Obstacle avoidance control method, autonomous work device, readable storage medium and software product

Abstract

Embodiments of the present application provide an obstacle avoidance control method, autonomous work equipment, a readable storage medium and software products, and relate to the technical field of autonomous work equipment. The obstacle avoidance control method comprises: when following a path to work, detecting obstacles in the surrounding environment in real time based on a sensor, and identifying the detected obstacles; when the detected obstacles cannot be identified, the obstacles are determined as a first type of obstacle, and a first obstacle avoidance strategy is executed to avoid the first type of obstacle; wherein the first type of obstacle is an obstacle that cannot be identified.

Description

Technical Field

[0001] This invention relates to the field of autonomous operating equipment technology, specifically to an obstacle avoidance control method, autonomous operating equipment, readable storage medium, and software product. Background Technology

[0002] Autonomous operating equipment, especially robots that can move autonomously within a preset area and perform specific tasks, typically includes intelligent sweeping / vacuum cleaners for cleaning and intelligent lawnmowers for mowing. For existing intelligent lawnmowers, the lawn area where they operate is only a part of the user's living environment, not an absolutely static scene. The lawn area in their operating environment may contain various types of obstacles, such as dynamic obstacles like humans and animals, temporarily placed static obstacles, and fixed obstacles.

[0003] Currently, obstacle avoidance strategies for autonomous operating equipment are not flexible enough, have low efficiency, and lack a high degree of intelligence. Summary of the Invention

[0004] The purpose of this invention is to provide an obstacle avoidance control method, autonomous operating equipment, readable storage medium, and software product that can dynamically avoid unidentified obstacles during path-following operations.

[0005] To achieve the above objectives, the present invention provides an obstacle avoidance control method applied to autonomous operating equipment; the method includes: during path following operation, detecting obstacles in the surrounding environment in real time based on sensors, and identifying the detected obstacles; when an obstacle cannot be identified, the obstacle is determined to be a first type of obstacle, and a first obstacle avoidance strategy is executed to avoid the first type of obstacle; wherein, the first type of obstacle is an obstacle that cannot be identified.

[0006] The present invention also provides an autonomous operating device for performing the obstacle avoidance control method described above.

[0007] The present invention also provides a non-transitory computer-readable storage medium storing processor-executable instructions configured to enable the processor of an autonomous operating device to execute the obstacle avoidance control method described above.

[0008] The present invention also provides a computer software product, including a computer program / instructions, which, when executed by a processor, implements the obstacle avoidance control method described above.

[0009] In one embodiment, the process of executing the first obstacle avoidance strategy to avoid the first type of obstacle includes the following steps:

[0010] The current driving speed is reduced to the first speed, while the status of the first type of obstacle is detected in real time based on the sensor.

[0011] When the first type of obstacle is detected to have disappeared, the current driving speed will be restored from the first speed to the original driving speed before the deceleration and the vehicle will continue to drive.

[0012] When the state of the first type of obstacle is detected as not having disappeared, continue driving at the first speed until a collision occurs with the first type of obstacle, then perform obstacle avoidance maneuver.

[0013] In one embodiment, the process of executing the first obstacle avoidance strategy to avoid the first type of obstacle includes the following steps:

[0014] Directly implement non-contact obstacle avoidance strategies.

[0015] In one embodiment, after executing the first obstacle avoidance strategy to avoid the first type of obstacle, the method further includes:

[0016] Mark the smallest area containing the first type of obstacle in the working map as the area to be re-inspected; wherein, the first type of obstacle is at least on the pre-planned Nth following path, and the Nth following path is the following path when the first type of obstacle is first detected during the path following operation, and N is a positive integer.

[0017] In one embodiment, after the autonomous operating device completes the pre-planned Nth following path, it continues to follow the N+1th following path and detects in real time whether the first type of obstacle detected on the Nth following path has disappeared.

[0018] If the first type of obstacle is detected to have disappeared, then supplementary work will be carried out on the area to be re-inspected during the operation of following the N+1th following path;

[0019] If the first type of obstacle is detected to have not disappeared, the obstacle-not-disappeared strategy is executed.

[0020] In one embodiment, the step of executing the obstacle not-disappeared strategy if the first type of obstacle is detected to have not disappeared includes:

[0021] If the first type of obstacle is detected to have not disappeared and is on the N+1th following path, the first obstacle avoidance strategy is executed again to avoid the first type of obstacle.

[0022] In one embodiment, the step of executing the obstacle not-disappeared strategy if the first type of obstacle is detected to have not disappeared includes:

[0023] If the first type of obstacle is detected to have not disappeared and is not on the N+1 following path, then continue to follow the N+1 following path for operation.

