Obstacle avoidance method and apparatus

Abstract

Disclosed in the present invention are an obstacle avoidance method and apparatus. The method comprises: acquiring first image data captured by a camera at a first moment, second image data captured at a second moment, a photographing angle of the camera, and a speed function of a vehicle during the first moment and the second moment; extracting a target obstacle in the first image data to obtain a first contour, and extracting a target obstacle in the second image data to obtain a second contour; determining dimension information of the target obstacles on the basis of the speed function, the photographing angle of the camera, the first contour and the second contour; and controlling the vehicle on the basis of the dimension information of the target obstacles. Thus, obstacle recognition and avoidance can be realized on the basis of currently available software and hardware equipment of vehicles, thereby greatly saving on costs. After road conditions are photographed multiple times, rapid calculation processing is performed by means of an algorithm to obtain the width and height dimensions of an obstacle, and a chassis is used for adjustment in the vertical direction, so as to ensure that the vehicle efficiently and safely passes through the obstacle.

Description

Obstacle avoidance method and device Technical Field

[0001] The present invention relates to the field of vehicle control technology, and in particular to an obstacle avoidance method and device. Background Art

[0002] During driving, vehicles often encounter obstacles falling from the road, which affects driving safety and requires the driver to be distracted to identify and deal with them quickly, which often causes the vehicle to slow down and change direction, thus posing a driving safety hazard to other vehicles.

[0003] Existing solutions for obstacle avoidance typically utilize radar detection technology: radar emits radio waves to calculate distance, identify obstacles, and issue warnings. However, obstacles are often irregular in shape, making radar detection and measurement difficult. Radar can only determine the distance from the vehicle, not the exact height, and the hardware cost is high.

[0004] Summary of the Invention

[0005] In view of the above problems, the present invention is proposed to provide an obstacle avoidance method and device, which can quickly identify the size of the obstacle and adjust the chassis height or perform avoidance measures such as deceleration to avoid scratches on the vehicle chassis and reduce adverse effects on driving safety.

[0006] According to a first aspect of the present invention, there is provided an obstacle avoidance method, comprising:

[0007] Obtaining first image data captured by a camera at a first moment, second image data captured at a second moment, a camera shooting angle, and a speed function of the vehicle between the first moment and the second moment;

[0008] Extracting the target obstacle in the first image data to obtain a first outline; extracting the target obstacle in the second image data to obtain a second outline;

[0009] Determine the size information of the target obstacle according to the speed function, the camera shooting angle, the first outline, and the second outline;

[0010] The vehicle is controlled based on the size information of the target obstacle.

[0011] Optionally, the camera is installed at the opening of the front bumper of the vehicle, the angle between the upper shooting boundary and the lower shooting boundary of the camera is the camera shooting angle, and the upper shooting boundary is set as the horizontal boundary.

[0012] Optionally, determining the size information of the target obstacle according to the speed function, the camera shooting angle, the first profile, and the second profile includes:

[0013] determining a travel distance of the vehicle between a first moment and a second moment based on the speed function;

[0014] Determining upper and lower boundaries and left and right boundaries of the target obstacle in the first image data according to the first contour;

[0015] determining upper and lower boundaries of the target obstacle in the second image data based on the second contour;

[0016] Determine the height of the target obstacle based on the driving distance, the upper and lower boundaries of the target obstacle in the first image data, the upper and lower boundaries of the target obstacle in the second image data, and the camera shooting angle;

[0017] The target obstacle width is determined based on the target obstacle height and the left and right boundaries of the target obstacle in the first image data; the target obstacle height and the target obstacle width constitute the size information of the target obstacle.

[0018] Optionally, determining the height of the target obstacle based on the driving distance, the upper and lower boundaries of the target obstacle in the first image data, the upper and lower boundaries of the target obstacle in the second image data, and the camera shooting angle includes:

[0019] The height of the target obstacle is determined using the following formula based on the driving distance, the upper and lower boundaries of the target obstacle in the first image data, the upper and lower boundaries of the target obstacle in the second image data, and the camera shooting angle:

[0020] h=tgA*ΔL / (ab)

[0021] Where h is the height of the target obstacle, A is the camera shooting angle, ΔL is the driving distance, a is the ratio of the pixel height of the upper and lower boundaries of the target obstacle in the first image data to the total pixel height of the first image data; b is the ratio of the pixel height of the upper and lower boundaries of the target obstacle in the second image data to the total pixel height of the second image data.

