CN118210299A

CN118210299A - Cliff edge traveling control method and device based on multi-sensor data fusion

Info

Publication number: CN118210299A
Application number: CN202211592942.4A
Authority: CN
Inventors: 陈小平; 陈逸
Original assignee: Guangdong Lizi Technology Co Ltd
Current assignee: Guangdong Lizi Technology Co Ltd
Priority date: 2022-12-13
Filing date: 2022-12-13
Publication date: 2024-06-18

Abstract

The invention discloses a cliff edge traveling control method and device based on multi-sensor data fusion, wherein the method comprises the following steps: when the target cliff sensor corresponding to the intelligent equipment is detected to be triggered, acquiring environmental information of a current area based on the laser radar corresponding to the intelligent equipment; and estimating the travelling path of the intelligent equipment parallel to the cliff edge of the current area according to the acquired environmental information of the current area, and controlling the intelligent equipment to execute the moving operation parallel to the cliff edge according to the travelling path. Therefore, the intelligent equipment can accurately identify the cliff in the travelling area based on the environmental information acquired by the various sensors corresponding to the intelligent equipment, so that the intelligent equipment is estimated to move along the cliff fast travelling route, the intelligent equipment is controlled to move along the cliff according to the estimated travelling route, the intelligent equipment does not need to be interfered by a user to carry out route planning, the travelling efficiency of the intelligent equipment along the cliff is improved, and the falling situation of the intelligent equipment is reduced.

Description

Cliff edge traveling control method and device based on multi-sensor data fusion

Technical Field

The invention relates to the technical field of intelligent equipment movement, in particular to a cliff edge traveling control method and device based on multi-sensor data fusion.

Background

Along with the rapid development of intelligent cleaning robot technology, the intelligent cleaning robot has more and more intelligent functions, such as: the floor is automatically cleaned, and the household burden of the user can be reduced. Therefore, cleaning robots are favored by more and more users.

In practical application, when a cliff exists around a cleaning robot running route, the cleaning robot can effectively detect the cliff (such as stairs and high slopes) through the cliff sensor, and perform actions such as stopping, turning, bypassing and the like to prevent the cleaning robot from falling from a high place. However, when the conventional robot is used to avoid and travel along the cliff, the robot needs to repeatedly check the edge of the cliff, repeatedly advance and retreat, and the operation is complicated and time-consuming. Therefore, it is important to provide a technical solution that can improve the efficiency of the robot traveling along the cliff edge.

Disclosure of Invention

The invention aims to solve the technical problem of providing a cliff edge traveling control method and device based on multi-sensor data fusion, which can improve the edge traveling efficiency of a robot at the edge of a cliff.

In order to solve the technical problems, the first aspect of the invention discloses a cliff edge traveling control method based on multi-sensor data fusion, which comprises the following steps:

when the target cliff sensor corresponding to the intelligent equipment is detected to be triggered, acquiring environmental information of a current area based on the laser radar corresponding to the intelligent equipment;

And estimating a traveling path of the intelligent equipment parallel to the cliff edge of the current area according to the acquired environmental information of the current area, and controlling the intelligent equipment to execute a moving operation parallel to the cliff edge according to the traveling path.

As an alternative embodiment, in the first aspect of the present invention, the method further includes:

Determining a rotation control parameter of the intelligent device according to the position of the target cliff sensor on the intelligent device, controlling the intelligent device to execute rotation operation according to the rotation control parameter of the intelligent device, and executing the operation of acquiring the environmental information of the current area based on the laser radar corresponding to the intelligent device, wherein the environmental information of the current area comprises the currently acquired position information of the cliff edge point position of the current area;

Estimating a travel path of the intelligent device parallel to the cliff edge of the current area according to the collected environmental information of the current area, wherein the estimated travel path comprises the following steps:

Determining a reference distance corresponding to the cliff edge point position of the current area which is currently acquired according to the rotation control parameters of the intelligent equipment and the position information of the cliff edge point position of the current area which is currently acquired, wherein the reference distance corresponding to the cliff edge point position of the current area which is currently acquired is the smaller distance between the laser radar and the cliff edge point position of the current area which is currently acquired and the reference distance corresponding to the cliff edge point position of the current area which is determined last time; repeatedly executing the operation of determining the reference distance corresponding to the currently acquired cliff edge point position of the current area according to the rotation control parameters of the intelligent equipment and the currently acquired position information of the cliff edge point position of the current area;

After the operation is executed for a continuous preset number of times, and when the determined value of the reference distance corresponding to the cliff edge point position of the current area is always unchanged, controlling the intelligent equipment to stop rotating;

And estimating the travelling path of the intelligent equipment parallel to the cliff edge of the current area according to the acquired environmental information of the current area after the intelligent equipment stops rotating.

When the acquired environmental information of the current area comprises the distances between the laser radar and a plurality of measuring points in the current area, determining an acquisition result of the laser radar for the current area, and judging whether the acquisition result meets a cliff identification condition determined in advance;

If yes, determining the position of a measuring point meeting the cliff identification condition as a cliff, triggering the operation of estimating the travelling path of the intelligent equipment parallel to the cliff edge of the current area according to the collected environmental information of the current area;

wherein the judging whether the acquisition result meets the cliff identification condition determined in advance comprises the following steps:

When the acquisition result is that the distances corresponding to all the measurement points are acquired, judging whether the measurement points with the distances larger than or equal to a distance threshold exist in all the measurement points, if so, determining that the acquisition result meets a cliff identification condition determined in advance;

When the acquisition result is that the distances corresponding to all the measurement points are acquired, judging whether the measurement points with distance jump exist in all the measurement points, if so, determining that the acquisition result meets a predetermined cliff identification condition;

And when the acquired result is that the distances corresponding to all the measurement points are not acquired, determining that the acquired result meets the cliff identification condition which is determined in advance.

As an optional implementation manner, in the first aspect of the present invention, the controlling the smart device to perform a moving operation parallel to the cliff edge according to the travel path includes:

determining a second movement control parameter of the intelligent device according to the travel path;

And controlling the intelligent equipment to execute a moving operation parallel to the cliff edge according to the travelling path and a second moving control parameter of the intelligent equipment.