[0024] In one embodiment, the area to be re-inspected occupies part of the Nth to N+Yth following paths in the working map, where Y is an integer greater than or equal to 1;

[0025] Follow the Nth to the (N+Y)th follow paths sequentially, and during the process of performing the follow operation on each specified follow path from the Nth to the (N+Y)th follow path:

[0026] If the area to be re-inspected has been repaired, there is no need to detect in real time whether the first type of obstacle in the area to be re-inspected has disappeared;

[0027] If the re-inspection area has not completed the supplementary work, the system will detect in real time whether the first type of obstacle in the re-inspection area has disappeared; if the first type of obstacle has been detected to have disappeared, the system will perform supplementary work on the re-inspection area while following the specified follow path; if the first type of obstacle has not been detected to have disappeared, the system will execute the first obstacle avoidance strategy again to avoid the first type of obstacle.

[0028] In one embodiment, the specific method for performing supplementary work on the area to be re-inspected during the operation of following the Mth following path is as follows:

[0029] Based on the following path covered by the area to be re-inspected and the trajectory position of the Mth following path adjacent to the area to be re-inspected, a trajectory plan for supplementary work on the area to be re-inspected is obtained;

[0030] The re-inspection area is supplemented according to the trajectory planning; wherein, the Mth following path is the following path when the first type of obstacle is first detected to disappear, and M is an integer greater than 1.

[0031] In one embodiment, the method further includes: after completing the supplementary work on the area to be re-inspected according to the trajectory plan, the autonomous operating equipment returns to the trajectory position adjacent to the area to be re-inspected on the Mth following path, and continues to follow the remaining Mth following path to perform following path work.

[0032] In one embodiment, the method further includes:

[0033] When a detected obstacle is identified as a dynamic obstacle, the autonomous operating device is controlled to execute a second obstacle avoidance strategy.

[0034] When a detected obstacle is identified as a static obstacle, the autonomous operating device is controlled to execute a third obstacle avoidance strategy.

[0035] In one embodiment, controlling the autonomous operating device to execute a second obstacle avoidance strategy includes:

[0036] During the process of the autonomous operating equipment moving towards the detected dynamic obstacle:

[0037] If the distance between the autonomous operating equipment and the detected dynamic obstacle is detected in real time to meet the Kth deceleration condition among P deceleration levels, the current driving speed is reduced for the Kth time before driving continues, and the state of the dynamic obstacle is detected in real time; wherein, if the state of the dynamic obstacle is detected as having disappeared, the speed before the first deceleration is restored; if the state of the dynamic obstacle is detected as not having disappeared, the driving speed after the Kth deceleration is maintained and driving continues; 1≤K<P, P is an integer greater than 1, and each deceleration level condition is: the distance between the autonomous operating equipment and the dynamic obstacle reaches the corresponding preset distance, and the preset distance corresponding to the P deceleration levels decreases sequentially;

[0038] If the distance between the autonomous operating equipment and the detected dynamic obstacle is detected in real time and meets the deceleration condition of level P, then the non-contact obstacle avoidance strategy is executed.

[0039] In one embodiment, controlling the autonomous operating device to execute a third obstacle avoidance strategy includes:

[0040] Control the autonomous operating equipment to execute a non-contact obstacle avoidance strategy.

[0041] In one embodiment, the process of controlling the autonomous operating device to execute the third obstacle avoidance strategy further includes:

[0042] The state of the static obstacle is detected in real time. If the static obstacle is detected to be in a moved state, the system switches to execute the fourth obstacle avoidance strategy; otherwise, the third obstacle avoidance strategy continues to be executed.

[0043] In one embodiment, executing the fourth obstacle avoidance strategy includes:

[0044] Obtain the direction of movement of the static obstacle in the moving state;

[0045] When the direction of movement is towards the autonomous operating equipment, the autonomous operating equipment is controlled to detour around the static obstacle according to a preset obstacle detour range;

[0046] When the direction of movement is away from the autonomous operating device, the autonomous operating device is controlled to stop executing the third obstacle avoidance strategy and return to the following path to continue operation.

[0047] In one embodiment, identifying the detected obstacle includes:

[0048] The detected obstacles are compared with a predefined obstacle library;

[0049] If the currently detected obstacle is not found in the predefined obstacle library, then the currently detected obstacle is determined to be a Class I obstacle.

[0050] In one embodiment, the sensor is a non-contact obstacle detector.

