Traveling method of four-wheel-rotation four-wheel-drive robot

Abstract

The invention discloses a four-turn four-wheel-drive robot driving method which comprises the following steps that driving information of a robot is planned according to a starting point and a target point, the driving information comprises a driving path and a driving mode, the driving path comprises a basic path, a large-angle path or a narrow path, the driving mode corresponding to the basic path is an Ackerman driving mode, and the driving mode corresponding to the wide-angle path is a narrow path; the driving mode corresponding to the large-angle path is a self-rotating mode and an Ackerman mode, and the driving mode corresponding to the narrow path is a combination of at least two of an oblique moving driving mode, a transverse moving driving mode, a self-rotating driving mode, a straight driving mode and an Ackerman driving mode; and controlling the robot to drive from the starting point to the target point along the driving path in the corresponding driving mode. According to the technical scheme, dynamic multi-mode cooperative control is adopted, the Ackerman mode, the transverse moving mode, the spinning mode and the like are automatically switched according to the scene requirement, adaptation of the motion mode and the environment requirement is achieved, and the environment adaptability and the operation efficiency of the four-rotation four-drive robot are remarkably improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of four-wheel four-drive robot driving technology, and particularly relates to a four-wheel four-drive robot driving method. BACKGROUND

[0002] The four-wheel four-drive robot refers to an omnidirectional mobile robot with four independent drive wheels, and each wheel can independently control the steering angle and driving speed. In the actual path planning and control process of the existing four-wheel four-drive robot, there is still a significant technical bottleneck: the mismatch between the motion mode and the path characteristics. SUMMARY

[0003] Therefore, it is necessary to provide a four-wheel four-drive robot driving method to solve the mismatch between the motion mode and the path characteristics.

[0004] To achieve the above-mentioned purpose, the inventor provides a four-wheel four-drive robot driving method, which includes the following steps:

[0005] The driving information of the robot is planned according to the starting point and the target point, the driving information includes a driving path and a driving mode, the driving path includes a basic path, a large-angle path or a narrow path, the basic path corresponds to an Ackermann driving mode, the large-angle path corresponds to a self-rotation mode and an Ackermann mode, and the narrow path corresponds to a combination of at least two of the following driving modes: oblique movement driving mode, transverse movement driving mode, self-rotation driving mode, straight movement driving mode and Ackermann driving mode.

[0006] The robot is controlled to drive from the starting point to the target point along the driving path in the corresponding driving mode.

[0007] Further, the following steps are included:

[0008] It is judged whether there is an obstacle with a moving speed above a speed threshold value within a preset distance in front of the robot, and if so, the robot is switched to a double-Ackermann driving mode to avoid the obstacle.

[0009] Further, the preset distance is 2m, and the speed threshold value is 1.5m / s.

[0010] Further, the following steps are included:

[0011] When the robot drives in the Ackermann mode, the time cost value, the energy cost value, the path deviation cost value and the safety cost value are obtained.

[0012] It is judged whether the safety cost value is greater than the sum of the time cost value and the energy cost value, and the path deviation cost value, and if so, the robot is detoured or braked to avoid the obstacle.

[0013] whether the sum of the time cost value and the energy cost value is greater than the path deviation cost value, the safety cost value, and if so, increasing the travel speed of the robot;

[0014] whether the path deviation cost value is greater than the sum of the time cost value and the energy cost value, the time cost value, and if so, the robot corrects the lateral error to return to the preset travel path;

[0015] wherein:

[0016] the time cost value j1 is obtained by the following formula:

[0017] j1 = w1 * T

[0018] T = t / t m

[0019] wherein, T is the time cost, w1 is the weight corresponding to the time cost, t is the action time consumption, t m is the maximum set consumption;

[0020] the energy cost value j2 is obtained by the following formula:

[0021] j2 = w2 * E

[0022] E = α * ∫P m dt + β∑|Δθ|

[0023] wherein, E is the energy cost, w2 is the weight corresponding to the energy cost, P m is the motor power, Δθ is the steering angle change, α, β are the weight coefficients of energy consumption and steering, and α + β = 1;

[0024] the path cost value j3 is obtained by the following formula:

[0025] j3 = w3 * D

[0026]

[0027] wherein, D is the path cost, w3 is the weight corresponding to the path cost, P act is the actual path point, P ref is the preset path point, and N is the number of sampling points;

[0028] the safety cost value j4 is obtained by the following formula:

[0029] j4 = w4 * S

[0030]

[0031] wherein, w4 is the weight corresponding to the safety cost, dk is the distance between the robot and the kth obstacle, and λ is the attenuation coefficient;

[0032] and w1+w2+w3+w4=1.

