All-terrain assault tracked robot for monitoring

Abstract

The invention relates to the technical field of robots, and particularly discloses an all-terrain assault tracked robot for monitoring, which comprises a track transmission mechanism for driving a robot body to walk; the detection module is arranged on the robot body and used for detecting road surface environment data; and the adjusting module is used for adjusting the tensioning force of the crawler belt on the crawler belt transmission mechanism according to the road surface environment data detected by the detection module. According to the condition of the road surface where the robot body passes through, the tensioning force of the crawler belt is correspondingly adjusted so as to select the proper tensioning force to pass through different road surfaces, the walking speed of the robot body is guaranteed, meanwhile, the crawler belt is prevented from being separated from the belt wheels, and the stability of the crawler belt transmission mechanism walking on various road surfaces is guaranteed; and the service life of the crawler belt can be prolonged.

Description

Technical Field

[0001] The present invention relates to the field of robot technology, and more particularly to an all-terrain charging crawler robot for monitoring. Background Art

[0002] Tracked robots used for monitoring can replace people to conduct reconnaissance work in dangerous environments. For example, before fire rescue work is carried out, the robot can enter the oxygen-deficient or toxic environment to carry out reconnaissance work, and can perform monitoring work such as relevant data collection, processing and feedback. Because the terrain where the robot is located is relatively complex during the rescue, it is necessary for it to be able to walk on various terrains to carry out reconnaissance work smoothly.

[0003] In the prior art, there are many tracked robots that can adapt to various terrains. Most of them consider how to enable the robots to walk on various terrains, but less consideration is given to the stability of the tracks when walking on various terrains, especially the tension of the tracks affects the walking speed and life of the robot. The time for reconnaissance during the rescue process is very precious, and the robot needs to be able to collect, process and feedback the corresponding data in the shortest time. Therefore, it is necessary to propose an all-terrain assault tracked robot for monitoring to at least partially solve the problems existing in the prior art. Summary of the Invention

[0004] The Summary of the Invention introduces a series of simplified concepts that will be further described in the Detailed Description of the Invention. The Summary of the Invention is not intended to limit the key features and essential features of the claimed technical solution, nor is it intended to determine the scope of protection of the claimed technical solution.

[0005] To at least partially solve the above problems, the present invention provides an all-terrain charging crawler robot for monitoring, comprising: The crawler transmission mechanism is used to drive the robot body to walk; A detection module is provided on the robot body and is used to detect road environment data; The adjustment module is used to adjust the tension of the crawler track on the crawler drive mechanism according to the road environment data detected by the detection module.

[0006] Preferably, the adjustment module includes: A selection unit selects a set tension force corresponding to the road environment data detected by the detection module; An adjusting unit adjusts the tension of the crawler belt on the crawler belt transmission mechanism to the set tension selected by the selecting unit; The track tension measurement module detects the track tension and adjusts the extension and contraction, thus maintaining the balance of extension and contraction of each part of the track and further enhancing the stability of the track during operation; The track tensioning measurement module includes: a track tensioning and expansion measuring device, an upper and lower track tensioning balancer and a control processing wireless transmitter; the signal transmission is carried out with the operation and processing terminal control device through the control processing wireless transmitter; the track tensioning and expansion measuring device is composed of multiple groups of relative distance sensors, each group of relative distance sensors produces a relative distance change as the track expands and contracts, and the control processing wireless transmitter receives the relative distance change signal to calculate the relative distance change between each section of the track caused by the track expansion and contraction, and calculates the expansion and contraction of the corresponding section of the track; the relative distance change is transmitted to the operation and processing terminal control device through the control processing wireless transmitter; the operation and processing terminal control device calculates the expansion and contraction of the corresponding section of the track for each group of relative distance sensors based on the relative distance change; when the track is in the initial state with no tension and natural length, multiple groups of relative distance sensors are evenly spaced and fitted. Inside the circumferential pad of the track; a wear-resistant rubber protective layer is set on the surface of the track; the wear-resistant rubber protective layer provides wear-resistant and pressure-bearing protection for the track surface and the track tensioning measurement module during the operation of the track; the track expansion and contraction length changes as the tensioning force is adjusted, and the length distance inside the circumferential pad of the track changes; because the upper half-ring track is not under pressure and the lower half-ring track is under pressure, the upper and lower track half-rings are unevenly stressed due to the pressure of the road wheels, resulting in a difference in the expansion and contraction of the upper and lower track parts, causing the upper half-ring track part to produce unstable jumping during the operation of the track, and the lower half-ring track part to produce excessive stretching due to the pressure of the road wheels and the driving force; according to the expansion and contraction of the corresponding track section, the upper and lower track tensioning balancers are controlled by the control processing wireless transmitter to use the elastic force to follow the expansion and contraction balance, and adjust the expansion and contraction difference of the upper and lower track parts; maintain the expansion and contraction balance of the various parts of the track and further enhance the stability of the track during operation.