[0051] In one embodiment, the non-contact obstacle detector is a vision module. Attached Figure Description

[0052] Figure 1 This is a detailed flowchart of the obstacle avoidance control method according to the first embodiment of the present invention;

[0053] Figure 2 This is a schematic diagram of the autonomous operating equipment according to the first embodiment of the present invention operating along a bow-shaped full-coverage trajectory;

[0054] Figure 3 This is a schematic diagram of an autonomous operating device according to the first embodiment of the present invention avoiding a first type of obstacle Z1;

[0055] Figure 4 This is a schematic diagram of the autonomous operating device according to the first embodiment of the present invention performing obstacle avoidance again for the first type of obstacle Z1;

[0056] Figure 5 This is a schematic diagram of the autonomous operating equipment according to the first embodiment of the present invention performing supplementary operations on the area to be re-inspected where the first type of obstacle Z1 is located;

[0057] Figure 6 This is a schematic diagram of the autonomous operating device according to the first embodiment of the present invention performing multiple obstacle avoidances against the first type of obstacle Z2;

[0058] Figure 7 This is a schematic diagram of the autonomous operating equipment according to the first embodiment of the present invention performing supplementary operations on the area to be re-inspected where the first type of obstacle Z2 is located;

[0059] Figure 8 This is a detailed flowchart of the obstacle avoidance control method according to the second embodiment of the present invention;

[0060] Figure 9 This is a schematic diagram of the autonomous operating system of this application;

[0061] Figure 10 This is a schematic diagram of the autonomous operating equipment of this application. Detailed Implementation

[0062] The embodiments of the present invention will be described in detail below with reference to the accompanying drawings to provide a clearer understanding of the purpose, features, and advantages of the present invention. It should be understood that the embodiments shown in the drawings are not intended to limit the scope of the present invention, but are merely illustrative of the essential spirit of the technical solution of the present invention.

[0063] In the following description, certain specific details are set forth for the purpose of illustrating various disclosed embodiments in order to provide a thorough understanding of the various disclosed embodiments. However, those skilled in the art will recognize that embodiments may be practiced without one or more of these specific details. In other instances, well-known apparatuses, structures, and techniques associated with this application may not have been shown or described in detail to avoid unnecessarily obscuring the description of the embodiments.

[0064] Unless the context requires otherwise, throughout the specification and claims, the word “comprising” and its variations, such as “including” and “having”, shall be understood to have an open, inclusive meaning, that is, to be interpreted as “including, but not limited to”.

[0065] Throughout this specification, references to "an embodiment" or "an embodiment" indicate that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment. Therefore, the appearance of "in an embodiment" or "an embodiment" in various places throughout the specification does not necessarily refer to the same embodiment. Furthermore, a particular feature, structure, or characteristic may be combined in any manner in one or more embodiments.

[0066] The singular forms “a” and “the” used in this specification and the appended claims include plural references unless otherwise expressly stated herein. It should be noted that the term “or” is generally used to include the meaning of “or / and” unless otherwise expressly stated herein.

[0067] In the following description, in order to clearly demonstrate the structure and working method of the present invention, a number of directional terms will be used. However, terms such as "front", "back", "left", "right", "outside", "inside", "outward", "inward", "up", and "down" should be understood as convenient terms and not as limiting terms.

[0068] The first embodiment of this invention relates to an obstacle avoidance control method applied to an autonomous operating device, specifically executed by a control module within the autonomous operating device. The autonomous operating device is a robot capable of autonomously moving and performing specific tasks within a pre-defined working area enclosed by boundaries, typically such as a smart sweeper / vacuum cleaner performing cleaning tasks, or a smart lawnmower performing mowing tasks. The aforementioned pre-defined working area enclosed by boundaries can be formed by pre-embedded wires at the boundaries, with the autonomous operating device using its built-in inductance sensor to detect the inductance signal at the boundary wires to identify the boundary lines; alternatively, the autonomous operating device is equipped with sensors, allowing it to identify the boundaries and obtain the pre-defined working area enclosed by the boundaries during initial operation, the first operation after initialization and reset, or when user-triggered boundary recognition. Additionally, a docking station for charging the autonomous operating device is also provided on the boundaries.

[0069] The specific process of the obstacle avoidance control method in this embodiment is as follows: Figure 1 As shown, the autonomous operating device in this embodiment has a pre-stored obstacle library. This obstacle library contains various identifiable obstacles, including obstacles pre-installed at the factory and obstacles actively added by the user. The identifiable obstacles in the obstacle library can be pre-classified by type, specifically including static obstacles and dynamic obstacles. For example, dynamic obstacles include animals, people, or other obstacles that can move autonomously; static obstacles include furniture (tables, chairs), electrical appliances (oven), trees, and other obstacles that cannot move autonomously.

[0070] Step 101: During path following operation, obstacles in the surrounding environment are detected in real time based on sensors, and the detected obstacles are identified.