[0033] Further, when the robot is to avoid the obstacle by turning around, or by emergency braking, or by double Ackerman mode, the turning around, or the emergency braking, or the double Ackerman mode is selected according to the relationship between the moving speed V2 of the obstacle and the moving speed VI of the robot;

[0034] If V2<5 / 15*VI, the robot turns around to avoid the obstacle;

[0035] If 5 / 15*VI<V2<9 / 15*VI, the robot switches to the double Ackerman mode to avoid the obstacle;

[0036] If V2>9 / 15*VI, the robot emergency brakes to avoid the obstacle.

[0037] Further, the method further comprises the following steps:

[0038] determining whether the distance between the robot and the target point is less than a distance threshold, and if so, controlling the robot to move from the current point to the target point in the Ackerman mode, and to rotate the robot to a preset orientation in the self-rotation mode when approaching the target point.

[0039] Further, the distance threshold is 1.5 m.

[0040] Further, the narrow path comprises a lightning-shaped path, and the corresponding driving mode of the lightning-shaped path is a combination of the diagonal driving mode and the lateral driving mode;

[0041] When the robot is controlled to move from the starting point to the target point along the driving path in the corresponding driving mode, the method further comprises the following steps:

[0042] controlling the robot to move from the starting point to the target point along the driving path in the diagonal driving mode or the lateral driving mode.

[0043] Further, the narrow path comprises an omega-shaped path, and the corresponding driving mode of the omega-shaped path is a combination of the self-rotation driving mode and the Ackerman driving mode;

[0044] When the robot is controlled to move from the starting point to the target point along the driving path in the corresponding driving mode, the method further comprises the following steps:

[0045] controlling the robot to move from the starting point to the target point along the driving path in the self-rotation driving mode or the Ackerman driving mode.

[0046] Further, the narrow path comprises a convex path, and the corresponding driving mode of the convex path is a combination of the lateral driving mode and the straight driving mode;

[0047] When the robot is controlled to move from the starting point to the target point along the driving path in the corresponding driving mode, the method further comprises the following steps:

[0048] The robot is controlled to drive from a starting point to a target point along a driving path in a lateral driving mode or a straight driving mode.

[0049] Compared with the prior art, the above technical solution adopts dynamic multi-mode cooperative control, automatically switches the Ackerman mode, lateral movement mode, self-rotation mode and the like according to the scene requirements, realizes the adaptation of the movement mode to the environmental requirements, and significantly improves the environmental adaptability and operation efficiency of the four-wheel four-drive robot.

[0050] The above invention content related records are only summaries of the technical solutions of the present application. In order to enable those skilled in the art to more clearly understand the technical solutions of the present application, and then can be implemented according to the content recorded in the specification and drawings, and in order to let the above-mentioned purposes and other purposes, characteristics and advantages of the present application can be more easily understood, the following is described in combination with the specific embodiments of the present application and the drawings. BRIEF DESCRIPTION OF DRAWINGS

[0051] The accompanying drawings are only used to show the principles, implementation modes, applications, characteristics and effects of the specific embodiments of the present application and other related contents, and cannot be considered as limitations of the present application.

[0052] Figure 1 One of the four-wheel four-drive robot driving method flowcharts in the present application;

[0053] Figure 2 The schematic diagram of the lightning-shaped path in the present application;

[0054] Figure 3 The schematic diagram of the omega-shaped path in the present application;

[0055] Figure 4 The schematic diagram of the convex-shaped path in the present application;

[0056] Figure 5 The second four-wheel four-drive robot driving method flowchart in the present application;

[0057] Figure 6 The third four-wheel four-drive robot driving method flowchart in the present application. DETAILED DESCRIPTION

[0058] In order to explain the possible application scenarios, technical principles, specific schemes that can be implemented, and the purposes and effects that can be achieved of the present application in detail, the following will be described in combination with the specific embodiments listed and the accompanying drawings. The embodiments recorded in this paper are only used to more clearly explain the technical solutions of the present application, therefore only as an example, and cannot limit the protection scope of the present application.