Collecting current movement parameters of the intelligent equipment and current position information of the intelligent equipment in the process that the intelligent equipment executes movement operation parallel to the edge of the cliff;

According to the current movement parameters of the intelligent equipment, the current position information of the intelligent equipment and the travelling path, adjusting second movement control parameters of the intelligent equipment based on a cliff edge travelling calculation model;

And controlling the intelligent equipment to execute the moving operation parallel to the cliff edge according to the adjusted second moving control parameter of the intelligent equipment.

As an optional implementation manner, in the first aspect of the present invention, the adjusting, based on the cliff edge traveling calculation model, the second movement parameter of the smart device according to the current movement parameter of the smart device, the current location information of the smart device, and the traveling path includes:

estimating a target position of the travel path to which the intelligent device is to be moved and a target movement control parameter corresponding to the target position to which the intelligent device is to be moved according to the current position information of the intelligent device, the current movement parameter of the intelligent device and the travel path;

Inputting the current position information of the intelligent equipment, the current movement parameters of the intelligent equipment, the target position of the intelligent equipment and the target movement control parameters corresponding to the target position into a cliff edge travel path adjustment calculation model, and calculating to obtain the position error between the current position information of the intelligent equipment and the target position of the intelligent equipment and the control parameter error between the current movement parameters of the intelligent equipment and the target movement control parameters of the intelligent equipment;

and adjusting a second movement control parameter of the intelligent device according to the position error and the control parameter error.

As an optional implementation manner, in the first aspect of the present invention, after the detecting that the target cliff sensor corresponding to the smart device is triggered, before the collecting, based on the lidar corresponding to the smart device, environmental information of the current area, the method further includes:

Determining a first movement control parameter of the intelligent device according to the position of the target cliff sensor on the intelligent device;

And controlling the intelligent equipment to execute a first moving operation according to the first moving control parameter of the intelligent equipment, and triggering the operation of collecting the environmental information of the current area based on the laser radar corresponding to the intelligent equipment.

Collecting ground information when the intelligent equipment is controlled to execute a moving operation parallel to the edge of the cliff, wherein the ground information comprises ground dirt degree and ground material type;

Analyzing the ground information to obtain cleaning control parameters of the intelligent equipment;

and controlling the intelligent equipment to execute cleaning operation according to the cleaning control parameters of the intelligent equipment.

The invention discloses a cliff edge traveling control device based on multi-sensor data fusion, which comprises the following components:

The first acquisition module is used for acquiring environmental information of a current area based on a laser radar corresponding to the intelligent equipment when the target cliff sensor corresponding to the intelligent equipment is triggered;

The estimating module is used for estimating the travelling path of the intelligent equipment parallel to the cliff edge of the current area according to the environmental information of the current area acquired by the first acquisition module;

And the first control module is used for controlling the intelligent equipment to execute a moving operation parallel to the cliff edge according to the travelling path.

As an alternative embodiment, in the second aspect of the present invention, the apparatus further includes:

The first determining module is used for determining rotation control parameters of the intelligent equipment according to the position of the target cliff sensor on the intelligent equipment;

the first control module is further used for controlling the intelligent equipment to execute rotation operation according to rotation control parameters of the intelligent equipment;

The estimating module estimates a traveling path of the intelligent device parallel to the cliff edge of the current area according to the environmental information of the current area acquired by the first acquisition module, wherein the specific mode comprises the following steps:

the second determining module is used for determining an acquisition result of the laser radar for the current area when the environmental information of the current area acquired by the first acquiring module comprises the distances between the laser radar and a plurality of measuring points in the current area;

The judging module is used for judging whether the acquisition result meets the cliff identification condition determined in advance;

The second determining module is further configured to determine, when the determining module determines that the acquisition result meets a cliff identification condition that is determined in advance, that a measurement point position that meets the cliff identification condition is a cliff, and trigger the estimating module to execute the operation of estimating, according to the environmental information of the current area acquired by the first acquiring module, a travel path of the intelligent device parallel to a cliff edge of the current area;

The specific mode of judging whether the acquisition result meets the predetermined cliff identification condition by the judging module comprises the following steps:

As an optional implementation manner, in the second aspect of the present invention, a specific manner of controlling, by the first control module, the smart device to perform a moving operation parallel to the cliff edge according to the travel path includes:

The second acquisition module is used for acquiring current movement parameters of the intelligent equipment and current position information of the intelligent equipment in the process that the intelligent equipment executes movement operation parallel to the edge of the cliff;

the adjustment module is used for adjusting a second movement control parameter of the intelligent equipment based on the cliff edge traveling calculation model according to the current movement parameter of the intelligent equipment, the current position information of the intelligent equipment and the traveling path;

the first control module is further configured to control the intelligent device to execute a movement operation parallel to the cliff edge according to the adjusted second movement control parameter of the intelligent device.

As an optional implementation manner, in the second aspect of the present invention, the specific manner of adjusting, by the adjustment module, the second movement control parameter of the smart device based on the cliff edge travel calculation model according to the current movement parameter of the smart device, the current location information of the smart device, and the travel path includes:

the first determining module is further configured to determine, after detecting that a target cliff sensor corresponding to an intelligent device is triggered, a first movement control parameter of the intelligent device according to a position of the target cliff sensor on the intelligent device before the laser radar corresponding to the intelligent device collects environmental information of a current area;

The first control module is further configured to control the intelligent device to perform a first movement operation according to a first movement control parameter of the intelligent device, and trigger the first acquisition module to perform an operation of acquiring environmental information of a current area based on a laser radar corresponding to the intelligent device.

the third acquisition module is used for acquiring ground information when the intelligent equipment is controlled to execute a moving operation parallel to the edge of the cliff, wherein the ground information comprises the ground pollution degree and the ground material type;

the analysis module is used for analyzing the ground information to obtain cleaning control parameters of the intelligent equipment;

And the second control module is used for controlling the intelligent equipment to execute cleaning operation according to the cleaning control parameters of the intelligent equipment.

The third aspect of the invention discloses another cliff edge traveling control device based on multi-sensor data fusion, which comprises:

A memory storing executable program code;

A processor coupled to the memory;

the processor invokes the executable program code stored in the memory to execute the cliff edge travel control method based on multi-sensor data fusion disclosed in the first aspect of the invention.

A fourth aspect of the present invention discloses a computer storage medium storing computer instructions for executing the cliff edgewise travel control method based on multi-sensor data fusion disclosed in the first aspect of the present invention when the computer instructions are called.