[0071] Step 102: When the detected obstacle cannot be identified, the obstacle is identified as a first type of obstacle, and a first obstacle avoidance strategy is executed to avoid the first type of obstacle; wherein, the first type of obstacle is an obstacle that cannot be identified.

[0072] Specifically, when the autonomous operating equipment operates within a preset work area, it can pre-plan its operating path according to a set operating mode, resulting in a predetermined operating path. The operating mode determines the operating path of the autonomous operating equipment. Common operating modes include, but are not limited to, bow-shaped following operating mode, spiral following operating mode, and random path operating mode. For example, in bow-shaped following operating mode, the predetermined operating path is a bow-shaped full-coverage trajectory; in spiral following operating mode, the predetermined operating path is a spiral full-coverage path. In some embodiments, the pre-planned predetermined operating path can also be a user-configured operating path.

[0073] After startup, the autonomous operating equipment will follow the predetermined operating path. Please refer to [link / reference]. Figure 2 The pre-planned operation path is a bow-shaped full-coverage path, and the autonomous operation equipment follows the bow-shaped full-coverage path to perform path-following operations within the preset work area.

[0074] The autonomous operating equipment can travel at a preset fixed speed or a speed currently configured by the user when following a path. This speed is referred to as the initial speed. When following a predetermined operating path, the autonomous operating equipment will use its equipped sensors to detect whether there are obstacles in the surrounding environment in real time. For example, the sensors are non-contact obstacle detectors, such as ultrasonic sensors, infrared sensors, and lidar (LiDAR). For example, the sensors are vision modules, such as cameras.

[0075] If no obstacle is detected in the surrounding environment, the path following operation continues; at the same time, the surrounding environment is continuously detected for obstacles using sensors.

[0076] If an obstacle is detected in the surrounding environment, the detected obstacle is identified to determine whether it is an identifiable obstacle; if the obstacle is an unidentifiable obstacle (i.e., a first type of obstacle), the first obstacle avoidance strategy avoids the first type of obstacle.

[0077] Taking the sensor as a vision module as an example, the autonomous operating equipment detects obstacles in the environmental image through visual recognition. The specific process is as follows: During the path-following operation of the autonomous operating equipment, the vision module collects the environmental image in front of the autonomous operating equipment (in the direction of movement) and sends it to the control module; the control module then performs obstacle detection on the collected environmental image and identifies the obstacles. For example, if the autonomous operating device is a lawnmower, the control module will identify grass and non-grass obstacles in the environmental image. Specifically, the control module extracts images of the objects contained in the environmental image, such as using the depth point cloud information of the environmental image, and converts all objects contained in the environmental image into the machine coordinate system of the autonomous operating device. Then, it compares the height of these objects in the machine coordinate system with a preset height threshold to determine the obstacles. Taking a lawnmower as an example, if the height of the grass cut by the lawnmower is 80mm to 140mm, the height threshold can be set to a value greater than 140mm, such as 150mm. For non-grass objects identified from the environmental image, the lawnmower will identify objects with a height greater than 150mm as detected obstacles.

[0078] In addition, the autonomous operating equipment can add detected obstacles to the working map during path-following operations, forming an obstacle map to facilitate subsequent obstacle avoidance. For example, the autonomous operating equipment is equipped with a camera that can upload images of obstacles to the control module, which then adds the obstacle to the working map.

[0079] Then, the control module compares the detected obstacles with a predefined obstacle library, that is, it compares the detected obstacles with the identifiable obstacles in the predefined obstacle library. This comparison can be, for example, comparing the image of the obstacle with the images of each identifiable obstacle in the predefined obstacle library in turn; or comparing the name of the detected obstacle with the names of each identifiable obstacle in the predefined obstacle library. Through comparison, it can be determined whether the obstacle is in the predefined obstacle library, that is, whether the detected obstacle is an identifiable obstacle in the obstacle library or a first-class obstacle.

[0080] If the detected obstacle is not in the predefined obstacle library, the obstacle is determined to be a first-class obstacle. A first-class obstacle is an obstacle that is not predefined in the obstacle library or cannot be found in the obstacle library. For a first-class obstacle, a preset first obstacle avoidance strategy is executed to avoid the first-class obstacle.

[0081] To better understand the process by which the autonomous operating device of a specific embodiment of the present invention executes a preset first obstacle avoidance strategy to avoid a first type of obstacle, please refer to the following... Figure 3 The autonomous operating equipment detected obstacle Z1 during the path-following operation. Obstacle Z1 was not in the predefined obstacle library, that is, obstacle Z1 was a first type of obstacle. The autonomous operating equipment executed the preset first obstacle avoidance strategy to avoid obstacle Z1.