[0059] The term "embodiment" is mentioned herein means that the specific features, structures, or characteristics described in connection with the embodiment can be included in at least one embodiment of the present application. The term "embodiment" appearing in various places in the specification does not necessarily refer to the same embodiment, nor does it particularly limit the independence or association between other embodiments. In principle, in the present application, as long as there is no technical contradiction or conflict, the technical features mentioned in each embodiment can be combined in any way to form a corresponding implementable technical solution.

[0060] Unless otherwise defined, the meanings of the technical terms used herein are the same as those commonly understood by those skilled in the art to which the present application belongs; the use of related terms herein is only for the purpose of describing specific embodiments, and is not intended to limit the present application.

[0061] In the description of the present application, the phrase "and / or" is a description of the logical relationship between the objects, which means that there can be three relationships, for example, A and / or B, which means that there are three cases: A exists, B exists, and A and B exist at the same time. In addition, the character " / " herein generally represents that the associated objects before and after are a "or" logical relationship.

[0062] In the present application, the terms such as "first" and "second" are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual quantity, primary and secondary or order relationship between the entities or operations.

[0063] Without more limitations, in the present application, the phrases "include", "contain", "have" or other similar expressions used in the sentence are intended to cover non-exclusive inclusion, and these expressions do not exclude the presence of other elements in the process, method or product including the described elements, so that the process, method or product including a series of elements can not only include those limited elements, but also include other elements not explicitly listed, or also include the elements inherent to such process, method or product.

[0064] As the same as the understanding in the "Guidelines for Examination", in the present application, the expressions "greater than", "less than", "exceed" and the like are understood as not including the number; the expressions "above", "below", "within" and the like are understood as including the number. In addition, in the description of the embodiments of the present application, the meaning of "multiple" is more than two (including two), and similar expressions related to "multiple" are also understood in this way, for example, "multiple groups", "multiple times" and the like, unless otherwise explicitly limited.

[0065] In the description of the embodiments of the present application, the spatial relative expressions such as "central", "longitudinal", "transverse", "length", "width", "thickness", "upper", "lower", "front", "back", "left", "right", "vertical", "horizontal", "vertical", "top", "bottom", "inner", "outer", "clockwise", "counterclockwise", "axial", "radial", "circumferential", and the like, indicate the orientation or positional relationship shown in the specific embodiments or the drawings, and are only for the convenience of describing the specific embodiments of the present application or for the reader to understand, and do not indicate or imply that the indicated device or component must have a particular position, a particular orientation, or be constructed or operated in a particular orientation, and therefore cannot be understood as a limitation on the embodiments of the present application.

[0066] Unless otherwise expressly specified or limited, the terms "mount", "connect", "connect", "fix", "set", and the like used in the description of the embodiments of the present application should be interpreted broadly. For example, the "connection" can be fixed connection, or detachable connection, or integral setting; it can be mechanical connection, or electrical connection, or communication connection; it can be direct connection, or indirect connection through intermediate medium; it can be the internal communication of two elements or the interaction relationship between two elements. For those skilled in the art to which the present application belongs, the specific meaning of the above terms in the embodiments of the present application can be understood according to the specific circumstances.

[0067] Please refer to Figures 1 to 6 The present embodiment provides a four-wheel four-drive robot driving method, comprising the following steps:

[0068] Step S101, the driving information of the robot is planned according to the starting point and the target point, the driving information includes the driving path and the driving mode, the driving path includes the basic path, the large-angle path or the narrow path, the basic path corresponds to the Ackermann driving mode, the large-angle path corresponds to the self-rotation mode and the Ackermann mode, and the narrow path corresponds to the combination of at least two of the oblique moving driving mode, the transverse moving driving mode, the self-rotation driving mode, the straight moving driving mode and the Ackermann driving mode;

[0069] Step S102, controlling the robot to drive from the starting point to the target point along the driving path in its corresponding driving mode.

[0070] Please refer to Figure 2 In some embodiments, the narrow path includes a lightning-shaped path, and the lightning-shaped path corresponds to the combination of the oblique moving driving mode and the transverse moving driving mode;

[0071] When the robot is controlled to drive from the starting point to the target point along the driving path in its corresponding driving mode, the following steps are further included:

[0072] The robot is controlled to travel from a starting point to a target point along a travel path in a diagonal travel mode or a lateral travel mode.