[0022] Optionally, the size information of the target obstacle includes the height of the target obstacle and the width of the target obstacle;

[0023] Control the vehicle based on the size of the target obstacle, including:

[0024] comparing the target obstacle height with a first height, the first height being the height of the vehicle suspension relative to the ground when the vehicle suspension is raised to a maximum height;

[0025] If the target obstacle height is less than the first height, the height of the vehicle suspension is adjusted according to the target obstacle height.

[0026] Optionally, the method further includes:

[0027] If the target obstacle height is greater than or equal to the first height, obtaining a vehicle control mode;

[0028] If the vehicle control mode is manual driving mode, the vehicle suspension is controlled to rise to a first height and a prompt message is issued.

[0029] Optionally, after issuing the prompt message, the method further includes:

[0030] Get the target distance between the vehicle and the target obstacle;

[0031] If the target distance is less than the distance threshold, the vehicle is controlled to brake.

[0032] Optionally, the method further includes:

[0033] If the target obstacle height is greater than or equal to the first height, obtaining a vehicle control mode;

[0034] If the vehicle control mode is the automatic driving mode, the target distance between the vehicle and the target obstacle is obtained;

[0035] If the target distance is greater than or equal to the distance threshold, the vehicle speed is controlled within the speed threshold and the path is replanned based on the width of the target obstacle.

[0036] According to a second aspect of the present invention, there is provided an obstacle avoidance device, comprising:

[0037] An acquisition module is configured to acquire first image data captured by a camera at a first moment, second image data captured at a second moment, a camera shooting angle, and a speed function of the vehicle between the first moment and the second moment;

[0038] an extraction module configured to extract the target obstacle in the first image data to obtain a first outline; and extract the target obstacle in the second image data to obtain a second outline;

[0039] a calculation module configured to determine size information of the target obstacle based on the speed function, the camera shooting angle, the first profile, and the second profile;

[0040] The control module is configured to control the vehicle according to the size information of the target obstacle.

[0041] According to a third aspect of the present invention, a controller is provided. The controller includes: a memory, a processor, and a computer program stored in the memory and executable on the processor. The processor executes the aforementioned obstacle avoidance method.

[0042] According to a fourth aspect of the present invention, a vehicle is provided, comprising a vehicle body and a controller installed in the vehicle body, wherein the controller executes the aforementioned obstacle avoidance method.

[0043] The above one or more technical solutions in the embodiments of this specification have at least the following technical effects:

[0044] The embodiments of this specification provide an obstacle avoidance method and device. These methods obtain first image data captured by a camera at a first moment, second image data captured at a second moment, the camera's shooting angle, and a vehicle speed function between the first and second moments; extract the target obstacle from the first image data to obtain a first outline; extract the target obstacle from the second image data to obtain a second outline; determine the size of the target obstacle based on the speed function, the camera's shooting angle, the first outline, and the second outline; and control the vehicle based on the target obstacle's size information. In this way, obstacle recognition and avoidance can be achieved based on existing vehicle hardware and software, significantly reducing costs. By capturing multiple road conditions, an algorithm rapidly calculates and processes the width and height of the obstacle, and the chassis is adjusted vertically to ensure the vehicle can efficiently and safely pass through the obstacle.

[0045] The above description is only an overview of the technical solution of the present invention. In order to more clearly understand the technical means of the present invention, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are specifically listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Various other advantages and benefits will become apparent to those skilled in the art upon reading the detailed description of the preferred embodiment below. The accompanying drawings are for illustration purposes only and are not to be considered as limiting the present invention. Throughout the drawings, the same reference figures denote the same components. In the drawings:

[0047] FIG1 shows a flow chart of an obstacle avoidance method according to an embodiment of the present invention.