[0007] Preferably, it also includes: The walking speed determination module is used to determine the corresponding maximum walking speed based on the road environment data detected by the detection module and the set tension force selected by the selection unit.

[0008] Preferably, the road surface environment data includes: road surface topography and road surface properties.

[0009] Preferably, the road surface topography includes: slope, flat road and uneven road; the road surface properties include: hard and soft.

[0010] Preferably, the detection module includes: A first acquisition unit is used to acquire the current road surface image from multiple directions; The recognition unit is used to recognize the road surface image and obtain a road surface recognition image, and obtain road surface material information based on the road surface recognition image; Obtaining pavement material information based on a pavement recognition image includes: extracting pavement material-related image features from the pavement recognition image based on the pavement recognition image; setting a reference pavement model for identifying various pavement materials; collecting various pavement material reference images; extracting various pavement material reference image features from the various pavement material reference images; performing feature comparison between the pavement material-related image features and the various pavement material reference image features; selecting pavement material information corresponding to the pavement material reference image features having the smallest feature comparison difference, and outputting the result as pavement material recognition information, thereby obtaining pavement material information; The classification unit classifies the pavement material according to the pavement material information to obtain the pavement properties.

[0011] Preferably, the detection module further includes: A second acquisition unit is used to acquire the current road surface three-dimensional point cloud from multiple directions; The posture determination unit obtains the current walking posture of the robot body based on the road surface image corresponding to each direction and the walking trajectory of the robot body; The first processing unit is used to process the road surface three-dimensional point cloud corresponding to each direction to obtain the corresponding road surface target point cloud, and then splice the road surface target point clouds corresponding to each direction according to the current walking posture of the robot body to obtain a spliced ​​three-dimensional point cloud of the road surface; The second processing unit obtains the current road topography based on the road surface recognition segmentation image and the road surface splicing three-dimensional point cloud.

[0012] Preferably, the determination of the set tension force includes: Establishing a first relationship model between the maximum contact force of the track under the road wheel of the track transmission mechanism and the track tension under multiple different environments; Establish a second relationship model between track life and track tension under multiple different environments; Under multiple different environments, a third relationship model between the vertical displacement change of the track transmission mechanism and the track tension is established; A multi-objective optimization model for track tension under different environments was established, using track tension as the design variable, the setting range of track tension as the constraint condition, and the first, second, and third relationship models as the objective functions. According to the optimization results of the multi-objective optimization model, the set tension forces corresponding to the multiple different environments are determined.

[0013] Preferably, the multiple different environments are: multiple combinations of different road topography and different road properties.

[0014] Preferably, the adjustment unit includes: An adjusting body, used to be connected to an adjusting wheel, wherein the adjusting wheel is connected to the inner side of the crawler track; The driving part is used to drive the adjustment body to adjust the contact pressure between the adjustment wheel and the crawler.

[0015] Compared with the prior art, the present invention has at least the following beneficial effects: The all-terrain charge tracked robot for monitoring described in the present invention adjusts the tension of the track accordingly according to the road conditions that the robot body passes through, so as to select the appropriate tension to pass through different road surfaces, thereby ensuring the walking speed of the robot body while preventing the track from being separated from the pulley, thereby ensuring the stability of the track transmission mechanism when walking on various road surfaces, and also being able to increase the service life of the track.