[0073] The robot needs to travel from a starting point A to a target point B, passing through a narrow channel in a "lightning shape" as shown. Figure 2 It should be noted that the path can be identified by map information or a perception system such as a laser radar. Due to the limited width of the channel, the traditional Ackermann travel mode cannot pass through smoothly. Therefore, the combination strategy of the diagonal travel mode and the lateral travel mode is adopted to realize the passing. When the path angle is acute, the diagonal travel is used on the path, and the self-rotation is used at the corner; when the path angle is greater than 140 degrees, the diagonal travel is directly used to pass through the whole path.

[0074] As an embodiment, in the lightning-shaped path, the robot first enters from the starting segment in the diagonal travel mode, travels to the corner, then switches to the lateral travel mode to pass through the middle turning area, and finally switches back to the diagonal travel mode to continue traveling in the target direction, thereby completing the path passing.

[0075] Please refer to Figure 3 In some embodiments, the narrow path includes an Ω-shaped path, and the corresponding travel mode is a combination of the self-rotation travel mode and the Ackermann travel mode.

[0076] When the robot is controlled to travel from a starting point to a target point along a travel path in its corresponding travel mode, the following steps are further included:

[0077] The robot is controlled to travel from a starting point to a target point along a travel path in a self-rotation travel mode or an Ackermann travel mode.

[0078] The robot rotates at the corner and uses the Ackermann mode on the middle path segment (the curvature is greater than a certain value combined with the self-rotation mode, which can be calculated by the maximum steering angle of the vehicle Ackermann mode, the wheelbase, and the track). It should be noted that in the Ackermann travel mode, the robot can realize left turn, right turn, and straight motion by front wheel steering.

[0079] When entering the circular arc path segment of the Ω-shaped path, the robot switches to the self-rotation travel mode to rotate in place to quickly adjust the vehicle attitude so that its direction is aligned with the direction of the entrance of the circular arc path segment. Then, the robot switches to the Ackermann travel mode to smoothly travel along the arc-shaped path to realize continuous turning. When approaching the exit of the arc-shaped path, the robot switches back to the self-rotation travel mode to accurately adjust the vehicle direction so that it is consistent with the direction of the exit path segment. After completing the attitude correction, the robot reenters the Ackermann travel mode to continue traveling along the target path to the end point.

[0080] Please refer to Figure 4In some embodiments, the narrow path comprises a convex path, and the corresponding driving mode is a combination of the lateral driving mode and the straight driving mode.

[0081] When the robot is controlled to drive from the starting point to the target point along the driving path in its corresponding driving mode, the method further comprises the following steps:

[0082] The robot is controlled to drive from the starting point to the target point along the driving path in the lateral driving mode or the straight driving mode.

[0083] The robot drives from the starting point along the main path in the straight driving mode, and switches to the lateral driving mode when encountering a right-angle corner. At this time, the four wheels are uniformly turned by 90° (relative to the forward direction of the vehicle body), realizing lateral translation. When encountering a right-angle corner, the robot switches to the straight driving mode.

[0084] In some embodiments, the corner parameter of the Ackermann mode is calculated according to the wheelbase and the track of the vehicle, for example, the relationship formula between the front wheel corner and the path curvature is as follows:

[0085] δ = arctan ((L * k) / (1-d / 2 * k))

[0086] In the formula, L is the wheelbase, d is the track, and k is the path curvature.

[0087] Generally, the Ackermann mode has a maximum corner limit: for example, the Ackermann maximum steering angle is set to ±30°, and when it is exceeded, the self-rotation driving mode is triggered.

[0088] In some embodiments, the angular velocity of the self-rotation driving mode is designed according to the target angle difference (such as [-π, π]) PID control law, for example:

[0089] w = Kp * deltaθ + Kd * d(deltaθ) / dt

[0090] In the formula, deltaθ is the current and target orientation difference.

[0091] Generally, when the robot is in the self-rotation driving mode, the angle difference is less than ±10°, and the Ackermann driving mode is switched back.

[0092] In some embodiments, the maximum corner of the diagonal driving mode can be set to 45 degrees, and the lateral mode is equivalent to a corner of 90 degrees. When diagonal moving in a narrow space, the corner is dynamically adjusted according to the channel width. If diagonal moving cannot pass, it can be determined whether it can pass through straight / horizontal moving after rotating.

[0093] In some embodiments, the partial straight path can directly use the straight driving mode to reduce the amount of calculation; if the obstacle is close to a certain distance (related to the vehicle, about 3 times the length of the vehicle), the Ackermann driving mode is switched.