[0048] FIG. 2 is a schematic diagram showing imaging within a camera viewfinder in an embodiment of the present invention.

[0049] FIG3 is a schematic diagram showing a vehicle identifying a target obstacle in an embodiment of the present invention.

[0050] Icons: 1-Camera; 2-Front bumper opening; 3-Road surface; 4-Target obstacle; 5-Image data; 6-Obstacle in the image data. DETAILED DESCRIPTION

[0051] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions of the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Generally, the components of the embodiments of the present invention described and shown in the drawings herein can be arranged and designed in various different configurations.

[0052] Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the invention as claimed, but rather merely represents selected embodiments of the present invention. All other embodiments derived by persons of ordinary skill in the art based on the embodiments of the present invention without creative effort are intended to fall within the scope of protection of the present invention.

[0053] It should be noted that similar reference numerals and letters denote similar items in the following drawings, and therefore, once an item is defined in one drawing, it does not need to be further defined or explained in subsequent drawings.

[0054] In the description of the present invention, it should also be noted that, unless otherwise expressly specified or limited, the terms "disposed," "installed," "connected," and "connected" should be understood in a broad sense. For example, they may refer to fixed connections, detachable connections, or integral connections; they may refer to mechanical connections or electrical connections; they may refer to direct connections or indirect connections through an intermediate medium; and they may refer to internal communication between two components. Those skilled in the art will understand the specific meanings of the above terms in the present invention based on the specific circumstances.

[0055] An embodiment of the present invention provides an obstacle avoidance method. Referring to the flowchart shown in FIG1 , the obstacle avoidance method includes steps 101 to 104 .

[0056] Step 101: Obtain first image data captured by a camera at a first moment, second image data captured at a second moment, a camera shooting angle, and a speed function of a vehicle between the first moment and the second moment.

[0057] The obstacle avoidance method of this embodiment is executed by a controller, which is installed in a vehicle. The vehicle also includes a chassis and a vehicle suspension with adjustable height. The camera is installed at the opening of the front bumper of the vehicle, and the opening is located in the middle of the bumper. It should be noted that this embodiment requires some processing of the camera, the purpose of which is to set the upper shooting boundary of the camera to a horizontal boundary. During actual processing, the upper part of the opening can be partially blocked, and the upper shooting boundary of the camera can be made a horizontal boundary through calibration. The angle between the upper shooting boundary and the lower shooting boundary of the camera is the camera shooting angle. In this embodiment, the shooting angle of the camera is known, and as shown in Figure 2, the camera shooting angle is marked as A.

[0058] The vehicle of this embodiment can be an autonomous driving vehicle or a manually driven vehicle, and the specific requirements are determined according to the vehicle driving mode. When the vehicle is driving, the camera on the front bumper will take pictures of the vehicle's route to be driven to obtain image data. The image data taken at the first moment is called the first image data. The image data taken at the second moment is called the second image data. It should be noted that the second moment is later than the first moment, and the second image data taken at the second moment is historical image data compared to the first image data. In addition, the first moment and the second moment can be two adjacent shooting cycles of the camera, or there can be one or more shooting cycles between the first moment and the second moment.

[0059] Step 102: extract the target obstacle in the first image data to obtain a first outline; extract the target obstacle in the second image data to obtain a second outline.

[0060] It should be noted that as a vehicle drives, its camera periodically captures the path it is traveling. There may or may not be obstacles on the road ahead. Specifically, obstacle recognition, or obstacle outline extraction, is performed on the captured image data. If an obstacle outline is extracted, it indicates that there is an obstacle on the road ahead.

[0061] In this embodiment, target obstacles are extracted from the first image data and the second image data, respectively. For example, if a first outline is extracted from the first image data captured at a first moment, and a second outline is extracted from the second image data captured at a second moment, this indicates that an obstacle exists on the road ahead.

[0062] In actual driving, the extracted first contour and the second contour correspond to the same target obstacle. The difference lies in that when the camera captures the target obstacle, the distance between the vehicle and the target obstacle and the shooting time are different.

