing resources and errors in measuring displacement, the motion parameter determination method provided in this embodiment further includes:

[0132] The processor 101 determines whether the frequency of change of the ground distance within a preset time period exceeds a preset value; if so, an alarm process is executed, or S501-S504 are not executed.

[0133] The motion parameter determination method provided in this embodiment detects the current ground distance between the chassis of the autonomous mobile device and the ground, determines the corresponding correction coefficient according to the current ground distance, and finally calculates the motion parameters by the output of the optical flow sensor, the correction coefficient and the calibration coefficient. The design of the correction coefficient makes the calculated motion parameters closer to the actual motion parameters, and can more accurately feedback the motion data of the autonomous mobile device.

[0134] For the second approach, we provide Figure 7 The architecture shown, Figure 7 The difference from FIG. 1 is that in the figure, the optical flow sensor 102 and the anti-fall sensor 103 are connected. Figure 8 This is a flow chart of the second embodiment of the present invention. Figure 8 As shown, the motion parameter determination method provided by the present invention includes:

[0135] S801 : The anti-fall sensor 103 detects a change in the distance between the chassis of the autonomous mobile device 10 and the ground.

[0136] Specifically, after the anti-fall sensor detects the current ground distance between the chassis of the autonomous mobile device 10 and the ground, the current ground distance is compared with the ground distance detected last time to obtain the change in the ground distance. For example, the ground distance detected last time was 70 mm, and the ground distance currently detected is 50 mm. If a decrease is negative and an increase is positive, then the ground distance at this time decreases from 70 mm to 50 mm, so the change in the ground distance is -20 mm.

[0137] S802, the anti-fall sensor 103 controls the optical flow sensor 102 to extend and retract up and down according to the change in the distance from the ground, so that the optical distance between the optical flow sensor 102 and the ground is constant.

[0138] The above-mentioned constant is a basically constant concept. Taking into account the measurement error, it can be considered constant within the range of ±5mm of the starting light-to-ground distance. The starting light-to-ground distance is defined as: the distance between the optical flow sensor 102 and the ground when the optical flow sensor 102 is not telescopically moved and the ground distance is the calibrated ground distance.

[0139] Specifically, if the current ground distance is larger than the ground distance detected last time, the anti-fall sensor may send an extension instruction to the optical flow sensor 102, and the extension instruction may carry the above-mentioned change amount. After receiving the extension instruction, the optical flow sensor 102 extends a specific distance, and the specific distance is the same as the above-mentioned change amount. If the current ground distance is smaller than the ground distance detected last time, the anti-fall sensor may send a shortening instruction to the optical flow sensor 102, and the shortening instruction may carry the above-mentioned change amount. After receiving the shortening instruction, the optical flow sensor 102 shortens a specific distance, and the specific distance is the same as the above-mentioned change amount.

[0140] In one possible implementation, a distance sensor for detecting the distance between the optical flow sensor 102 and the ground can be set next to the optical flow sensor 102, and can be extended and retracted synchronously with the optical flow sensor 102. When the optical flow sensor 102 completes the above-mentioned extension or shortening operation, the distance sensor can detect whether the light-to-ground distance between the optical flow sensor 102 and the ground remains constant, and feeds back the detection result to the optical flow sensor 102, the anti-fall sensor 102 or the processor 101, which controls the optical flow sensor 102 to adjust the extension and retraction distance so that the light-to-ground distance is the same as the previously calibrated bottom-to-ground distance or is within the error range (for example, ±5mm).

[0141] S803 : The processor 101 obtains the output of the optical flow sensor 102 .

[0142] Similar to the above-mentioned related embodiments, the optical flow sensor 102 may periodically report the output to the processor 101, or report the output to the processor 101 in real time, or the processor 101 may send a reporting instruction to the optical flow sensor 102, and after receiving the reporting instruction, the optical flow sensor 102 reports the output to the processor 101. The present invention is not limited to this.

[0143] S804 : The processor 101 determines the motion parameters of the autonomous mobile device 10 according to the output of the optical flow sensor 102 and the calibration coefficient.

[0144] Specifically, since the optical-to-ground distance between the optical flow sensor 102 and the ground is constant, the output of the optical flow sensor 102 is accurate, and the processor 101 can directly multiply the output of the optical flow sensor 102 by the calibration coefficient to obtain the motion parameters of the autonomous mobile device 10 .

[0145] The motion parameter determination method provided in this embodiment detects the change in the ground distance between the chassis of the autonomous mobile device and the ground, and then controls the optical flow sensor to extend and retract up and down according to the change in the ground distance, so that the optical-to-ground distance between the optical flow sensor and the ground is constant. Since the optical-to-ground distance between the optical flow sensor and the ground is constant, the output of the optical flow sensor is calibrated, and the measured displacement calculated by the calibration coefficient is consistent with the actual displacement, so the measured displacement obtained is accurate, so that the motion parameters calculated by the output of the optical flow sensor are closer to the actual motion parameters.