[0094] Please refer to Figure 5 In some embodiments, when the robot is controlled to drive from the starting point to the target point along the driving path in its corresponding driving mode, the driving method further comprises the following steps:

[0095] Step S201, determine whether there is an obstacle with a moving speed above a speed threshold within a preset distance in front of the robot, if yes, go to step S202, switch to the double Ackermann driving mode to avoid the obstacle, if no, go to step S203, keep unchanged.

[0096] Active avoidance measures are taken for high-speed moving obstacles (such as pedestrians passing by). In the double Ackermann driving mode, the front and rear wheel groups of the robot have opposite steering angles, with the maximum turning angle, forming a transient rotation center close to the middle of the vehicle body, quickly deviating from the path.

[0097] It should be noted that the preset distance and the speed threshold are configurable parameters, and their specific values can be adjusted according to the robot operating environment, safety level and task requirements. For example, the preset distance can be set to 1.5m, 2.0m, 3.0m or 5.0m; the speed threshold can be set to 0.8m / s, 1.2m / s, 1.5m / s or 2.0m / s. Those skilled in the art can select appropriate parameter combinations according to actual applications, which should all fall within the protection scope of the present application.

[0098] Preferably, the preset distance is 2m and the speed threshold is 1.5m / s. The robot is driving along the planned path in the Ackermann mode. The laser radar carried by it continuously monitors the environmental state within 2 meters in front. This detection range covers the minimum safety distance required for emergency braking or avoidance of the robot, ensuring sufficient reaction time. When the system detects a rapidly walking staff 1.8 meters in front, whose moving speed is determined to be 1.6m / s after multiple frame data analysis, exceeding the preset speed threshold of 1.5m / s, the system immediately determines that the target is a "high-speed moving obstacle", triggering the obstacle avoidance mechanism.

[0099] In some embodiments, the driving method further comprises the following steps:

[0100] When the robot is driving in the Ackermann mode, the time cost value, the energy cost value, the path deviation cost value, and the safety cost value are obtained;

[0101] Determine whether the safety cost value is greater than the sum of the time cost value and the energy cost value, and the path deviation cost value, which represents that the safety deviation cost value accounts for the largest proportion, if yes, the robot detours or brakes urgently to avoid the obstacle;

[0102] determining whether the sum of the time cost value and the energy cost value is greater than the path deviation cost value, with the safety cost value, representing the proportion of the sum of the time cost value and the energy cost value being the largest, if yes, increasing the driving speed of the robot, or maintaining high-speed driving, and allowing slight path deviation;

[0103] determining whether the path deviation cost value is greater than the sum of the time cost value and the energy cost value, with the time cost value, representing the proportion of the path deviation cost value being the largest, if yes, the robot corrects the lateral error to return to the preset driving path;

[0104] wherein:

[0105] The time cost value j1 is obtained by the following formula:

[0106] j1 = w1 * T

[0107] T = t / t m

[0108] In the formula, T is the time cost, w1 is the weight corresponding to the time cost, t is the action time, t m is the maximum set time;

[0109] The energy cost value j2 is obtained by the following formula:

[0110] j2 = w2 * E

[0111] E = a * ∫P m dt + b * ∑|Δθ|

[0112] In the formula, E is the energy cost, w2 is the weight corresponding to the energy cost, P m is the motor power, Δθ is the steering angle change, a, b are the weight coefficients of energy and steering, and a + b = 1;

[0113] The path cost value j3 is obtained by the following formula:

[0114] j3 = w3 * D

[0115]

[0116] In the formula, D is the path cost (path deviation), w3 is the weight corresponding to the path cost, P act is the actual path point, P ref is the preset path point, and N is the number of sampling points;

[0117] The safety cost value j4 is obtained by the following formula:

[0118] j4 = w4 * S

[0119]

[0120] In the formula, w4 is the weight corresponding to the safety cost, dk is the distance between the robot and the kth obstacle, and λ is the attenuation coefficient, such as λ = 2.0, and the closer the distance, the higher the cost;

[0121] And w1 + w2 + w3 + w4 = 1.

[0122] In complex road conditions, the total sum of the time cost value and the energy consumption cost value, the path deviation cost value, and the safety cost value are used to assist decision-making. Based on the priority judgment result, a low-cost driving strategy is automatically selected, such as detouring to avoid obstacles, accelerating driving, or correcting the path, which can flexibly cope with complex working conditions.