[0063] The images obtained by shooting with a camera are composed of the same number of pixels. Therefore, it is not difficult to understand that the pixel points of the target obstacle in the first image data and the second image data are different, and the first contour and the second contour extracted are also different.

[0064] During the first contour extraction, existing technologies can be utilized to obtain the contour boundary of the obstacle by extracting image features, including binarizing the pixels in the image based on the difference between the first contour boundary and the road surface, or performing pixel grayscale or brightness processing to obtain the boundary pixel points of the obstacle.

[0065] Step 103: Determine the size information of the target obstacle based on the speed function, the camera shooting angle, the first outline, and the second outline.

[0066] In this embodiment, after obtaining the speed function, camera shooting angle, first profile, and second profile, the size information of the obstacle can be obtained through algorithm processing based on these data. The size information mainly refers to the height and width of the target obstacle.

[0067] Specifically, the algorithm processing steps may include:

[0068] Determine the travel distance of the vehicle between the first moment and the second moment according to the speed function;

[0069] Determining upper and lower boundaries and left and right boundaries of the target obstacle in the first image data according to the first contour;

[0070] determining upper and lower boundaries of the target obstacle in the second image data based on the second contour;

[0071] Determine the height of the target obstacle based on the driving distance, the upper and lower boundaries of the target obstacle in the first image data, the upper and lower boundaries of the target obstacle in the second image data, and the camera shooting angle;

[0072] The target obstacle width is determined based on the height of the obstacle and the left and right boundaries of the target obstacle in the first image data; the target obstacle height and the target obstacle width constitute the size information of the target obstacle.

[0073] The speed function primarily refers to the relationship between speed and time between the first and second moments, allowing calculation of the vehicle's travel distance between them. As you can imagine, the camera periodically captures images of the driving path, with a time lag between captures. During this time lag, if the vehicle continues to travel, it will have traveled a certain distance. This distance causes the target obstacle imaged in the first and second image data to differ.

[0074] In the above steps, the first and second contours have been extracted respectively. Both contours refer to pixel contours. Therefore, the boundary pixel points of the first and second contours can be determined respectively. That is, the upper and lower boundaries and the left and right boundaries of the first contour are determined, and the upper and lower boundaries of the second contour are determined. Among them, when determining the upper and lower boundaries, first determine the topmost pixel point and the bottommost pixel point, and determine the pixel height of the target obstacle based on the topmost pixel point and the bottommost pixel point; similarly, when determining the left and right boundaries, first determine the leftmost pixel point and the rightmost pixel point, and determine the pixel width of the target obstacle based on the leftmost pixel point and the rightmost pixel point. Then, combined with the driving distance, based on the trigonometric function relationship, the height and width of the target obstacle can be calculated.

[0075] Specifically, as shown in Figure 3 , camera 1 captures a target obstacle 4 on the road surface 3 through the front bumper opening 2, generating image data 5. The obstacle 6 in the image data divides the entire image data 5 into three parts: the upper portion of the obstacle, the obstacle, and the lower portion of the obstacle. Based on trigonometric relationships, a right triangle with the position of camera 1 as the vertex is constructed, with the camera 1 at its location as the vertex. The angle between the upper and lower boundaries of camera 1 is the camera angle A. L1 is the distance between camera 1 and obstacle 6 in the image data when the first image data is captured at the first moment. L2 is the distance between camera 1 and obstacle 6 in the image data when the second image data is captured at the second moment. h is the actual height of the target obstacle. H1 is the virtual imaging height when the first image data is captured, and H2 is the virtual imaging height when the second image data is captured. It can be understood that when the camera is capturing, the upper boundary of camera 1 reaches the target obstacle at the first position height, and the lower boundary reaches the target obstacle at the second position height. The difference between the two boundary heights is H1 or H2. Based on the pixels in the first and second image data, the ratio a of H1 to h and the ratio b of H2 to h can be calculated. Here, a is the ratio of the obstacle pixel height to the total pixel height in the first image data; b is the ratio of the obstacle pixel height to the total pixel height in the second image data. Furthermore, based on the speed function, the distance ΔL traveled between the first and second moments can be calculated.