[0146] An embodiment of the present invention further provides a method for determining a ground type of an autonomous mobile device. The method involves an autonomous mobile device including an anti-fall sensor, a motion unit, and a processor.

[0147] The ground type is determined by Fig.9A As shown, specifically including:

[0148] S901: The anti-fall sensor 103 detects the current ground distance between the chassis of the autonomous mobile device 10 and the current ground, and sends the current ground distance to the processor.

[0149] This step S901 is similar to step S501 in the above embodiment and will not be described again here.

[0150] S902: The processor 101 determines the ground type of the current ground according to the current ground distance.

[0151] The above-mentioned ground types can be specific ground types, such as floors, tiles, carpets, etc., or types classified by ground hardness, such as hard floors, soft floors, etc., wherein hard floors include floors made of non-compressible materials such as wooden floors, tiles, marble, etc., and soft floors include floors made of compressible materials such as carpets and floor mats, such as long-haired carpets, short-haired carpets, yoga mats, plastic mats, etc. In some embodiments, the ground types include at least one hard ground and at least one soft ground; the bottom hard ground distance between the chassis of the autonomous mobile device and the hard ground is greater than the bottom soft ground distance between the chassis of the autonomous mobile device and the soft ground. Of course, there can also be multiple hard floors and / or multiple soft floors, multiple hard floors, for example, corresponding to wooden floors, tiles, etc., respectively, and multiple soft floors, for example, corresponding to floor mats, short-haired carpets, long-haired carpets, etc., respectively. According to the different hardness of the ground type, a distance-to-ground correspondence relationship between the bottom ground distance and the ground type can be established, such as Fig. 9B and Fig. 9C The corresponding relationship between the ground distance and the ground types obtained by different classification methods is shown respectively. For example, Fig. 9BIn the example, the ground type corresponding to the distance from the bottom to the ground is 65 to 70 mm, which is a hard ground, and the ground type corresponding to the distance from the bottom to the ground is 48 to 68 mm, which is a soft ground. Fig. 9C In the figure, the ground type corresponding to the distance between the bottom and the ground of 68 to 69 mm is wooden floor, the ground type corresponding to the distance between the bottom and the ground of 70 to 71 mm is tile floor, the ground type corresponding to the distance between the bottom and the ground of 47 to 53 mm is long-haired carpet (according to the length of the hair, it can be further subdivided into different types of long-haired carpet; but they can also be classified into one category, collectively referred to as long-haired carpet), the ground type corresponding to the distance between the bottom and the ground of 54 to 60 mm is short-haired carpet (according to the length of the hair, it can be further subdivided into different types of short-haired carpet; but they can also be classified into one category, collectively referred to as short-haired carpet), and the ground type corresponding to the distance between the bottom and the ground of 61 to 67 mm is floor mat (according to the material and purpose of the floor mat, it can be further subdivided into different types, such as plastic mat, yoga mat, soft mat, etc.; but they can also be classified into one category, collectively referred to as floor mat). According to the distance-ground correspondence, the ground type of the current ground can be determined according to the current ground distance detected by the anti-fall sensor. Fig. 9B , 9C The middle dotted line is the alignment line, for clarification.

[0152] S903: The processor determines an operation mode to be executed by the autonomous mobile device according to the ground type of the current ground.

[0153] When the processor obtains the ground type of the current ground, it can be used for many purposes, such as marking the ground type in the established map, or determining the operating mode executed by the autonomous mobile device according to the ground type of the current ground. It is easy to understand that different ground types may have different resistance and power consumption for the operation of autonomous mobile devices. For example, hard surfaces have small resistance to autonomous mobile devices and low power consumption, while soft surfaces such as carpets have relatively large resistance to autonomous mobile devices and high power consumption; in addition, for the case where the autonomous mobile device is a cleaning robot, it can implement both the sweeping mode and the wet mopping mode when running on hard surfaces such as wooden floors and tiles, but for soft surfaces such as carpets and floor mats, it is only suitable for the sweeping mode and not for the wet mopping mode. Therefore, if the obtained ground type is marked at the corresponding position in the map, the user and the autonomous mobile device can know the ground conditions of each area in the map, so as to more accurately predict the power consumption, operating mode and other information of each area in the map, making the autonomous mobile device smarter and giving users more choices. The processor of the autonomous mobile device can also determine that the autonomous mobile device executes different operating modes according to the ground type of the current ground, such as Fig.9A As shown in step S903.