[0123] The first embodiment is listed here. The robot detects an obstacle at a position with a distance d = 0.05 m (d safe = 1.0 m) in front, the maximum set time t m is 10 s, the action time t = 2 s, the motor power integral ∫Pdt = 0.8 (normalized value), the steering angle change difference ∑|Δθ| = 0.3, the path deviation D = 0.02, w1 = 0.1, w2 = 0.05, w3 = 0.15, w4 = 0.7, the time cost T = 2 / 10 = 0.2, the time cost value j1 = 0.2*0.1 = 0.02, the energy consumption cost E = 0.7*0.8 + 0.3*0.3 = 0.65, the energy consumption cost value j2 = 0.65*0.05 = 0.0325, the path cost D = 0.02, the path cost value j3 = 0.02*0.15 = 0.003, the safety cost S = exp(-2.0·0.5) = exp(-1) ≈ 0.37, and the safety cost value j4 = 0.37*0.7 = 0.259.

[0124] At this time, the safety cost value j4 is the largest, and the proportion in the total cost value is the largest. The robot preferentially performs obstacle avoidance actions (such as emergency braking or detouring), and ignores the path deviation and energy consumption.

[0125] In some embodiments, the weights of w1, w2, w3, and w4 can be adjusted according to the driving path.

[0126] Example two: when there is no obstacle and the accuracy is prioritized, the weight of w3 can be increased, for example, w1 = 0.2, w2 = 0.1, w3 = 0.6, w4 = 0.1, the maximum set time t mFor 10s, action time t = 6s, energy consumption cost E = 0.2, path deviation D = 0.5, time cost T = 6 / 10 = 0.6, safety cost S = 0 (no obstacle), time cost value j1 = 0.6 * 0.2 = 0.12, energy consumption cost value j2 = 0.2 * 0.1 = 0.02, path cost value j3 = 0.5 * 0.6 = 0.3, safety cost value j4 = 0, the path cost value j3 is the largest, which occupies the largest proportion in the total cost value, the robot path deviation weight dominates, and the system prioritizes correcting the lateral error (such as adjusting the steering wheel angle).

[0127] Example three: when on an open highway, the target is to reach the target point in a short time, the weight of w1 can be increased, for example, w1 = 0.4, w2 = 0.3, w3 = 0.2, w4 = 0.1, the maximum set time t m For 20s, action time t = 5s, energy consumption cost E = 0.6, path deviation D = 0.03, distance d = 5m from the nearest obstacle, safety cost S = exp(-2*5) ≈ 0, time cost T = 5 / 20 = 0.25, time cost value j1 = 0.25 * 0.4 = 0.1, energy consumption cost value j2 = 0.6 * 0.3 = 0.18, path cost value j3 = 0.03 * 0.2 = 0.006, safety cost value j4 = 0, the sum of time cost value j1 and energy consumption cost value j2 is the largest, which occupies the largest proportion in the total cost value, that is, time and energy consumption jointly dominate, the robot chooses to accelerate or maintain high-speed driving, allowing slight path deviation.

[0128] Example four: when the robot detects an obstacle moving at a speed above the speed threshold within a preset distance in front, the weight of w4 can be increased, and the robot immediately slows down and detours, sacrificing time and energy consumption.

[0129] In some embodiments, when the robot detours or brakes suddenly or switches to the double Ackerman mode to avoid obstacles, the detouring or sudden braking or double Ackerman mode is selected according to the relationship between the moving speed V2 of the obstacle and the moving speed V1 of the robot;

[0130] If V2 < 5 / 15 * V1, the robot detours to avoid the obstacle;

[0131] If 5 / 15 * V1 < V2 < 9 / 15 * V1, the robot switches to the double Ackerman mode to avoid the obstacle;

[0132] If V2 > 9 / 15 * V1, the robot brakes suddenly to avoid the obstacle.

[0133] When the robot needs to detour, brake suddenly, or switch to the double Ackerman mode to avoid obstacles, the system automatically selects the most appropriate avoidance strategy according to the relationship between the moving speed V2 of the obstacle and the moving speed V1 of the robot.

[0134] In some embodiments, the driving method further comprises the following steps:

[0135] If the distance between the robot and the target point is less than the distance threshold, the robot drives from the current point to the target point in the Ackermann mode, and rotates the robot to the preset orientation in the self-rotation mode when approaching the target point.