Compared with the prior art, the embodiment of the invention has the following beneficial effects:

In the embodiment of the invention, when the target cliff sensor corresponding to the intelligent equipment is detected to be triggered, the environmental information of the current area is collected based on the laser radar corresponding to the intelligent equipment; and estimating the travelling path of the intelligent equipment parallel to the cliff edge of the current area according to the acquired environmental information of the current area, and controlling the intelligent equipment to execute the moving operation parallel to the cliff edge according to the travelling path. Therefore, the intelligent equipment can accurately identify the cliff in the travelling area based on the environmental information acquired by the various sensors corresponding to the intelligent equipment, so that the intelligent equipment is estimated to move along the cliff fast travelling route, the intelligent equipment is controlled to move along the cliff according to the estimated travelling route, the intelligent equipment does not need to be interfered by a user to conduct route planning, the travelling efficiency of the intelligent equipment along the edge of the cliff is improved, the falling situation of the intelligent equipment can be reduced, and the intelligent equipment using experience of a user is improved, and the using viscosity of the intelligent equipment by the user is improved.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.

Fig. 1 is a schematic view of a cliff edge traveling control scene based on multi-sensor data fusion according to an embodiment of the present invention;

Fig. 2 is a schematic view of another cliff edge traveling control scene based on multi-sensor data fusion according to an embodiment of the present invention;

Fig. 3 is a schematic flow chart of a cliff edge traveling control method based on multi-sensor data fusion according to an embodiment of the present invention;

Fig. 4 is a schematic flow chart of another cliff edge traveling control method based on multi-sensor data fusion according to an embodiment of the present invention;

Fig. 5 is a schematic structural diagram of a cliff edge traveling control device based on multi-sensor data fusion according to an embodiment of the present invention;

Fig. 6 is a schematic structural diagram of another cliff edge traveling control device based on multi-sensor data fusion according to an embodiment of the present invention;

Fig. 7 is a schematic structural diagram of another cliff edge traveling control device based on multi-sensor data fusion according to an embodiment of the present invention.

Detailed Description

In order that those skilled in the art will better understand the present invention, a technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in which it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.

The terms first, second and the like in the description and in the claims and in the above-described figures are used for distinguishing between different objects and not necessarily for describing a sequential or chronological order. Furthermore, the terms "comprise" and "have," as well as any variations thereof, are intended to cover a non-exclusive inclusion. For example, a process, method, apparatus, article, or article that comprises a list of steps or elements is not limited to only those listed but may optionally include other steps or elements not listed or inherent to such process, method, article, or article.

Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment may be included in at least one embodiment of the invention. The appearances of such phrases in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. Those of skill in the art will explicitly and implicitly appreciate that the embodiments described herein may be combined with other embodiments.

The invention discloses a cliff edge traveling control method and device based on multi-sensor data fusion, which can accurately identify cliffs in a traveling area based on environmental information acquired by various sensors corresponding to intelligent equipment in the traveling process of the intelligent equipment so as to estimate a rapid traveling route of the intelligent equipment along the cliffs, control the intelligent equipment to move along the cliffs according to the estimated traveling route without intervention of a user on the intelligent equipment for route planning, improve the traveling efficiency of the intelligent equipment along the edges of the cliffs, and reduce the falling situation of the intelligent equipment, thereby being beneficial to improving the use experience of the user on the intelligent equipment and further improving the use viscosity of the intelligent equipment by the user. The following will describe in detail.

In order to better understand the method and the device for controlling the cliff edge traveling based on multi-sensor data fusion described in the present invention, a scene to which the method for controlling the cliff edge traveling based on multi-sensor data fusion is applied is first described, and specifically, the scene schematic diagram may be shown in fig. 1, and fig. 1 is a scene schematic diagram according to an embodiment of the present invention. As shown in fig. 1, a cliff edge traveling control scene diagram based on multi-sensor data fusion, which may include a smart device (e.g., a cleaning robot), a work area, a cliff (e.g., a stair), and a user, is illustrated with a large area as a stairwell area. The working area is a working range of the intelligent device, can be an area where the intelligent device moves and performs map drawing, and can be an area where the intelligent device moves and performs cleaning. A cliff is understood to be an interface area between two working areas of different heights. The cliff advancing control method of the intelligent equipment comprises the following steps of: when the target cliff sensor corresponding to the intelligent equipment is triggered, acquiring the environmental information of the current area based on the laser radar corresponding to the intelligent equipment, estimating the traveling path of the intelligent equipment parallel to the edge of the cliff of the current area according to the acquired environmental information of the current area, and controlling the intelligent equipment to execute the moving operation parallel to the edge of the cliff according to the traveling path, wherein if the intelligent equipment moves from the working area to the cliff, the intelligent equipment is caused to fall from a high place. A scenario in which the intelligent device performs a movement operation parallel to the edge of the cliff is shown in fig. 2, and fig. 2 is a schematic diagram of another scenario of a cliff edge traveling control scenario based on multi-sensor data fusion according to an embodiment of the present invention.

It should be noted that, the scene schematic diagram shown in fig. 1 is only for illustrating a scene suitable for the cliff edge traveling control method based on multi-sensor data fusion, the related intelligent devices, working areas, cliffs, etc. are also only schematically presented, and the scene schematic diagram shown in fig. 1 is not limited thereto. The application scenario to which the cliff edge traveling control method based on multi-sensor data fusion is applicable is described above, and the cliff edge traveling control method and device based on multi-sensor data fusion are described in detail below.

Example 1

Referring to fig. 3, fig. 3 is a flow chart of a cliff edge traveling control method based on multi-sensor data fusion according to an embodiment of the present invention. The method for controlling the cliff edge traveling based on multi-sensor data fusion described in fig. 3 may be applied to a device for controlling the cliff edge traveling based on multi-sensor data fusion, where the device includes any one of an intelligent device that needs to perform the cliff edge traveling, a server that is used to control the intelligent device, and an intelligent platform, where the server includes a cloud server or a local server, where the intelligent device that needs to perform the cliff edge traveling may be a cleaning robot or an intelligent trolley, and embodiments of the present invention are not limited. As shown in fig. 3, the cliff edge travel control method based on multi-sensor data fusion may include the following operations:

101. when the target cliff sensor corresponding to the intelligent equipment is triggered, the environmental information of the current area is collected based on the laser radar corresponding to the intelligent equipment.