[0016] The other advantages, objectives and features of the all-terrain charging crawler robot for monitoring described in the present invention will be reflected in part through the following description, and will also be understood by technicians in this field through research and practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings: Figure 1 This is a schematic structural diagram of the all-terrain charging crawler robot for monitoring according to the present invention; Figure 2 This is a block diagram of the adjustment module in the all-terrain charging crawler robot for monitoring according to the present invention; Figure 3 This is a block diagram of the detection module in the all-terrain charging crawler robot for monitoring according to the present invention; Figure 4 This is a schematic structural diagram of the adjustment unit in the all-terrain charging crawler robot for monitoring according to the present invention; Figure 5 This is a schematic structural diagram of the track tensioning measurement module in the all-terrain charging crawler robot for monitoring described in the present invention. DETAILED DESCRIPTION

[0018] The present invention will be further described in detail below with reference to the accompanying drawings and embodiments so that those skilled in the art can implement the invention with reference to the description.

[0019] It should be understood that terms such as “having”, “including” and “comprising” used herein do not preclude the existence or addition of one or more other elements or combinations thereof.

[0020] like Figure 1As shown, the present invention provides an all-terrain charging crawler robot for monitoring, comprising: A crawler transmission mechanism, used to drive the robot body 10 to walk; The detection module 9 is provided on the robot body 10 and is used to detect road environment data; The adjustment module is used to adjust the tension of the crawler belt 1 on the crawler belt transmission mechanism according to the road environment data detected by the detection module 9.

[0021] The detection module 9 is arranged on the top of the robot body 10. When the robot body 10 is walking, the detection module 9 can obtain the current road environment data in real time; then, the adjustment module adjusts the tension of the crawler 1 accordingly based on the road environment data to adapt to the road surface to be passed; When the robot body 10 is walking, if the tension of the crawler 1 is too low, the contact pressure between the crawler 1 and the ground under the road wheel of the crawler transmission mechanism will increase, and the speed of the robot body 10 will decrease accordingly. In serious cases, the pulley and the crawler 1 will be separated. When the tension of the crawler 1 is too high, the speed of the robot body 10 will increase accordingly. However, when the tension is too high, it is not suitable for passing through complex terrain, which will shorten the life of the crawler 1. Therefore, it is necessary to adjust the tension of the track 1 accordingly according to the road conditions that the robot body 10 passes through, so as to select the appropriate tension to pass through different road surfaces, ensure the walking speed of the robot body 10, and prevent the track 1 from being separated from the pulley, thereby ensuring the stability of the track transmission mechanism when walking on various road surfaces, and also improving the service life of the track 1.

[0022] like Figure 2 As shown, in one embodiment, the adjustment module includes: A selection unit selects a set tension force corresponding to the road environment data detected by the detection module 9; The adjusting unit adjusts the tension of the crawler belt 1 on the crawler belt transmission mechanism to the set tension selected by the selecting unit.

[0023] The set tension is pre-set, and each road environment corresponds to its corresponding set tension. Therefore, the selection unit can directly call the corresponding set tension according to the detected road environment data, and then use the adjustment unit to adjust the tension of the crawler 1 to the corresponding set tension. Through the above technical solution, the robot body 10 can pass through the corresponding road surface with the set tension to ensure its walking speed and walking stability, and ensure the efficiency and stability of the monitoring work; like Figure 5As shown, the track tensioning measurement module detects the tension of the track 1 to adjust the extension and contraction amount, and maintains the balance of the extension and contraction amount of each part of the track 1 and further enhances the stability of the track 1 during operation; The track tensioning measurement module includes: a track tensioning and expansion measuring device 11, an upper and lower track tensioning balancer 12 and a control processing wireless transmitter 13; and the signal transmission with the operation processing terminal control device 14 is carried out through the control processing wireless transmitter 13; the track tensioning and expansion measuring device 11 is composed of multiple groups of relative distance sensors, and each group of relative distance sensors produces a relative distance change as the track 1 expands and contracts. The control processing wireless transmitter 13 receives the relative distance change signal and calculates the relative distance change of each section of the track 1 caused by the expansion and contraction of the track 1, and calculates the expansion and contraction of the corresponding section of the track; the relative distance change is transmitted to the operation processing terminal control device 14 through the control processing wireless transmitter 13; the operation processing terminal control device 14 calculates the expansion and contraction of the corresponding section of the track for each group of relative distance sensors according to the relative distance change; in the initial state, when the track 1 has no tension and natural length, multiple groups of relative distance sensors are evenly spaced and fitted on the track. Inside the circumferential pad 15; a wear-resistant rubber protective layer is provided on the surface of the track 1 (not shown in the figure); the wear-resistant rubber protective layer provides wear-resistant and pressure-bearing protection for the surface of the track 1 and the track tensioning measuring module during the operation of the track 1; the track extension length changes as the tensioning force is adjusted, and the length distance inside the circumferential pad 15 of the track changes; because the upper half-ring track 1 is not under pressure and the lower half-ring track 1 is under pressure, the upper and lower half-rings of the track 1 are unevenly stressed due to the pressure of the road wheel, resulting in a difference in the extension and contraction of each part of the upper and lower track 1, causing the upper half-ring track 1 part to produce unstable jumping during the operation of the track 1, and the lower half-ring track 1 part to produce excessive stretching due to the pressure of the road wheel and the driving force; according to the extension and contraction of the corresponding section of the track, the upper and lower track tensioning balancers 12 are controlled by the control processing wireless transmitter 13 to use the elastic force to follow the extension and contraction balance to adjust the extension and contraction difference of each part of the upper and lower track 1; maintain the extension and contraction balance of each part of the track 1 and further enhance the stability of the track 1 during operation.