[0082] The first obstacle avoidance strategy includes the following two strategies:

[0083] Method 1: Deceleration and Obstacle Avoidance Strategy; When the autonomous operating equipment detects a first type of obstacle through sensors (e.g., the first type of obstacle is detected by visual recognition and also by image depth point cloud information), it executes a deceleration and obstacle avoidance strategy. The autonomous operating equipment decelerates from its current speed. The deceleration method can be, for example, directly reducing to a fixed speed, or it can decelerate by a certain percentage based on the current speed, such as a 50% reduction. For example, if the current speed of the autonomous operating equipment is 4 km / h, then the decelerated speed of the autonomous operating equipment will be 2 km / h. The timing of the deceleration can be determined by the autonomous operating equipment continuously monitoring the first type of obstacle within a preset time period. For example, the sensor is a vision module, and the environmental image collected by the vision module of the autonomous operating equipment is pre-configured with a rectangular bounding box. The area covered by this rectangular bounding box is: 0-50cm directly in front of the autonomous operating equipment and a rectangular area on the left and right sides that is 5cm wider than the body of the autonomous operating equipment. If the autonomous operating equipment can consistently detect the first type of obstacle within this rectangular bounding box within the preset time period, then deceleration is triggered.

[0084] After decelerating to the initial speed, the autonomous operating equipment continues to follow the predetermined operating path, continuously monitoring the status of the first type of obstacle using sensors (e.g., continuous status detection of the first type of obstacle through environmental images captured by a vision module). If the first type of obstacle is detected as having disappeared, it indicates that the obstacle may be an unidentified dynamic obstacle or a static obstacle that has been promptly removed. In this case, the autonomous operating equipment resumes its speed from the initial speed to its pre-deceleration speed and continues operating along the predetermined operating path. If the first type of obstacle is detected as not having disappeared, it continues to travel at the initial speed until a collision occurs with the obstacle. This indicates that the first type of obstacle persists, and it may be an unidentified static obstacle or an unidentified stationary dynamic obstacle. In this case, the autonomous operating equipment detours to avoid the first type of obstacle, either maintaining a certain distance or staying close to it during the detour.

[0085] by Figure 3 For example, when the autonomous operating equipment is bypassing the first type of obstacle Z1, it leaves the current following path at point P1, turns left to bypass the first type of obstacle Z1, and forms an obstacle avoidance trajectory as shown in the figure. After bypassing the obstacle, it returns to point P2 of the current following path, resumes the speed before deceleration, and continues to follow the current following path from point P2.

[0086] In the deceleration and obstacle avoidance strategy, the autonomous operating equipment further determines whether the first type of obstacle persists by decelerating and colliding. If the first type of obstacle persists, it will detour around the obstacle. If the first type of obstacle disappears, it will pass directly, which makes the autonomous operating equipment more adaptable to the site and has a higher operating coverage.

[0087] Method 2: Non-contact obstacle avoidance strategy; After the autonomous operating equipment detects the first type of obstacle through sensors (for example, the first type of obstacle is detected by visual recognition and also by image depth point cloud information), it continues to move towards the first type of obstacle and continuously detects the status of the first type of obstacle through sensors (for example, continuously detecting the status of the first type of obstacle through environmental images collected by the vision module); if the status of the first type of obstacle is detected as disappearing, it means that the first type of obstacle may be an unidentified dynamic obstacle or a static obstacle that has been moved in time. There is no need to avoid the obstacle, and the path following operation can continue according to the predetermined operation path.

[0088] If the detected first-type obstacle is still present, the distance between the autonomous operating equipment and the first-type obstacle is detected by the sensor. The distance is then compared to a set distance threshold. If the distance is greater than the threshold, the equipment continues driving, continuously monitoring the distance to the first-type obstacle until it falls below the threshold. This indicates the obstacle is either an unidentified static obstacle or an unidentified stationary dynamic obstacle. The autonomous operating equipment then avoids this obstacle, maintaining a certain distance or remaining close to it during the avoidance process. Taking a vision module as an example, the distance between the autonomous operating equipment and the first-type obstacle can be obtained from the depth point cloud information in the environmental image captured by the vision module. The specific method by which the autonomous operating equipment avoids the first-type obstacle is as follows... Figure 3 Similarly, I will not go into details here.

[0089] It should be noted that when the autonomous operating equipment detects a first type of obstacle, it can randomly select one of the above-mentioned obstacle avoidance strategies (deceleration contact obstacle avoidance strategy and non-contact obstacle avoidance strategy) as the first obstacle avoidance strategy to avoid the first type of obstacle. Alternatively, the user can configure which obstacle avoidance strategy is currently used as the first obstacle avoidance strategy.