In the embodiment of the invention, the target cliff sensor corresponding to the intelligent equipment can be at least one cliff sensor arranged on the intelligent equipment, and when a plurality of cliff sensors are arranged on the intelligent equipment, each cliff sensor is arranged at different positions on the intelligent equipment; the target cliff sensor corresponding to the intelligent device may also be at least one cliff sensor connected to the intelligent device through a server or an intelligent platform, which is not limited in the embodiment of the present invention. The data collected by the cliff sensor is the ambient light intensity; the triggering of the target cliff sensor can be understood as: when the ambient light intensity collected by the cliff sensor exceeds an ambient light intensity threshold, determining that the cliff sensor is triggered, namely, the cliff sensor detected to be triggered is a target cliff sensor.

In the embodiment of the invention, the laser radar corresponding to the intelligent equipment can be the laser radar installed on the intelligent equipment, or can be the laser radar connected with the intelligent equipment through a server or an intelligent platform, and the embodiment of the invention is not limited. The laser radar corresponding to the intelligent device can be a two-dimensional laser radar and/or a three-dimensional laser radar, and the embodiment of the invention is not limited.

In the embodiment of the invention, the environmental information of the current area can comprise x and y of the current position of the intelligent device, the acquisition direction of the laser radar, a plurality of measurement points acquired by the laser radar and the distance between the laser radar and the plurality of measurement points in a two-dimensional rectangular coordinate system of the current area; the measurement point is understood to be the position detected by the lidar in the current region.

102. And estimating the travelling path of the intelligent equipment parallel to the cliff edge of the current area according to the acquired environmental information of the current area.

In the embodiment of the present invention, the cliff may be understood as an area lower than the current travelling area of the intelligent device, and the cliff may be a stair, a high slope, a high table, a tatami or a bay window, which is not limited in the embodiment of the present invention. The shape of the cliff edge may be a straight line, a smooth curve or a broken line composed of a plurality of line segments, which is not limited in the embodiment of the present invention; the travel path of the smart device parallel to the cliff edge of the current area can be understood as: on the travel path, for each point in time, the current travel direction of the intelligent device is parallel to the tangent of the cliff edge point that is the shortest distance from the current location of the intelligent device.

103. According to the travelling path, the intelligent device is controlled to execute a moving operation parallel to the edge of the cliff.

Therefore, the method described by the embodiment of the invention can accurately identify the cliff in the travelling area based on the environmental information acquired by the various sensors corresponding to the intelligent equipment, so as to estimate the rapid travelling route of the intelligent equipment along the cliff, control the intelligent equipment to move along the cliff according to the estimated travelling route, and avoid the need of user intervention on the intelligent equipment for route planning, thereby not only improving the travelling efficiency of the intelligent equipment along the edge of the cliff, but also reducing the falling situation of the intelligent equipment, and further being beneficial to improving the use experience of the intelligent equipment by the user and further improving the use viscosity of the intelligent equipment by the user.

In an alternative embodiment, after detecting that the target cliff sensor corresponding to the smart device is triggered, before collecting the environmental information of the current area based on the lidar corresponding to the smart device, the method may further include:

The first movement control parameter of the intelligent device may include a first movement direction and a first movement rate; when the target cliff sensor corresponding to the intelligent device is a cliff sensor installed on the intelligent device, the position of the target cliff sensor on the intelligent device is the installation position of the target cliff sensor on the intelligent device, and the installation position is predetermined and stored in a storage medium corresponding to the intelligent device.

Therefore, according to the alternative embodiment, the first movement control parameter of the intelligent device can be determined according to the position of the target cliff sensor on the intelligent device, and the intelligent device is controlled to retreat, so that the intelligent device can effectively avoid the cliff, the situation that the intelligent device continuously moves towards the cliff to fall down is reduced, and the safety of the intelligent device during movement is improved.

In another alternative embodiment, the method may further comprise:

When the intelligent equipment is controlled to execute a moving operation parallel to the edge of the cliff, collecting ground information, wherein the ground information comprises the ground dirt degree and the ground material type;

Analyzing ground information to obtain cleaning control parameters of the intelligent equipment;

Wherein the cleaning control parameters may include: one or more combinations of cleaning range, cleaning intensity, cleaning pattern, and cleaning procedure; the cleaning mode may include: one or more of sweeping the floor, scrubbing the floor, sanitizing the floor.

It can be seen that this optional embodiment can gather and analyze ground information when intelligent device moves along cliff edge, obtains intelligent device's clean control parameter, and control intelligent device cleans ground, has improved intelligent device's multitasking capability, is favorable to improving intelligent device's work efficiency, and then is favorable to liberating user's both hands, improves user's use experience.

Example two

Referring to fig. 4, fig. 4 is a schematic flow chart of a cliff edge traveling control method based on multi-sensor data fusion according to an embodiment of the present invention. The method for controlling the cliff edge traveling based on multi-sensor data fusion described in fig. 4 may be applied to a device for controlling the cliff edge traveling based on multi-sensor data fusion, where the device includes any one of an intelligent device that needs to perform the cliff edge traveling, a server that is used to control the intelligent device, and an intelligent platform, where the server includes a cloud server or a local server, where the intelligent device that needs to perform the cliff edge traveling may be a cleaning robot or an intelligent trolley, and embodiments of the present invention are not limited. As shown in fig. 4, the cliff edge travel control method based on multi-sensor data fusion may include the following operations:

201. after the target cliff sensor corresponding to the intelligent device is triggered, determining the rotation control parameters of the intelligent device according to the position of the target cliff sensor on the intelligent device.

In the embodiment of the present invention, rotation control parameters of the intelligent device may include: rotation direction, rotation angle, and rotation angular velocity.

202. And controlling the intelligent equipment to execute the rotation operation according to the rotation control parameters of the intelligent equipment.

Optionally, steps 201 to 202 may be performed after the first embodiment is performed, where the first movement control parameter of the intelligent device is determined according to the position of the target cliff sensor on the intelligent device, the first movement operation is controlled to be performed by the intelligent device according to the first movement control parameter of the intelligent device, and the operation of collecting the environmental information of the current area based on the lidar corresponding to the intelligent device is triggered. By controlling the intelligent equipment to sequentially withdraw and rotate, the accuracy of the intelligent equipment for avoiding the cliff can be improved, so that the probability of falling off the cliff of the intelligent equipment is reduced.

203. And acquiring environmental information of the current area based on the laser radar corresponding to the intelligent equipment.