[0076] Therefore, in this embodiment, the height of the obstacle can be determined by the following formula: L2 = b*ΔL / (ab) h = tgA*ΔL / (ab)

[0077] Where h is the height of the target obstacle, A is the camera shooting angle, ΔL is the driving distance, a is the ratio of the pixel height of the upper and lower boundaries of the target obstacle in the first image data to the total pixel height of the first image data; b is the ratio of the pixel height of the upper and lower boundaries of the target obstacle in the second image data to the total pixel height of the second image data.

[0078] Furthermore, the target obstacle width may be determined based on the target obstacle height h and the pixel width of the target obstacle; the target obstacle height and the target obstacle width constitute the size information of the target obstacle.

[0079] To ensure the accuracy of the measured data, multiple groups of photos can be taken and calculated, and then the average value h can be taken.

[0080] Step 104: Control the vehicle according to the target obstacle size information.

[0081] In this embodiment, after obtaining the size information of the target obstacle, the vehicle can be controlled according to the size information of the target obstacle. The control of the vehicle mainly refers to adjusting the height of the vehicle suspension, the vehicle speed and the vehicle's driving path.

[0082] Specifically, controlling the vehicle may include the following steps:

[0083] Comparing the target obstacle height with a first height; the first height being the height of the vehicle suspension relative to the ground when the vehicle suspension is raised to a maximum height;

[0084] If the target obstacle height is less than the first height, the height of the vehicle suspension is adjusted according to the target obstacle height.

[0085] After calculating the target obstacle height, it is compared with the first height to determine whether it exceeds the maximum adjustable height of the vehicle's suspension, i.e., the first height. If the target obstacle height does not exceed the first height, it is possible to directly pass the target obstacle by adjusting the vehicle's suspension. If the decision is made to directly pass the target obstacle, it is also necessary to consider that the width of the target obstacle is less than the vehicle's wheelbase. When adjusting the vehicle's suspension height, the vehicle can be adjusted directly to the first height or slightly higher than the target obstacle height.

[0086] In addition, based on different vehicle control modes, the control strategy when the target obstacle is greater than or equal to the first height should also be considered. In an optional embodiment, if the height of the target obstacle is greater than or equal to the first height, the vehicle control mode is obtained;

[0087] If the vehicle control mode is the automatic driving mode, the target distance between the vehicle and the obstacle is obtained;

[0088] If the target distance is greater than or equal to the distance threshold, the vehicle speed is controlled within the speed threshold and the path is replanned based on the width of the target obstacle.

[0089] Among them, the vehicle control mode of this embodiment belongs to automatic driving. If the height of the target obstacle is greater than or equal to the first height, it means that there may be a risk of scratching the chassis, and you can choose to slow down and detour. Of course, it is also necessary to consider the target distance between the vehicle and the target obstacle. If the target distance is close, it is best to slow down and brake. If the target distance is appropriate, such as the target distance is greater than or equal to the distance threshold, it means that there is enough time to control the vehicle speed within the speed threshold, and then re-plan the path according to the width of the target obstacle. The value of the speed threshold can be set to 10-20km / h or other reasonable ranges, and this embodiment does not limit this.

[0090] In another optional embodiment, if the target obstacle height is greater than or equal to the first height, the vehicle control mode is acquired;

[0091] If the vehicle control mode is manual driving mode, the vehicle suspension is controlled to rise to a first height and a prompt message is issued.

[0092] Furthermore, the target distance between the vehicle and the target obstacle can be obtained;

[0093] If the target distance is less than the distance threshold, the vehicle is controlled to brake.

[0094] In this embodiment, the vehicle control mode is manual driving mode. When the height of the target obstacle is greater than or equal to a first height, there is a risk of chassis scratching, and the target obstacle cannot be passed directly. Therefore, a prompt message is provided to the driver, such as a voice prompt. Furthermore, a target distance between the vehicle and the target obstacle can be obtained and compared with a distance threshold. If the target distance is less than the distance threshold, it indicates that the distance to the target obstacle is relatively close and the driver may not have time to effectively react. In this case, the controller can control the vehicle to brake. If the target distance is greater than or equal to the distance threshold, the controller can wait for the driver to effectively react, such as slowing down to avoid the obstacle.