[0090] In this embodiment, the autonomous operating device will continuously perform the aforementioned obstacle detection and obstacle avoidance processes during the path-following operation.

[0091] In some embodiments, step 102 is followed by:

[0092] Step 103: Mark the smallest area where the first type of obstacle is located on the working map as the area to be re-inspected; wherein, the first type of obstacle is at least on the pre-planned Nth following path, and the Nth following path is the following path when the first type of obstacle is first detected during the path following operation.

[0093] Specifically, after the autonomous operating equipment avoids a first-type obstacle, it returns to the predetermined operating path to continue working. The smallest area containing the first-type obstacle can be determined based on its trajectory during the avoidance process. This smallest area is the area to be re-inspected corresponding to the first-type obstacle. Subsequently, this area to be re-inspected is marked on the working map corresponding to the preset working area of ​​the autonomous operating equipment. The area to be re-inspected is a closed area formed on the working map. For example, the method for determining the area to be re-inspected can be as follows: when the autonomous operating equipment avoids a first-type obstacle on the Nth following path, the point where the autonomous operating equipment leaves the Nth following path, the obstacle avoidance trajectory, and the point where it returns to the Nth following path can be obtained, thus yielding an area to be re-inspected; alternatively, the area to be re-inspected, including the first-type obstacle, can be obtained through information about the first-type obstacle detected by sensors (including its position and volume).

[0094] The area to be re-inspected occupies at least one following path on the pre-planned predetermined operation path. For example, if the pre-planned predetermined operation path includes multiple following paths, and the Nth following path is the following path when the first type of obstacle is first detected during the path following operation, then the first type of obstacle is at least on the pre-planned Nth following path, where N is a positive integer. Figure 2 As shown, the pre-planned predetermined operation path includes 7 following paths from left to right. When the autonomous operation equipment starts from the starting point of the predetermined operation path and performs following operation along the first following path, it detects the first type of obstacle Z1. Therefore, the first type of obstacle Z1 is at least on the first following path.

[0095] It should be noted that, in this embodiment, the first type of obstacle is defined as: the autonomous operating equipment will come into contact with the first type of obstacle when it travels on the following path.

[0096] After step 103, you can choose to execute step 104 or step 105 to continue the following path operation.

[0097] Step 104: After the autonomous operating equipment completes the pre-planned Nth following path, it continues to follow the (N+1)th following path and continuously monitors whether the first type of obstacle detected on the Nth following path has disappeared. If the first type of obstacle has disappeared, supplementary operations are performed on the area to be re-inspected during the operation of the (N+1)th following path; if the first type of obstacle has not disappeared, the obstacle-not-disappeared strategy is executed.

[0098] Specifically, after the autonomous operating equipment detects and avoids a first-type obstacle on the Nth following path, it returns to the Nth following path to continue the remaining following operations. After completing the work on the Nth following path, it follows the (N+1)th following path. During the operation, it uses sensors to detect in real time whether the first-type obstacle detected on the Nth following path has disappeared, that is, whether the first-type obstacle in the area to be re-inspected has disappeared. The method of detecting whether the first-type obstacle has disappeared based on sensors can refer to the relevant content on detecting the presence of obstacles in the surrounding environment based on sensors, and the two are similar, so they will not be repeated here.

[0099] If the first type of obstacle has disappeared, supplementary work is performed on the area to be re-inspected during the operation of following the (N+1)th follow path. For example, when approaching the area to be re-inspected, the operator can leave the (N+1)th follow path to perform supplementary work on the area. After the supplementary work is completed, the operator returns to the point where it left the (N+1)th follow path to continue following the remaining follow path. The method of supplementary work is related to the type of autonomous operating equipment. For example, if the autonomous operating equipment is a lawnmower, the supplementary work is supplementary mowing; if the autonomous operating equipment is a sweeper, the supplementary work is supplementary sweeping.

[0100] After the area to be re-inspected has been repaired, the autonomous operating equipment will no longer check whether the first type of obstacle in the area to be re-inspected has disappeared.

[0101] If the first type of obstacle is detected as not having disappeared, the obstacle not yet disappeared strategy is executed, which is specifically divided into the following two types:

[0102] The first approach involves re-exercising the first obstacle avoidance strategy if it is detected that the first type of obstacle has not disappeared and is located on the (N+1)th following path. In other words, during the operation following the (N+1)th following path, if the first type of obstacle in the area to be re-inspected is detected as not having disappeared, further confirming that the first type of obstacle is also on the (N+1)th following path, the first obstacle avoidance strategy is executed again to avoid it. The specific details of the first obstacle avoidance strategy can be found in the previous description and will not be repeated here.