In the embodiment of the invention, the environmental information of the current area comprises the position information of the cliff edge point position of the current area which is currently acquired.

204. And determining the reference distance corresponding to the cliff edge point position of the current region which is currently acquired according to the rotation control parameters of the intelligent device and the position information of the cliff edge point position of the current region which is currently acquired.

In the embodiment of the invention, the reference distance corresponding to the cliff edge point position of the current region acquired at present is the smaller distance of the distance between the laser radar and the cliff edge point position of the current region acquired at present and the reference distance corresponding to the cliff edge point position of the current region determined at last time.

If no record of the reference distance corresponding to the cliff edge point position of the current area is determined last time, determining the initial reference distance as the reference distance corresponding to the cliff edge point position of the current area determined last time; the initial reference distance may be a preset initial value, or may be a distance between the laser radar and the cliff edge point position of the current area acquired for the first time.

205. After the step 204 is executed for a continuous preset number of times, and the determined value of the reference distance corresponding to the cliff edge point position of the current area is kept unchanged all the time, the intelligent equipment is controlled to stop rotating.

In the embodiment of the invention, when the intelligent equipment stops rotating, the current moving direction of the intelligent equipment is almost parallel to the edge of the cliff.

It should be noted that, step 202 is not related to any of steps 203 to 205, that is, step 202 may occur before or after any of steps 203 to 205 or may occur simultaneously with any of steps 203 to 205, which is not limited by the embodiment of the present invention.

206. And estimating the travelling path of the intelligent equipment parallel to the cliff edge of the current area according to the environmental information of the current area acquired after the intelligent equipment stops rotating.

207. According to the travelling path, the intelligent device is controlled to execute a moving operation parallel to the edge of the cliff.

In the embodiment of the present invention, for other detailed descriptions of step 201, step 203, step 206 and step 207, please refer to the detailed descriptions of step 101-step 103 in the first embodiment, and the detailed descriptions of the embodiment of the present invention are omitted.

For the embodiment of the invention, the following related experiments are performed: placing the intelligent device on a cliff platform with an area of 2.5 square meters; the movement of the intelligent device along the edge of the cliff using only the cliff sensor takes 2 minutes and 50 seconds, while the movement of the intelligent device along the edge of the cliff using the cliff sensor in combination with the lidar takes only 50 seconds. It can be seen that the efficiency of movement along the cliff edge of a smart device using cliff sensors in combination with lidar is significantly improved.

Therefore, the method described by the embodiment of the invention can accurately identify the cliff in the travelling area based on the environmental information acquired by the various sensors corresponding to the intelligent equipment, so as to estimate the rapid travelling route of the intelligent equipment along the cliff, control the intelligent equipment to move along the cliff according to the estimated travelling route, and avoid the need of user intervention on the intelligent equipment for route planning, thereby not only improving the travelling efficiency of the intelligent equipment along the edge of the cliff, but also reducing the falling situation of the intelligent equipment, and further being beneficial to improving the use experience of the intelligent equipment by the user and further improving the use viscosity of the intelligent equipment by the user. In addition, the reference distance can be determined through the rotation parameters and the acquired position information, when the reference distance determined continuously and repeatedly is the same distance, the prediction operation of the traveling path of the edge of the cliff is executed, the prediction accuracy of the traveling path can be improved, the control accuracy of the intelligent equipment in parallel advancing along the edge of the cliff is improved, and the probability of the intelligent equipment falling from the cliff is further reduced.

In an alternative embodiment, the method may further comprise:

If yes, determining the position of a measuring point meeting cliff identification conditions as a cliff, triggering the operation of estimating the travelling path of the intelligent equipment parallel to the edge of the cliff of the current area according to the collected environmental information of the current area;

The determining whether the collection result meets the cliff identification condition determined in advance may include:

When the acquisition result is that the distances corresponding to all the measurement points are acquired, judging whether the measurement points with the distances larger than or equal to a distance threshold exist in all the measurement points, if so, determining that the acquisition result meets the cliff identification condition determined in advance;

When the acquisition result is that the distances corresponding to all the measurement points are acquired, judging whether the measurement points with the distance jump exist in all the measurement points, if so, determining that the acquisition result meets the cliff identification condition which is determined in advance;

and when the acquisition result is that the distances corresponding to all the measurement points are not acquired, determining that the acquisition result meets the cliff identification condition which is determined in advance.

Therefore, according to the alternative embodiment, the distance between the laser radar and a plurality of measuring points in the current area can be acquired, the acquisition result of the laser radar for the current area can be analyzed, the position of the cliff in the current area is determined based on various cliff identification conditions, the accuracy of identifying the cliff by the intelligent equipment is improved, the accuracy of estimating the cliff edge travelling path of the intelligent equipment parallel to the current area is improved, and further the efficiency of moving the intelligent equipment along the cliff edge is improved.

In this alternative embodiment, optionally, the method may further comprise:

Analyzing the acquired results to obtain data analysis results of the acquired results;

According to the data analysis result of the acquisition result, determining the quality grade of the acquisition result, wherein the quality grade is used for representing the reliability degree and/or the referenceability degree of the acquisition result, and the higher the quality grade is, the higher the reliability degree and/or the referenceability degree of the acquisition result is;

screening out measuring points with the quality of measuring points being greater than or equal to a preset quality threshold corresponding to the quality grade in the acquired results according to the quality grade of the acquired results, and triggering and judging whether the screened acquired results meet the preset cliff identification conditions;

Wherein, according to the data analysis result of the collection result, determining the quality level of the collection result may include:

When the number of the measurement points in the acquisition result is greater than or equal to a preset number threshold, determining the number level of the acquisition result as a first level, otherwise, determining the number level of the acquisition result as a second level;

And/or the number of the groups of groups,

When the density degree of the measurement points in the acquisition result is greater than or equal to the preset density degree, determining the density level of the acquisition result as a first level, otherwise, determining the density level of the acquisition result as a second level;

And processing the number level of the acquisition results and the dense level of the acquisition results based on the corresponding weighting coefficients, and determining the quality level of the acquisition results.

Therefore, the quality grade of the acquisition result can be determined according to the data analysis result of the acquisition result, and the measurement points meeting the quality requirement are screened out from the acquisition result to perform subsequent cliff identification operation, so that the accuracy of the cliff identification operation is improved, the reliability and the accuracy of the cliff identification result are improved, and the accuracy of estimating the cliff edge travelling path of the intelligent equipment parallel to the current area is further improved.