[0136] The distance threshold is a parameter that can be flexibly set according to the type of robot, task requirements, and environmental conditions. Its value can be 0.5m, 1.0m, 1.5m, or 2.0m. Preferably, the distance threshold is 1.5m. When the Euclidean distance between the robot and the target point reaches 1.5 meters, the robot calculates the direction from the current point to the target point (i.e., the path direction) and compares it with the current orientation of the vehicle to obtain an angle difference. Based on the angle difference, the required steering angle of the robot is determined to adjust the driving direction. During the approach to the target point, when the distance between the robot and the target point is reduced to a preset small range (e.g., less than 0.05 meters), the system again compares the expected orientation of the target point with the current orientation of the vehicle. At this time, the robot switches to the self-rotation mode and adjusts the orientation of the vehicle by rotating in place until it is consistent with the expected orientation of the target point.

[0137] The common Ackermann mode may need multiple adjustments to achieve a certain accuracy, and by combining the self-rotation and diagonal shift modes, the time for point adjustment can be reduced and the accuracy can be improved.

[0138] Please refer to Figure 6 , Figure 6 The driving method of the four-wheel four-drive robot is shown.

[0139] The driving method of the four-wheel four-drive robot has the following beneficial effects:

[0140] Advantage 1: Dynamic multi-mode collaborative control is adopted, and the Ackermann, lateral shift, and self-rotation modes are automatically switched according to scene requirements, solving the problem of insufficient adaptability of traditional single control mode in complex environments.

[0141] Advantage 2: The dual-Ackermann emergency obstacle avoidance mode is innovatively proposed, which realizes rapid lateral maneuvering through reverse steering of the front and rear wheel groups, significantly improving the obstacle avoidance ability for dynamic obstacles.

[0142] Advantage 3: For angle-turning passages (such as lightning-shaped, Ω-shaped, and convex paths), a multi-mode combined strategy is designed, breaking through the geometric limitations of traditional steering modes and achieving efficient passage.

[0143] Advantage 4: An intelligent priority decision mechanism is introduced, which automatically selects the optimal control strategy when the modes conflict, taking into account efficiency and safety, and avoiding the unreliability of manual intervention.

[0144] The embodiment also provides a computer readable storage medium, which stores a computer program, and the program is executed by a processor to implement the four-wheel four-drive robot driving method according to any one of the preceding embodiments.

[0145] The embodiment also provides a four-wheel four-drive robot, which stores a computer program, and the four-wheel four-drive robot further comprises a processor and a storage medium, the storage medium stores the computer program, and the program is executed by the processor to implement the four-wheel four-drive robot driving method according to any one of the preceding embodiments.

[0146] The processor can be implemented by software, hardware, firmware or a combination thereof, and can use at least one of a circuit, a single or multiple Application Specific Integrated Circuit (ASIC), a Digital Signal Processor (DSP), a Digital Signal Processing Device (DSPD), a Programmable Logic Device (PLD), a Field Programmable Gate Array (FPGA), a Central Processing Unit (CPU), a controller, a microcontroller, and a microprocessor, so that the processor can execute any combination of the four-wheel four-drive robot driving method steps in the embodiments of the present application.

[0147] Finally, it should be noted that the above-mentioned embodiments have been described in the specification and drawings of the present application, but this does not limit the patent protection scope of the present application. Any technical solutions obtained by replacing or modifying the equivalent structure or equivalent process based on the essential concept of the present application, using the content described in the specification and drawings of the present application, and directly or indirectly implementing the technical solutions of the above embodiments in other related technical fields, are all included in the patent protection scope of the present application.

Claims

1. A four-wheel four-drive robot traveling method characterized by comprising: The method comprises the following steps: According to the starting point, the target point plans the driving information of the robot, the driving information includes the driving path and the driving mode, the driving path includes the basic path, the large angle path or the narrow path, the basic path corresponds to the driving mode as Ackermann driving mode, the large angle path corresponds to the driving mode as self-rotation mode and Ackermann mode, the narrow path corresponds to the driving mode as at least two kinds of combination of oblique moving driving mode, transverse moving driving mode, self-rotation driving mode, straight moving driving mode and Ackermann driving mode; Control the robot to drive from the starting point to the target point along the driving path in its corresponding driving mode.