[0103] like Figure 4 As shown, the autonomous operating equipment detects obstacle Z1 (Type 1) on the first following path. When performing following operations on the second following path, it detects that obstacle Z1 has not disappeared and is still on the second following path. The autonomous operating equipment then executes the first obstacle avoidance strategy again to avoid obstacle Z1. The autonomous operating equipment leaves the second following path and detours around obstacle Z1, as shown in the avoidance trajectory. Figure 4 As shown, after successfully avoiding the first type of obstacle Z1, the system returns to the second following path to continue the path following operation.

[0104] For example, after determining that the first type of obstacle is also on the (N+1)th following path, the first obstacle avoidance strategy is executed again to avoid the first type of obstacle. After avoiding it, the operation continues on the remaining (N+1)th following path. After completing the operation on the (N+1)th following path, if there is a subsequent (N+2)th following path, the operation continues on the (N+2)th following path. During the operation, it is possible to continue to detect whether the first type of obstacle in the area to be re-inspected has disappeared. If it is detected that the first type of obstacle has disappeared, then supplementary operations are performed on the area to be re-inspected while following the (N+2)th following path. If it is detected that the first type of obstacle has not disappeared, then the obstacle not disappeared strategy is executed again. This process can still be repeated when following subsequent following paths.

[0105] The second approach is to continue following the N+1 following path if the first type of obstacle is detected as not having disappeared and is not located on the N+1 following path. In other words, if, during the operation following the N+1 following path, the first type of obstacle in the area to be re-inspected is detected as not having disappeared, further confirming that the first type of obstacle is not on the N+1 following path, then the operation continues following the N+1 following path. After completing the following operation on the N+1 following path, the following operation on subsequent following paths can proceed normally.

[0106] Step 105: Perform follow-up operations sequentially on the Nth to N+Yth follow-up paths. During the operation on each designated follow-up path from the Nth to the N+Yth follow-up path: if the area to be re-inspected has completed the supplementary operation, there is no need to detect in real time whether the first type of obstacle in the area to be re-inspected has disappeared; if the area to be re-inspected has not completed the supplementary operation, then detect in real time whether the first type of obstacle in the area to be re-inspected has disappeared; if the first type of obstacle is detected to have disappeared, then supplementary operation is performed on the area to be re-inspected during the operation on the designated follow-up path; if the first type of obstacle is detected to have not disappeared, then the first obstacle avoidance strategy is executed again to avoid the first type of obstacle.

[0107] Specifically, the area to be re-inspected occupies part of the Nth to N+Yth following paths in the working map, where Y is an integer greater than or equal to 1; that is, the first type of obstacle is on at least one following path.

[0108] Taking Y=2 as an example, the area to be re-inspected occupies three consecutive following paths on the working map, from the Nth to the N+2th. During operation on the first following path, the autonomous operating equipment detects a first type of obstacle and executes the first obstacle avoidance strategy to avoid it. After completing operation on the Nth following path, it continues to operate on the N+1th following path. During operation on the N+1th following path:

[0109] Real-time detection of whether the first type of obstacle detected on the Nth following path has disappeared, that is, detection of whether the first type of obstacle in the area to be re-inspected has disappeared;

[0110] If the first type of obstacle is detected to have disappeared, then supplementary work is performed on the area to be re-inspected during the operation of following the N+1th following path;

[0111] If the first type of obstacle is not detected to have disappeared, the first obstacle avoidance strategy is executed again to avoid the first type of obstacle. After avoiding the first type of obstacle, the operation continues on the remaining part of the N+1th following path. After completing the operation on the N+1th following path, the operation continues on the N+2th following path. When operating on the N+2th following path:

[0112] If the area to be re-inspected has already completed the supplementary work during the operation of following the N+1th following path, then there is no need to detect in real time whether the first type of obstacle in the area to be re-inspected has disappeared.

[0113] If the area to be re-inspected does not complete the supplementary work during the operation of following the (N+1)th follow path, it is still necessary to detect in real time whether the first type of obstacle in the area to be re-inspected has disappeared. If the first type of obstacle is detected to have disappeared, supplementary work is performed on the area to be re-inspected during the operation of following the (N+2)th follow path. If the first type of obstacle is detected not to have disappeared, the first obstacle avoidance strategy is executed again to avoid the first type of obstacle, and after avoiding the first type of obstacle, the remaining part of the (N+2)th follow path is continued. After the follow operation of the (N+2)th follow path is completed, the follow operation of the subsequent follow paths can be performed normally.