In this alternative embodiment, optionally, controlling the smart device to perform a moving operation parallel to the cliff edge according to the travel path may include the steps of:

Determining a second movement control parameter of the intelligent device according to the travelling path;

And controlling the intelligent device to execute the moving operation parallel to the cliff edge according to the travelling path and the second moving control parameter of the intelligent device.

Wherein the second movement control parameter of the smart device may include a second movement direction and a second movement rate.

Therefore, the second movement control parameter of the intelligent device can be determined according to the travel path, which is beneficial to accurately setting the movement parameter for controlling the intelligent device to travel on the travel path, and further accurately controlling the intelligent device to move on the estimated travel path, so that the actual travel path of the intelligent device along the edge of the cliff is closer to the estimated travel path, and the accuracy of the intelligent device along the edge of the cliff is improved.

In this alternative embodiment, optionally, the method may further comprise:

According to the current movement parameters of the intelligent equipment, the current position information of the intelligent equipment and the travelling path, adjusting second movement control parameters of the intelligent equipment based on the cliff edge travelling calculation model;

And controlling the intelligent equipment to execute the moving operation parallel to the edge of the cliff according to the adjusted second moving control parameter of the intelligent equipment.

The current movement parameters may include a current movement direction and a current movement rate, among others.

Therefore, the optional embodiment can collect current movement parameters and position information of the intelligent device in real time, adjust the second movement control parameters based on the cliff edge travelling calculation model so as to improve the accuracy of the second movement control parameters, further, control the intelligent device to execute the movement operation parallel to the cliff edge according to the second movement control parameters, and adjust the actual travelling path of the intelligent device along the cliff, so that the intelligent device can be controlled to move along the cliff edge more accurately and effectively, and the efficiency of the intelligent device along the cliff edge can be improved.

In this optional embodiment, further optionally, adjusting the second movement parameter of the smart device based on the cliff edge travel calculation model according to the current movement parameter of the smart device, the current location information of the smart device, and the travel path may include:

Estimating a target position of a travel path to which the intelligent device is to be moved and a target movement control parameter corresponding to the target position to which the intelligent device is to be moved according to the current position information of the intelligent device, the current movement parameter of the intelligent device and the travel path;

inputting the current position information of the intelligent equipment, the current movement parameters of the intelligent equipment, the target position of the intelligent equipment and the target movement control parameters corresponding to the target position into a cliff edge traveling path adjustment calculation model, and calculating to obtain the position error between the current position information of the intelligent equipment and the target position of the intelligent equipment and the control parameter error between the current movement parameters of the intelligent equipment and the target movement control parameters of the intelligent equipment;

The current position information comprises the distance between the laser radar and the currently acquired cliff edge point position.

Therefore, according to the alternative embodiment, the target position and the target movement control parameter of the intelligent device can be determined through the current movement parameter, the position information and the estimated travel path of the intelligent device, the error value of the position and the control parameter is calculated in real time, the second movement control parameter of the intelligent device is adjusted more accurately, the movement of the intelligent device parallel to the edge of the cliff is further effectively controlled, and the efficiency of the intelligent device moving along the edge of the cliff is further improved.

In this alternative embodiment, further optionally, the method may further comprise:

determining the working parameters of the motor of the intelligent equipment according to the position error, the control parameter error and the motor type of the intelligent equipment;

and adjusting a second movement control parameter of the intelligent equipment according to the motor working parameter of the intelligent equipment.

The motor of the intelligent device can be a micro motor, the micro motor can be an alternating current motor, a direct current motor or a stepping motor, the direct current motor can comprise a brush direct current motor and/or a brushless direct current motor, and the embodiment of the invention is not limited; the motor operating parameters of the smart device may include a motor pulse width modulation value or a motor pulse width modulation frequency.

Therefore, according to the alternative embodiment, the motor working parameters of the intelligent equipment can be determined according to the error value calculated based on the cliff edge travelling path adjustment calculation model and the motor type of the intelligent equipment, and the second movement control parameters can be adjusted in a self-adaptive manner more pertinently according to the motor working parameters, so that the accuracy of the estimated travelling path of the intelligent equipment parallel to the cliff edge is improved, and the moving efficiency of the intelligent equipment along the cliff is improved.

In this alternative embodiment, optionally, the method may further comprise:

Collecting working parameters of the intelligent equipment and ground material parameters of the cliff edge area in the process that the intelligent equipment executes a moving operation parallel to the cliff edge;

Determining the current friction force born by the bottom of the intelligent equipment according to the working parameters of the intelligent equipment and the ground material parameters of the cliff edge area;

Judging whether the friction force currently born by the bottom of the intelligent device is smaller than or equal to a preset friction force threshold value;

If so, adjusting a second movement control parameter of the intelligent equipment according to the ground material parameter of the cliff edge area and the friction force;

The working parameters of the intelligent equipment comprise the quality of the intelligent equipment and the current movement parameters of the intelligent equipment, and the ground material parameters of the cliff edge area comprise one or more of the combination of the ground material type, the ground texture shape and the ground texture direction.

Therefore, according to the optional embodiment, the current friction force born by the bottom of the intelligent device can be calculated according to the working parameters of the intelligent device and the ground material parameters of the edge area of the cliff, and when the friction force born by the bottom of the intelligent device is too small, the second movement control parameters of the intelligent device can be adjusted in a self-adaptive manner, so that the possibility of skidding of the intelligent device in the movement process of the edge area of the cliff is reduced, the accuracy and the reliability of the intelligent device travelling along the edge of the cliff are improved, and the probability of falling of the intelligent device from the cliff is reduced.

Example III

Referring to fig. 5, fig. 5 is a schematic structural diagram of a cliff edge traveling control device based on multi-sensor data fusion according to an embodiment of the present invention. The cliff edge traveling control device based on multi-sensor data fusion described in fig. 5 may include any one of an intelligent device that needs to perform cliff edge traveling, a server for controlling the intelligent device, or an intelligent platform, where the server includes a cloud server or a local server, where the intelligent device that needs to perform cliff edge traveling may be a cleaning robot or an intelligent trolley, and the embodiment of the present invention is not limited. As shown in fig. 5, the cliff edge travel control device based on multi-sensor data fusion may include:

the first acquisition module 301 is configured to acquire environmental information of a current area based on a laser radar corresponding to the intelligent device when it is detected that a target cliff sensor corresponding to the intelligent device is triggered;

The estimating module 302 is configured to estimate, according to the environmental information of the current area collected by the first collecting module 301, a travel path of the intelligent device parallel to a cliff edge of the current area;

the first control module 303 is configured to control the smart device to perform a movement operation parallel to the edge of the cliff according to the travel path.