[0024] In one embodiment, it further includes: The walking speed determination module is used to determine the corresponding maximum walking speed based on the road environment data detected by the detection module 9 and the set tension force selected by the selection unit.

[0025] When the robot body 10 walks on different roads with different set tensions, each has a corresponding maximum walking speed. For example, when walking on a flat road, there are no obstacles when passing through, and the set tension will be correspondingly larger, so the speed will be correspondingly faster. However, when walking on an uneven road, there are obstacles when passing through, and the track 1 is unevenly stressed. The set tension will be smaller than when walking on a flat road, and the speed will be correspondingly reduced. If the speed is too fast at this time, the track 1 may be separated from the pulley, causing the robot body 10 to be unable to continue walking. Therefore, an upper limit value should be set for the walking speed based on the road environment data and the set tension, that is, the maximum walking speed in this embodiment. When passing through different road surfaces, the robot body 10 will not exceed its maximum walking speed, thereby ensuring its walking stability.

[0026] In one embodiment, the road environment data includes: road topography and road properties.

[0027] The road environment data that affect the walking speed and walking stability of the robot body 10 mainly include road topography and road properties.

[0028] Furthermore, the road surface topography includes: slope, flat and uneven roads; the road surface properties include: hard and soft.

[0029] The road surface terrain includes slopes, such as uphill roads and downhill roads, flat roads, such as flat roads, and uneven roads, such as rugged mountain roads. Of course, the road surface terrain is not limited to the types listed above. Road properties include hard and soft. The classification of hard and soft mainly depends on the degree of sinking when walking on the road, which affects the rollover risk of the robot body 10 when turning. For the rollover risk of different road properties, the corresponding data can be obtained through simulation analysis of the robot walking when other environments are the same (for example, the road terrain is the same, all are flat roads), and then a set value corresponding to the road property is pre-set. Roads with a rollover risk lower than the set value are classified as hard, and roads with a rollover risk higher than the set value are classified as soft.

[0030] like Figure 3 As shown, in one embodiment, the detection module 9 includes: A first acquisition unit is used to acquire the current road surface image from multiple directions; The recognition unit is used to recognize the road surface image and obtain a road surface recognition image, and obtain road surface material information based on the road surface recognition image; The method of obtaining the pavement material information based on the pavement recognition image includes: extracting pavement material-related image features from the pavement recognition image based on the pavement recognition image; setting a reference pavement model for identifying various pavement materials; collecting various pavement material reference images; extracting various pavement material reference image features from the various pavement material reference images; performing feature comparison between the pavement material-related image features and the various pavement material reference image features; selecting the pavement material information corresponding to the pavement material reference image feature having the smallest feature comparison difference as the pavement material recognition information output, thereby obtaining the pavement material information; Among them, identifying the reference road surface model includes: a reference road surface 3D model and a reference road surface physical model; the reference road surface 3D model is simulated by inputting 3D characteristic parameters of various road surface materials into a computer 3D modeling system through 3D modeling; the computer 3D modeling system automatically generates a reference road surface 3D model according to the 3D characteristic parameters of various road surface materials; the 3D characteristic parameters of various road surface materials include: 3D characteristic parameters of hard road surface materials and 3D characteristic parameters of soft road surface materials; the 3D characteristic parameters of hard road surface materials include: hardness of hard road surface materials, particle size of hard road surface materials base material and friction coefficient of hard road surface materials; the 3D characteristic parameters of soft road surface materials include: hardness of hard road surface materials, particle size of hard road surface materials base material and friction coefficient of hard road surface materials; The 3D characteristic parameters of the quality include: the deflection of the soft pavement material, the particle size of the soft pavement material base material and the friction coefficient of the soft pavement material; the hardness of the hard pavement material includes the degree to which the hard pavement material resists local stress deformation; the deflection of the soft pavement material includes the degree to which the soft pavement material bends after being stressed; the particle size of the hard pavement material base material includes: the size range of the particles mixed into the hard pavement material base material and the size range of the exposed part of the particles after the hard pavement material base material solidifies and bonds; the particle size of the soft pavement material base material includes: the size range of the particles mixed into the soft pavement material base material and the size range of the exposed part of the particles after the soft pavement material base material solidifies and bonds; The classification unit classifies the pavement material according to the pavement material information to obtain the pavement properties.