[0095] In summary, the obstacle avoidance method provided in the embodiments of this specification obtains first image data captured by a camera at a first moment, second image data captured at a second moment, the camera shooting angle, and a function of the vehicle's speed between the first and second moments; extracts the target obstacle from the first image data to obtain a first outline; extracts the target obstacle from the second image data to obtain a second outline; determines the size of the target obstacle based on the speed function, the camera shooting angle, the first outline, and the second outline; and controls the vehicle based on the target obstacle's size information. In this way, obstacle recognition and avoidance can be achieved based on existing vehicle hardware and software, significantly saving costs. By capturing multiple images of the road conditions, an algorithm is used to quickly calculate and process the width and height of the obstacle, and the chassis is adjusted vertically to ensure the vehicle passes the obstacle efficiently and safely.

[0096] Based on the same inventive concept, an embodiment of the present invention further provides an obstacle avoidance device, comprising:

[0097] An acquisition module is configured to acquire first image data captured by a camera at a first moment, second image data captured at a second moment, a camera shooting angle, and a speed function of the vehicle between the first moment and the second moment;

[0098] an extraction module configured to extract the target obstacle in the first image data to obtain a first outline; and extract the target obstacle in the second image data to obtain a second outline;

[0099] a calculation module configured to determine size information of the target obstacle based on the speed function, the camera shooting angle, the first profile, and the second profile;

[0100] The control module is configured to control the vehicle based on the size information of the target obstacle. The camera is installed at the opening of the front bumper of the vehicle, and the angle between the upper and lower shooting boundaries of the camera is the camera shooting angle, and the upper shooting boundary is set as the horizontal boundary.

[0101] In an optional embodiment, the calculation module is further configured to:

[0102] determining a travel distance of the vehicle between a first moment and a second moment based on the speed function;

[0103] Determining upper and lower boundaries and left and right boundaries of the target obstacle in the first image data according to the first contour;

[0104] determining upper and lower boundaries of the target obstacle in the second image data based on the second contour;

[0105] Determine the height of the target obstacle based on the driving distance, the upper and lower boundaries of the target obstacle in the first image data, the upper and lower boundaries of the target obstacle in the second image data, and the camera shooting angle;

[0106] The target obstacle width is determined based on the target obstacle height and the left and right boundaries of the target obstacle in the first image data; the target obstacle height and the target obstacle width constitute the size information of the target obstacle.

[0107] In an optional embodiment, the calculation module is further configured to:

[0108] Based on the driving distance, the upper and lower boundaries of the target obstacle in the first image data, the upper and lower boundaries of the target obstacle in the second image data, and the camera shooting angle, the height of the target obstacle is determined by the following formula: h = tgA*ΔL / (ab)

[0109] Where h is the height of the target obstacle, A is the camera shooting angle, ΔL is the driving distance, a is the ratio of the pixel height of the upper and lower boundaries of the target obstacle in the first image data to the total pixel height of the first image data; b is the ratio of the pixel height of the upper and lower boundaries of the target obstacle in the second image data to the total pixel height of the second image data.

[0110] In an optional embodiment, the control module is further configured to:

[0111] comparing the target obstacle height with a first height, the first height being the height of the vehicle suspension relative to the ground when the vehicle suspension is raised to a maximum height;

[0112] If the target obstacle height is less than the first height, the height of the vehicle suspension is adjusted according to the target obstacle height.

[0113] In an optional embodiment, the control module is further configured to:

[0114] If the target obstacle height is greater than or equal to the first height, obtaining a vehicle control mode;

[0115] If the vehicle control mode is manual driving mode, the vehicle suspension is controlled to rise to a first height and a prompt message is issued.

[0116] In an optional embodiment, the control module is further configured to:

[0117] Get the target distance between the vehicle and the target obstacle;

[0118] If the target distance is less than the distance threshold, the vehicle is controlled to brake.