Therefore, the device described by the embodiment of the invention can accurately identify the cliff in the travelling area based on the environmental information acquired by the various sensors corresponding to the intelligent equipment, so as to estimate the rapid travelling route of the intelligent equipment along the cliff, control the intelligent equipment to move along the cliff according to the estimated travelling route, and avoid the need of user intervention on the intelligent equipment for route planning, thereby not only improving the travelling efficiency of the intelligent equipment along the edge of the cliff, but also reducing the falling situation of the intelligent equipment, and further being beneficial to improving the use experience of the intelligent equipment by a user and further improving the use viscosity of the intelligent equipment by the user.

In this alternative embodiment, as shown in fig. 6, the apparatus may further include:

a first determining module 304, configured to determine a rotation control parameter of the intelligent device according to a position of the target cliff sensor on the intelligent device;

The first control module 303 is further configured to control the intelligent device to perform a rotation operation according to a rotation control parameter of the intelligent device;

the estimating module 302 estimates, according to the environmental information of the current area acquired by the first acquiring module 301, a travel path of the intelligent device parallel to the cliff edge of the current area in a specific manner, including:

Determining a reference distance corresponding to the cliff edge point position of the current region acquired at present according to the rotation control parameters of the intelligent device and the position information of the cliff edge point position of the current region acquired at present, wherein the reference distance corresponding to the cliff edge point position of the current region acquired at present is the smaller distance between the laser radar and the cliff edge point position of the current region acquired at present and the reference distance corresponding to the cliff edge point position of the current region determined at last time; repeatedly executing the operation of determining the reference distance corresponding to the cliff edge point position of the current region which is currently acquired according to the rotation control parameters of the intelligent device and the position information of the cliff edge point position of the current region which is currently acquired;

After the operation is executed for a continuous preset number of times, and the value of the reference distance corresponding to the cliff edge point position of the determined current area is always unchanged, controlling the intelligent equipment to stop rotating;

and estimating the travelling path of the intelligent equipment parallel to the cliff edge of the current area according to the environmental information of the current area acquired after the intelligent equipment stops rotating.

Therefore, the device described by implementing the alternative embodiment can accurately identify the cliff in the travelling area based on the environmental information acquired by the various sensors corresponding to the intelligent device, so as to estimate the rapid travelling route of the intelligent device along the cliff, control the intelligent device to move along the cliff according to the estimated travelling route, and avoid the need of user intervention on the intelligent device to conduct route planning, thereby not only improving the travelling efficiency of the intelligent device along the edge of the cliff, but also reducing the falling situation of the intelligent device, and further being beneficial to improving the use experience of the intelligent device for users and further improving the use viscosity of the intelligent device for users. In addition, the reference distance can be determined through the rotation parameters and the acquired position information, when the reference distance determined continuously and repeatedly is the same distance, the prediction operation of the traveling path of the edge of the cliff is executed, the prediction accuracy of the traveling path can be improved, the control accuracy of the intelligent equipment in parallel advancing along the edge of the cliff is improved, and the probability of the intelligent equipment falling from the cliff is further reduced.

In this alternative embodiment, optionally, the apparatus may further include:

a second determining module 305, configured to determine an acquisition result of the laser radar for the current area when the environmental information of the current area acquired by the first acquiring module 301 includes distances between the laser radar and a plurality of measurement points in the current area;

a judging module 306, configured to judge whether the acquisition result meets a predetermined cliff identification condition;

The second determining module 307 is further configured to determine, when the determining module 306 determines that the acquisition result meets the cliff identification condition determined in advance, that the measurement point position meeting the cliff identification condition is a cliff, and trigger the estimating module 302 to execute an operation of estimating, according to the environmental information of the current area acquired by the first acquiring module 301, a travel path of the intelligent device parallel to a cliff edge of the current area;

the specific ways that the judging module 306 judges whether the collection result meets the cliff identification condition determined in advance include:

It can be seen that the device described by implementing the alternative embodiment can determine the location of the cliff in the current area based on various cliff identification conditions by acquiring the distances between the laser radar and a plurality of measurement points in the current area and analyzing the acquisition result of the laser radar for the current area, thereby improving the accuracy of identifying the cliff by the intelligent device, being beneficial to estimating the accuracy of the cliff edge travelling path of the intelligent device parallel to the current area, and further being beneficial to improving the efficiency of the intelligent device moving along the cliff edge.

In this alternative embodiment, optionally, the specific manner in which the first control module 304 controls the smart device to perform the movement operation parallel to the cliff edge according to the travel path includes:

Therefore, the device described by implementing the alternative embodiment can determine the second movement control parameter of the intelligent device according to the travel path, which is favorable for accurately setting the movement parameter for controlling the intelligent device to travel on the travel path, and further accurately controlling the intelligent device to move on the estimated travel path, so that the actual travel path of the intelligent device along the edge of the cliff is closer to the estimated travel path, and the accuracy of the intelligent device along the edge of the cliff is improved.

Optionally, the apparatus may further include:

a second acquisition module 307, configured to acquire current movement parameters of the intelligent device and current position information of the intelligent device during a movement operation performed by the intelligent device parallel to the edge of the cliff;

An adjustment module 308, configured to adjust a second movement control parameter of the intelligent device based on the cliff edge traveling calculation model according to the current movement parameter of the intelligent device, the current position information of the intelligent device, and the traveling path;

the first control module 303 is further configured to control the smart device to perform a movement operation parallel to the cliff edge according to the adjusted second movement control parameter of the smart device.

Therefore, the device described by implementing the alternative embodiment can collect the current movement parameters and the position information of the intelligent equipment in real time, and adjust the second movement control parameters based on the cliff edge travelling calculation model so as to improve the accuracy of the second movement control parameters.