[0031] The recognition unit uses a pre-trained model (such as a deep network model or any trained model in the existing technology that can recognize road surface materials) to identify the material of the road surface image and obtain road surface material information; the classification unit stores classification results corresponding to various road surface materials, and based on the identified road surface material information, the corresponding road surface properties can be obtained.

[0032] like Figure 3 As shown, in one embodiment, the detection module 9 further includes: A second acquisition unit is used to acquire the current road surface three-dimensional point cloud from multiple directions; A posture determination unit obtains the current walking posture of the robot body 10 based on the road surface image corresponding to each direction and the walking trajectory of the robot body 10; Specifically, feature extraction is performed on the road surface image corresponding to each direction, and then the corresponding image feature points are obtained. The position and posture of the detection module 9 can be obtained through the image feature points and the walking trajectory of the robot body 10. Since the detection module 9 is set on the top of the robot body 10, the position and posture obtained by the detection module 9 is the position and posture of the robot body 10. Then, after the position and posture of multiple directions are integrated, the current walking posture of the robot body 10 can be obtained. The first processing unit is used to process the road surface three-dimensional point cloud corresponding to each direction to obtain a corresponding road surface target point cloud, and then splice the road surface target point clouds corresponding to each direction according to the current walking posture of the robot body 10 to obtain a spliced ​​three-dimensional point cloud of the road surface; Semantic segmentation is performed on the road surface image and the road surface 3D point cloud corresponding to each direction respectively to obtain the corresponding image semantics and point cloud semantics, and the two are mapped to obtain the actual semantics of each 3D point cloud. Then, the road surface 3D point cloud can be screened according to the actual semantics of each 3D point cloud to obtain the corresponding road surface target point cloud, which can improve the accuracy of the road surface terrain obtained subsequently; the road surface target point clouds in multiple directions are all converted to the same coordinate system, and then the point cloud feature points are extracted from the road surface target point cloud. The road surface target point cloud in each direction is matched and calibrated according to the point cloud feature points. The corresponding transformation matrix is ​​obtained based on the walking posture of the robot body 10, and the matched and calibrated road surface target point clouds are spliced ​​according to the transformation matrix to obtain a spliced ​​3D point cloud of the road surface; through the first processing unit, the accuracy of road surface terrain detection can be further improved; The second processing unit obtains the current road topography based on the road surface recognition segmentation image and the road surface splicing three-dimensional point cloud; Through the second processing unit, the current three-dimensional road environment can be established by using the road surface recognition segmentation image and the road surface splicing three-dimensional point cloud, which includes the road surface topography and road surface material, providing a more accurate basis for the selection of the set tension of the track 1. The three-dimensional road environment is also beneficial for the robot body 10 to plan the walking path and provide convenience for its walking monitoring; in addition, it can also be remotely transmitted to the terminal control device outside this environment.

[0033] Through the above technical solution, real-time detection of the current road terrain can be achieved, and the accuracy of road terrain detection can be improved, providing a more accurate basis for the selection of the set tension of the track 1, thereby ensuring the walking stability and walking speed of the robot body 10. In addition, the above technical solution can reconstruct the three-dimensional road environment so that operators outside the current environment can observe it, providing monitoring convenience.