[0119] In an optional embodiment, the control module is further configured to:

[0120] If the target obstacle height is greater than or equal to the first height, obtaining a vehicle control mode;

[0121] If the vehicle control mode is the automatic driving mode, the target distance between the vehicle and the target obstacle is obtained;

[0122] If the target distance is greater than or equal to the distance threshold, the vehicle speed is controlled within the speed threshold and the path is replanned based on the width of the target obstacle.

[0123] In summary, the obstacle avoidance device provided in the embodiments of this specification obtains first image data captured by a camera at a first moment, second image data captured at a second moment, the camera shooting angle, and the vehicle's speed function between the first and second moments; extracts the target obstacle from the first image data to obtain a first outline; extracts the target obstacle from the second image data to obtain a second outline; determines the size information of the target obstacle based on the speed function, the camera shooting angle, the first outline, and the second outline; and controls the vehicle based on the target obstacle's size information. In this way, obstacle recognition and avoidance can be achieved based on the existing vehicle hardware and software equipment, significantly saving costs. After taking multiple photos of the road conditions, the width and height of the obstacle are quickly calculated and processed using an algorithm, and the chassis is adjusted vertically to ensure that the vehicle passes the obstacle efficiently and safely.

[0124] According to a third aspect of the present invention, a controller is provided, which includes an obstacle avoidance device, a memory, a processor and a communication unit. The memory stores machine-readable instructions executable by the processor. When the controller is running, the processor and the memory communicate through a bus, the processor executes the machine-readable instructions, and executes an obstacle avoidance method.

[0125] The memory, processor, and communication unit components are electrically connected to each other, directly or indirectly, to enable signal transmission or interaction. For example, these components may be electrically connected to each other via one or more communication buses or signal lines. An obstacle avoidance device includes at least one software function module that can be stored in the memory in the form of software or firmware. The processor is configured to execute the executable module stored in the memory (e.g., a software function module or computer program included in the obstacle avoidance device).

[0126] Among them, the memory can be, but is not limited to, random access memory (RAM), read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), etc.

[0127] In some embodiments, the processor is used to perform one or more functions described in this embodiment. In some embodiments, the processor may include one or more processing cores (eg, a single-core processor (S) or a multi-core processor (S)).

[0128] In this embodiment, the memory is configured to store a program, and the processor is configured to execute the program after receiving an execution instruction. The process definition method disclosed in any implementation of this embodiment can be applied to a processor or implemented by a processor.

[0129] The communication unit is configured to establish a communication connection between the controller and other devices through a network, and is configured to send and receive data through the network.

[0130] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working process of the controller described above can refer to the corresponding process in the aforementioned method, and will not be elaborated here.

[0131] According to a fourth aspect of the present invention, a vehicle is provided, comprising a vehicle body, a controller installed in the vehicle body, a chassis, and a vehicle suspension on the chassis, wherein the controller is configured to implement the aforementioned obstacle avoidance method.

[0132] In summary, the embodiments of this specification provide a vehicle that obtains a first image data captured by a camera at a first moment, a second image data captured at a second moment, the camera shooting angle, and a speed function of the vehicle between the first and second moments; extracts the target obstacle from the first image data to obtain a first outline; extracts the target obstacle from the second image data to obtain a second outline; determines the size of the target obstacle based on the speed function, the camera shooting angle, the first outline, and the second outline; and controls the vehicle based on the target obstacle size information. In this way, obstacle recognition and avoidance can be achieved based on the existing vehicle hardware and software equipment, significantly saving costs. By taking multiple photos of the road conditions, an algorithm is used to quickly calculate and process the width and height of the obstacle, and the chassis is adjusted vertically to ensure that the vehicle passes the obstacle efficiently and safely.

[0133] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working process of the controller in the vehicle described above can refer to the corresponding process in the aforementioned method and will not be elaborated here.

[0134] The above are merely various embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. Any modifications or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in the present invention should be included in the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be based on the scope of protection of the claims.

Claims

1. An obstacle avoidance method, characterized in that: include: Acquire first image data taken by the camera at a first moment, second image data taken at a second moment, the camera shooting angle, and a speed function of the vehicle between the first moment and the second moment; Extracting the target obstacle in the first image data to obtain a first contour; Extracting the target obstacle in the second image data to obtain a second contour; Determine and obtain size information of the target obstacle according to the speed function, the camera shooting angle, the first profile, and the second profile; The vehicle is controlled according to the size information of the target obstacle.