Further optionally, the adjusting module 309 adjusts the second movement control parameter of the intelligent device based on the cliff edge travel calculation model according to the current movement parameter of the intelligent device, the current location information of the intelligent device, and the travel path, and the specific manner includes:

Therefore, the device described by implementing the alternative embodiment can determine the target position and the target movement control parameter of the intelligent device through the current movement parameter, the position information and the estimated travel path of the intelligent device, calculate the error value of the position and the control parameter in real time, more accurately adjust the second movement control parameter of the intelligent device, further effectively control the intelligent device to move parallel to the edge of the cliff, and be beneficial to further improving the efficiency of the intelligent device moving along the edge of the cliff.

In this alternative embodiment, optionally, the apparatus may further include:

The first determining module 304 is further configured to determine, after detecting that the target cliff sensor corresponding to the intelligent device is triggered, a first movement control parameter of the intelligent device according to a position of the target cliff sensor on the intelligent device before acquiring environmental information of a current area based on the lidar corresponding to the intelligent device;

The first control module 303 is further configured to control the intelligent device to perform a first movement operation according to a first movement control parameter of the intelligent device, and trigger the first acquisition module 301 to perform an operation of acquiring environmental information of a current area based on a lidar corresponding to the intelligent device.

Therefore, the device described by implementing the alternative embodiment can determine the first movement control parameter of the intelligent device according to the position of the target cliff sensor on the intelligent device and control the intelligent device to retreat, so that the intelligent device can effectively avoid the cliff, the situation that the intelligent device continuously moves towards the cliff to fall down is reduced, and the safety of the intelligent device during movement is improved.

In another alternative embodiment, the apparatus further comprises:

A third acquisition module 309, configured to acquire ground information when the intelligent device is controlled to perform a moving operation parallel to the edge of the cliff, where the ground information includes a ground soil level and a ground material type;

The analysis module 310 is used for analyzing the ground information to obtain the cleaning control parameters of the intelligent equipment;

the second control module 311 is configured to control the intelligent device to perform a cleaning operation according to the cleaning control parameter of the intelligent device.

Therefore, the device described by implementing the alternative embodiment can collect and analyze ground information when the intelligent device moves, obtain the cleaning control parameters of the intelligent device, control the intelligent device to clean the ground, improve the multitasking capability of the intelligent device, be beneficial to improving the working efficiency of the intelligent device, and further be beneficial to liberating the hands of a user and improve the use experience of the user.

Example IV

Referring to fig. 7, fig. 7 is a schematic structural diagram of another cliff edge traveling control device based on multi-sensor data fusion according to an embodiment of the present invention. As shown in fig. 7, the cliff edge travel control device based on multi-sensor data fusion may include:

a memory 401 storing executable program codes;

a processor 402 coupled with the memory 401;

the processor 402 invokes executable program codes stored in the memory 401 to perform the steps in the cliff edge travel control method based on multi-sensor data fusion described in the first or second embodiment of the present invention.

Example five

The embodiment of the invention discloses a computer storage medium which stores computer instructions for executing the steps in the cliff edge travelling control method based on multi-sensor data fusion described in the first embodiment or the second embodiment of the invention when the computer instructions are called.

Example six

Embodiments of the present invention disclose a computer program product comprising a non-transitory computer readable storage medium storing a computer program, and the computer program is operable to cause a computer to perform the steps in the cliff edge travel control method described in embodiment one or embodiment two, based on multi-sensor data fusion.

The apparatus embodiments described above are merely illustrative, wherein the modules illustrated as separate components may or may not be physically separate, and the components shown as modules may or may not be physical, i.e., may be located in one place, or may be distributed over a plurality of network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art will understand and implement the present invention without undue burden.

From the above detailed description of the embodiments, it will be apparent to those skilled in the art that the embodiments may be implemented by means of software plus necessary general hardware platforms, or of course by means of hardware. Based on such understanding, the foregoing technical solutions may be embodied essentially or in part in the form of a software product that may be stored in a computer-readable storage medium including Read-Only Memory (ROM), random access Memory (Random Access Memory, RAM), programmable Read-Only Memory (Programmable Read-Only Memory, PROM), erasable programmable Read-Only Memory (Erasable Programmable Read Only Memory, EPROM), one-time programmable Read-Only Memory (OTPROM), electrically erasable programmable Read-Only Memory (EEPROM), compact disc Read-Only Memory (Compact Disc Read-Only Memory, CD-ROM) or other optical disc Memory, magnetic disc Memory, tape Memory, or any other medium that can be used for computer-readable carrying or storing data.

Finally, it should be noted that: the embodiment of the invention discloses a cliff edge advancing control method and device based on multi-sensor data fusion, which are disclosed by the embodiment of the invention only for illustrating the technical scheme of the invention, but not limiting the technical scheme; although the invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art will understand that; the technical scheme recorded in the various embodiments can be modified or part of technical features in the technical scheme can be replaced equivalently; such modifications and substitutions do not depart from the spirit and scope of the corresponding technical solutions.

Claims

1. A cliff edge travel control method based on multi-sensor data fusion, the method comprising:

2. The cliff edge travel control method based on multi-sensor data fusion of claim 1, wherein the method further comprises:

3. The cliff edge travel control method based on multi-sensor data fusion of claim 2, wherein the method further comprises:

4. A cliff edge travel control method based on multi-sensor data fusion according to any one of claims 1-3, wherein said controlling said smart device to perform a movement operation parallel to said cliff edge according to said travel path comprises:

5. A cliff edgewise travel control method based on multi-sensor data fusion according to any one of claims 1-3, characterized in that the method further comprises:

6. The cliff side travel control method based on multi-sensor data fusion according to claim 5, wherein the adjusting the second movement parameter of the intelligent device based on the cliff side travel calculation model according to the current movement parameter of the intelligent device, the current position information of the intelligent device, and the travel path comprises:

7. The cliff side travel control method based on multi-sensor data fusion according to claim 1,2, 3 or 6, wherein after the target cliff sensor corresponding to the smart device is detected to be triggered, before the environmental information of the current area is collected based on the lidar corresponding to the smart device, the method further comprises:

8. The cliff edgewise travel control method based on multi-sensor data fusion of claim 1,2,3 or 6, further comprising:

9. A cliff edge travel control device based on multi-sensor data fusion, the device comprising:

10. A cliff edge travel control device based on multi-sensor data fusion, the device comprising:

A memory storing executable program code;

A processor coupled to the memory;

The processor invokes the executable program code stored in the memory to perform the cliff edge travel control method based on multi-sensor data fusion as claimed in any one of claims 1-8.