[0034] In one embodiment, the determination of the set tension force includes: Establishing a first relationship model between the maximum contact force of the crawler 1 under the road wheel of the crawler transmission mechanism contacting the road surface and the crawler tension force under multiple different environments; Establish a second relationship model between track life and track tension under multiple different environments; Under multiple different environments, a third relationship model between the vertical displacement change of the track transmission mechanism and the track tension is established; A multi-objective optimization model for track tension under different environments was established, using track tension as the design variable, the setting range of track tension as the constraint condition, and the first, second, and third relationship models as the objective functions. According to the optimization results of the multi-objective optimization model, the set tension forces corresponding to the multiple different environments are determined.

[0035] Furthermore, the multiple different environments are: multiple combinations of different road topography and different road properties.

[0036] The independent variables in the first, second, and third relationship models are all track tension. Each of the first, second, and third relationship models can employ a neural network model, with track tension (the independent variable) and other relevant key parameters serving as model inputs, and the maximum contact force of the track 1 below the road wheel contacting the road surface, the track life, and the vertical displacement change of the track transmission mechanism (indicating vibration of the track transmission mechanism) serving as model outputs. This allows for the establishment of a relationship model between track tension and the aforementioned three factors. The optimization objectives of the multi-objective optimization model are to minimize the maximum contact force of the track 1 under the road wheel contacting the road surface, maximize the track life, and minimize the displacement change of the track transmission mechanism in the vertical direction; the NSGA-Ⅱ algorithm can be used to optimize the multi-objective optimization model to obtain the optimal tensioning force corresponding to multiple different environments, that is, the set tensioning force, so that the track transmission mechanism can drive the robot body 10 to walk with the optimal tensioning force under any road terrain and road properties, and can ensure its walking stability and walking speed. Especially in emergency situations, it can ensure the walking speed while ensuring the walking stability of the track transmission mechanism, prevent the robot body 10 from rolling over, the track 1 and the pulley from detaching, and other accidents, thereby improving the stability of monitoring work.

[0037] like Figure 4 As shown, in one embodiment, the adjustment unit includes: An adjusting body, used to be connected to the adjusting wheel 2, wherein the adjusting wheel 2 is connected to the inner side of the crawler track 1; The driving unit 3 is used to drive the adjustment body to adjust the contact pressure between the adjustment wheel 2 and the crawler 1.

[0038] Furthermore, the adjustment body includes: an adjustment cylinder 5 arranged in the outer shell 4, with an internal thread provided on the inner side thereof; a stud 6 limitedly arranged in the outer shell 4, connected to the internal thread of the adjustment cylinder 5; a connecting member 7, one end of which is slidingly connected to the adjustment cylinder 5, and the other end is connected to the adjustment wheel 2, a spring 8 is provided between the connecting member 7 and the adjustment cylinder 5, and a pressure sensor is provided between the spring 8 and the connecting member 7; the driving part 3 is engaged with the outer side of the adjustment cylinder 5, and is used to drive the adjustment cylinder 5 to move.

[0039] The driving part 3 includes: a worm engaged with the adjusting cylinder 5, and a driving body for driving the worm to rotate; The housing 4 limits the stud 6 in radial and axial directions so that the position of the stud 6 remains fixed; the connecting member 7 is rotatably connected to the shaft of the adjusting wheel 2 through a bearing; The portion where the adjusting cylinder 5 is connected to the spring 8 is provided with a rotating member, so that the spring 8 can be rotatably connected to the adjusting cylinder 5 .

[0040] When the tensioning force needs to be adjusted, the adjusting cylinder 5 is driven to rotate by the driving part 3. Since the stud 6 is limitedly connected to the shell 4, the stud 6 will not rotate synchronously with the adjusting cylinder 5. The adjusting cylinder 5 rotates to move it toward or away from the adjusting wheel 2, so that the compression of the spring 8 increases or decreases, and the force exerted by the adjusting wheel 2 on the track 1 increases or decreases. Then, the pressure value detected by the pressure sensor can be used to know the magnitude of the force exerted by the adjusting wheel 2 on the track 1, thereby achieving precise adjustment of the tensioning force; the stud 6 can improve the adjustment accuracy and stability of the adjusting cylinder 5.

[0041] By utilizing the above-mentioned adjustment unit, it is possible to achieve precise adjustment of the tension of the crawler track 1 , thereby ensuring the stability and speed of the robot body 10 when walking.