[0154] Exemplarily, the operating mode may include: at least one hard ground mode and at least one soft ground mode; as mentioned above, it may also include multiple hard ground modes and / or multiple soft ground modes, which will not be described in detail here. In addition, the operating mode can be divided into different modes according to different uses. If classified by cleaning method, the hard ground mode may correspond to the above-mentioned sweeping mode and / or wet mopping mode, and the soft ground mode may correspond to the above-mentioned sweeping mode. Of course, based on the above-mentioned embodiment of the present invention, the ground type of the current ground can be determined according to the current bottom ground distance detected by the anti-fall sensor, so as to determine whether to execute the hard ground mode or the soft ground mode. At this time, the hard ground mode and the soft ground mode correspond to different correction coefficients, and then the motion parameters of the autonomous mobile device are determined according to the correction coefficient determined by the operating mode, combined with the calibration coefficient and the output of the optical flow sensor. The above-mentioned embodiment has been described in detail and will not be described in detail here.

[0155] Exemplarily, the above-mentioned step 903 specifically means that if the ground type of the current ground is any one of at least one hard ground, then the autonomous mobile device is determined to execute a corresponding hard ground mode; if the ground type of the current ground is any one of at least one soft ground, then the autonomous mobile device is determined to execute a corresponding soft ground mode.

[0156] It should be understood that the processor described in the present invention may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), etc. A general-purpose processor may be a microprocessor or any conventional processor. The steps of the method disclosed in the present invention may be directly implemented as being executed by a hardware processor, or may be implemented by a combination of hardware and software modules in the processor.

[0157] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for determining motion parameters of an autonomous mobile device, characterized in that: The autonomous mobile device comprises an optical flow sensor, an anti-fall sensor, a motion unit and a processor, and is characterized in that the method comprises: The anti-fall sensor detects the change in the ground distance between the chassis of the autonomous mobile device and the ground; the anti-fall sensor controls the optical flow sensor to extend and retract up and down according to the change in the ground distance, so that the optical-to-ground distance between the optical flow sensor and the ground is constant; The processor obtains the output of the optical flow sensor, and determines the motion parameters of the autonomous mobile device according to the output of the optical flow sensor and a calibration coefficient, wherein the calibration coefficient refers to the corresponding relationship between the output of the optical flow sensor and the actual motion parameters when the autonomous mobile device moves at a calibrated ground distance; the motion parameters include displacement and / or speed.

2. The method according to claim 1, characterized in that The processor determines the motion parameters of the autonomous mobile device according to the output of the optical flow sensor and the calibration coefficient, including: The processor multiplies the output of the optical flow sensor and the calibration coefficient to obtain the motion parameter of the autonomous mobile device.

3. The method according to claim 1, characterized in that The method further comprises: The anti-fall sensor detects a current ground distance between the chassis of the autonomous mobile device and the current ground, and sends the current ground distance to the processor; The processor determines the ground type of the current ground according to the current ground distance; The processor determines an operation mode executed by the autonomous mobile device according to a ground type of the current ground.

4. The method according to claim 3, characterized in that: The ground type includes at least one hard ground and at least one soft ground; the bottom hard ground distance between the chassis of the autonomous mobile device and the hard ground is greater than the bottom soft ground distance between the chassis of the autonomous mobile device and the soft ground; The operation modes include: at least one hard ground mode and at least one soft ground mode; The processor determines the operation mode executed by the autonomous mobile device according to the ground type of the current ground, including: If the ground type of the current ground is any one of the at least one hard ground, the autonomous mobile device is determined to execute a corresponding hard ground mode; if the ground type of the current ground is any one of the at least one soft ground, the autonomous mobile device is determined to execute a corresponding soft ground mode.

5. An autonomous mobile device, characterized in that: include: An optical flow sensor, an anti-fall sensor, a motion unit and a processor, wherein the optical flow sensor, the anti-fall sensor and the motion unit are respectively connected to the processor, and the optical flow sensor is connected to the anti-fall sensor; The anti-fall sensor is used to detect the change in the ground distance between the chassis of the autonomous mobile device and the ground, and according to the change in the ground distance, control the optical flow sensor to extend and retract up and down so that the optical-to-ground distance between the optical flow sensor and the ground is constant; The processor is used to obtain the output of the optical flow sensor, and determine the motion parameters of the autonomous mobile device according to the output of the optical flow sensor and a calibration coefficient, wherein the calibration coefficient refers to the corresponding relationship between the output of the optical flow sensor and the actual motion parameters when the autonomous mobile device moves at a calibrated ground distance; the motion parameters include displacement and / or speed.

6. The device according to claim 5, characterized in that The anti-fall sensor is also used to detect the current ground distance between the chassis of the autonomous mobile device and the current ground; The processor is used to determine the ground type of the current ground according to the current ground distance, and determine the operation mode executed by the autonomous mobile device according to the ground type of the current ground.

7. A non-transitory computer-readable storage medium, when instructions in the storage medium are executed by a processor of an autonomous mobile device, enables the autonomous mobile device to perform the method of any one of claims 1-4.

Images