2. The method according to claim 1, characterized in that: The camera is installed at the opening of the front bumper of the vehicle, the angle between the upper shooting boundary and the lower shooting boundary of the camera is the camera shooting angle, and the upper shooting boundary is set as a horizontal boundary.

3. The method according to claim 1, characterized in that The determining, according to the speed function, the camera shooting angle, the first profile, and the second profile, to obtain size information of the target obstacle includes: determining a travel distance of the vehicle between a first moment and a second moment according to the speed function; Determine, according to the first contour, upper and lower boundaries and left and right boundaries of the target obstacle in the first image data; Determining upper and lower boundaries of the target obstacle in the second image data according to the second contour; Determine the height of the target obstacle according to the driving distance, the upper and lower boundaries of the target obstacle in the first image data, the upper and lower boundaries of the target obstacle in the second image data, and the camera shooting angle; The target obstacle width is determined according to the target obstacle height and the left and right boundaries of the target obstacle in the first image data; the target obstacle height and the target obstacle width constitute the size information of the target obstacle.

4. The method according to claim 3, characterized in that The determining the height of the target obstacle according to the driving distance, the upper and lower boundaries of the target obstacle in the first image data, the upper and lower boundaries of the target obstacle in the second image data, and the camera shooting angle includes: According to the driving distance, the upper and lower boundaries of the target obstacle in the first image data, the upper and lower boundaries of the target obstacle in the second image data, and the camera shooting angle, the height of the target obstacle is determined by the following formula: h=tgA*ΔL / (ab) Wherein, h is the height of the target obstacle, A is the camera shooting angle, ΔL is the driving distance, a is the ratio of the pixel height of the upper and lower boundaries of the target obstacle in the first image data to the total pixel height of the first image data; b is the ratio of the pixel height of the upper and lower boundaries of the target obstacle in the second image data to the total pixel height of the second image data.

5. The method according to claim 1, characterized in that The size information of the target obstacle includes the height of the target obstacle and the width of the target obstacle; The controlling of the vehicle according to the size information of the target obstacle includes: comparing the target obstacle height with a first height, the first height being the height of the vehicle suspension relative to the ground when the vehicle suspension is raised to a maximum height; If the target obstacle height is less than the first height, the height of the vehicle suspension is adjusted according to the target obstacle height.

6. The method according to claim 5, characterized in that The method further comprises: If the target obstacle height is greater than or equal to the first height, obtaining a vehicle control mode; If the vehicle control mode is a manual driving mode, the vehicle suspension is controlled to rise to the first height and a prompt message is issued.

7. The method according to claim 6, characterized in that After the prompt message is sent, the method further includes: Obtaining a target distance between the vehicle and a target obstacle; If the target distance is less than the distance threshold, the vehicle is controlled to brake.

8. The method according to claim 5, characterized in that The method further comprises: If the target obstacle height is greater than or equal to the first height, obtaining a vehicle control mode; If the vehicle control mode is the automatic driving mode, obtaining a target distance between the vehicle and a target obstacle; If the target distance is greater than or equal to the distance threshold, the vehicle speed is controlled within the speed threshold, and the path is replanned according to the target obstacle width.

9. An obstacle avoidance device, characterized in that: include: An acquisition module is configured to acquire first image data taken by a camera at a first moment, second image data taken at a second moment, a camera shooting angle, and a speed function of the vehicle between the first moment and the second moment; an extraction module, configured to extract the target obstacle in the first image data to obtain a first contour; Extracting the target obstacle in the second image data to obtain a second contour; A calculation module is configured to determine the size information of the target obstacle according to the speed function, the camera shooting angle, the first profile and the second profile; The control module is configured to control the vehicle according to the size information of the target obstacle.

10. A controller, characterized in that: The controller includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor implements the obstacle avoidance method described in any one of claims 1 to 8 when executing the computer program.

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