2. The traveling method according to claim 1, characterized by, When controlling the robot to drive from the starting point to the target point along the driving path in its corresponding driving mode, the following steps are further included: Judge whether there is an obstacle with a moving speed above a speed threshold value within a preset distance in front of the robot, if yes, switch to double Ackermann driving mode to avoid the obstacle.

3. The traveling method according to claim 2, characterized by, The preset distance is 2 m, and the speed threshold value is 1.5 m / s.

4. The traveling method according to claim 1, characterized by, When controlling the robot to drive from the starting point to the target point along the driving path in its corresponding driving mode, the following steps are further included: When the robot drives in Ackermann mode, obtain time cost value, energy consumption cost value, path deviation cost value and safety cost value; Judge whether the safety cost value is greater than the sum of the time cost value and the energy consumption cost value, and the path deviation cost value, if yes, the robot detours or brakes suddenly to avoid the obstacle; Judge whether the sum of the time cost value and the energy consumption cost value is greater than the path deviation cost value and the safety cost value, if yes, increase the driving speed of the robot; Judge whether the path deviation cost value is greater than the sum of the time cost value and the energy consumption cost value, and the time cost value, if yes, the robot corrects the lateral error to return to the preset driving path; Wherein: The time cost value j1 is obtained by the following formula: j1 = w1*T T = t / t m In the formula, T is a time cost, w1 is a weight corresponding to the time cost, t is an action time consumption, t m is a maximum set consumption. The energy consumption cost value j2 is obtained by the following formula: j2 = w2*E E = a - P dt + β∑|Δθ| m dt + β∑|Δθ| In the formula, E is an energy consumption cost, w2 is a weight corresponding to the energy consumption cost, P m is a motor power, Δθ is a steering angle change amount, α and β are weight coefficients of energy consumption and steering, and α+β=1. The path cost value j3 is obtained by the following formula: j3 = w3*D In the formula, D is a path cost, w3 is a weight corresponding to the path cost, P act is an actual path point, P ref is a preset path point, and N is a number of sampling points. The safety cost value j4 is obtained by the following formula: j4 = w4*S In the formula, w4 is the weight corresponding to the safety cost, d k is the distance between the robot and the kth obstacle, and λ is the attenuation coefficient. And w1+w2+w3+w4 = 1.

5. The traveling method according to claim 4, characterized by, When the robot detours or brakes suddenly or double Ackermann mode to avoid the obstacle, the detour or braking or double Ackermann mode is selected according to the relationship between the moving speed V2 of the obstacle and the moving speed V1 of the robot; If V2 < 5 / 15*V1, the robot detours to avoid the obstacle; If 5 / 15*V1 < V2 < 9 / 15*V1, the robot switches to double Ackermann mode to avoid the obstacle; If V2 > 9 / 15*V1, the robot brakes suddenly to avoid the obstacle.

6. The traveling method according to claim 1, characterized by, When controlling the robot to drive from the starting point to the target point along the driving path in its corresponding driving mode, the following steps are further included: Judge whether the distance between the robot and the target point is less than a distance threshold value, if yes, the robot drives from the current point to the target point in oblique moving mode, and rotates the robot to a preset orientation in self-rotation mode when approaching the target point.

7. The traveling method according to claim 1, characterized by, The distance threshold value is 1.5 m.

8. The traveling method according to claim 1, characterized by, The narrow path includes lightning-shaped path, and the lightning-shaped path corresponds to the combination of oblique moving driving mode and transverse moving driving mode; When controlling the robot to move from the starting point to the target point along the travel path in its corresponding travel mode, the method further comprises the steps of: controlling the robot to move from the starting point to the target point along the travel path in the diagonal travel mode or the lateral travel mode.

9. The traveling method according to claim 1, characterized by, The narrow path comprises an Ω-shaped path, and the Ω-shaped path corresponds to a combination of the spin travel mode and the Ackermann travel mode; When controlling the robot to move from the starting point to the target point along the travel path in its corresponding travel mode, the method further comprises the steps of: controlling the robot to move from the starting point to the target point along the travel path in the spin travel mode or the Ackermann travel mode.

10. The traveling method according to claim 1, characterized by, The narrow path comprises a convex path, and the convex path corresponds to a combination of the lateral travel and the straight travel mode; When controlling the robot to move from the starting point to the target point along the travel path in its corresponding travel mode, the method further comprises the steps of: controlling the robot to move from the starting point to the target point along the travel path in the lateral travel mode or the straight travel mode.

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