[0042] In the description of the present invention, it should be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", "clockwise", "counterclockwise", "axial", "radial", "circumferential" and the like to indicate orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as limiting the present invention.

[0043] In the present invention, unless otherwise specified or limited, the terms "installed," "connected," "connect," "fixed," etc. should be understood in a broad sense. For example, they can refer to fixed connection, detachable connection, or integration; mechanical connection, electrical connection, or communication; direct connection or indirect connection through an intermediate medium; internal communication between two elements or interaction between two elements, unless otherwise specified. Those skilled in the art will understand the specific meanings of the above terms in the present invention based on specific circumstances.

[0044] Although the embodiments of the present invention have been disclosed above, they are not limited to the applications listed in the description and implementation methods. They can be fully applied to various fields suitable for the present invention. For those familiar with this field, additional modifications can be easily implemented. Therefore, without departing from the general concept defined by the present invention, the present invention is not limited to the specific details and illustrations shown and described herein.

Claims

1. An all-terrain charging crawler robot for monitoring, characterized in that: include: The crawler transmission mechanism is used to drive the robot body to walk; A detection module, which is arranged on the robot body and is used to detect road environment data; An adjustment module, used to adjust the tension of the crawler track on the crawler track transmission mechanism according to the road environment data detected by the detection module; The road surface environment data includes: road surface topography and road surface properties.

2. The all-terrain charging crawler robot for monitoring according to claim 1, characterized in that: The adjustment module comprises: A selection unit selects a set tension force corresponding to the road environment data detected by the detection module; The adjusting unit adjusts the tension of the crawler belt on the crawler belt transmission mechanism to the set tension selected by the selecting unit.

3. The all-terrain charging crawler robot for monitoring according to claim 2, characterized in that: Also includes: The walking speed determination module is used to determine the corresponding maximum walking speed according to the road environment data detected by the detection module and the set tension force selected by the selection unit.

4. The all-terrain charging crawler robot for monitoring according to claim 2, characterized in that: The road surface topography includes: slope road, flat road and uneven road; the road surface properties include: hard and soft.

5. The all-terrain charging crawler robot for monitoring according to claim 2, characterized in that: The detection module comprises: A first acquisition unit, used to acquire the current road surface image from multiple directions; The recognition unit is used to recognize the road surface image and obtain the road surface recognition image, and obtain the road surface material information according to the road surface recognition image; The classification unit classifies the pavement material according to the pavement material information to obtain the pavement properties.

6. The all-terrain charging crawler robot for monitoring according to claim 5, characterized in that: The detection module also includes: A second acquisition unit is used to acquire the current road surface three-dimensional point cloud from multiple directions; The posture determination unit obtains the current walking posture of the robot body according to the road surface image corresponding to each direction and the walking trajectory of the robot body; The first processing unit is used to process the road surface three-dimensional point cloud corresponding to each direction to obtain the corresponding road surface target point cloud, and then splice the road surface target point clouds corresponding to each direction according to the walking posture of the current robot body to obtain the road surface spliced ​​three-dimensional point cloud; The second processing unit obtains the current road topography based on the road surface recognition segmentation image and the road surface splicing three-dimensional point cloud.

7. The all-terrain charging crawler robot for monitoring according to claim 2, characterized in that: The determination of the set tension force includes: A first relationship model between the maximum contact force of the track under the road wheel of the track transmission mechanism and the track tension force is established under multiple different environments; A second relationship model between track life and track tension is established under multiple different environments; Under multiple different environments, a third relationship model between the displacement variation of the track transmission mechanism in the vertical direction and the track tension force is established; Taking the track tension as the design variable, the setting range of the track tension as the constraint condition, and the first relationship model, the second relationship model and the third relationship model as the objective function, a multi-objective optimization model of the track tension under multiple different environments is established; According to the optimization result of the multi-objective optimization model, the set tension forces corresponding to the multiple different environments are determined.

8. The all-terrain charging crawler robot for monitoring according to claim 7, characterized in that: The multiple different environments are: various combinations of different road topography and different road properties.

9. The all-terrain charging crawler robot for monitoring according to claim 2, characterized in that: The adjustment unit comprises: An adjustment body, used to be connected to an adjustment wheel, wherein the adjustment wheel is connected to the inner side of the crawler track; The driving part is used to drive the adjustment body to move so as to adjust the contact pressure between the adjustment wheel and the crawler track.

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