[0114] In steps 104 and 105 above, when the autonomous operating equipment detects the disappearance of the first type of obstacle during operation on the following path, supplementary operation is performed on the area to be re-inspected. Let the Mth following path be the following path where the disappearance of the first type of obstacle is first detected, and M be an integer greater than 1. That is, when the autonomous operating equipment detects the disappearance of the first type of obstacle for the first time on the Mth following path after the Nth following path where the first type of obstacle was first detected, the specific method for supplementary operation on the area to be re-inspected during operation on the Mth following path is as follows:

[0115] Based on the following path covered by the area to be re-inspected and the trajectory position of the Mth following path adjacent to the area to be re-inspected, a trajectory plan for supplementary work on the area to be re-inspected is obtained; then, supplementary work is performed on the area to be re-inspected based on the trajectory plan.

[0116] Furthermore, after completing the supplementary work in the area to be re-inspected according to the trajectory plan, the autonomous operating equipment returns to the trajectory position adjacent to the area to be re-inspected on the Mth following path, and continues to follow the remaining Mth following path to perform following path work.

[0117] Autonomous operating equipment may detour around and avoid Class I obstacles once or multiple times. The following will explain two scenarios.

[0118] Scenario 1: The autonomous operating equipment only detoured to avoid the first type of obstacle once. Please refer to [reference needed]. Figure 5 The pre-planned operating path of the autonomous operating equipment is a bow-shaped following path, which includes 7 following paths from left to right. The autonomous operating equipment first detects the first type of obstacle Z1 on the first following path and avoids it. It leaves the first following path at point P1, turns left to drive around the first type of obstacle Z1, and forms an obstacle avoidance trajectory as shown in the figure. After avoiding the obstacle, it returns to point P2 on the first following path. The area to be re-inspected can be composed of the following path and obstacle avoidance trajectory between point P1 and point P2 on the first following path.

[0119] When the autonomous operating equipment is working on the second following path, it detects the disappearance of the first type of obstacle Z1. At this time, the autonomous operating equipment prepares to perform supplementary work on the area to be re-inspected. The second following path is the following path on which the disappearance of the first type of obstacle was first detected. First, the trajectory positions of the area to be re-inspected on the second following path are obtained. For example, the two positions on the second following path can be obtained: point P1, where the autonomous operating equipment leaves the first following path when it avoids the first type of obstacle Z1, and point P2, where it returns to the first following path. The point on the second following path adjacent to point P1 is point P4, and the point adjacent to point P2 is point P3. For example, the coordinates of point P1 are (x1, y1), and the coordinates of point P2 are (x1, y1 + Δy). P1P2 If the distance between adjacent following paths is K when the bow-shaped pattern is followed, then the coordinates of the determined trajectory position point P3 are (x1+K, y1), and the coordinates of the trajectory position point P4 are (x1+K, y1+Δy). P1P2 ).

[0120] Then, points P1, P2, P3, and P4 can be combined to obtain the trajectory planning for supplementary work on the area to be re-inspected. The trajectory planning is, for example, P3->P2->P1->P4->P3, or P3->P4->P1->P2->P3.

[0121] After completing the supplementary work in the area to be reviewed according to the trajectory plan, the autonomous operating equipment returns to the starting point P3 of the supplementary work and continues to work on the remaining part of the second following path from point P3, that is, it works from point P3 toward point P5 on the second following path.

[0122] Scenario 2: The autonomous operating equipment repeatedly detours to avoid Category I obstacles. Please refer to [reference needed]. Figure 6 and Figure 7 The autonomous operating equipment pre-plans a bow-shaped following path, which includes 9 following paths from left to right. The autonomous operating equipment first detects obstacle Z2 (Type 1) on the first following path and avoids it, leaving point P1 on the first following path and returning to point P2. The autonomous operating equipment detects obstacle Z2 again on the second following path and avoids it again, leaving point P3 on the second following path and returning to point P4. The autonomous operating equipment detects obstacle Z2 again on the third following path and avoids it again, leaving point P6 on the third following path and returning to point P5.

[0123] The area to be re-inspected can be a closed area formed by the avoidance trajectory between point P1 and point P2, the avoidance trajectory between point P5 and point P6, and the combination of points P1 to P6.

[0124] When the autonomous operating equipment is working on the fourth following path, it detects that the first type of obstacle Z2 has disappeared. At this time, the autonomous operating equipment is ready to carry out supplementary work on the area to be re-inspected. The fourth following path is the following path on which the disappearance of the first type of obstacle Z2 was first detected. First, the trajectory positions of the area to be re-inspected on the fourth following path are obtained. For example, the two positions of the point P6 on the fourth following path where the autonomous operating equipment leaves the previous following path (i.e., the third following path) and the point P5 where it returns to the previous following path (i.e., the third following path) can be obtained as trajectory positions; among them, the point adjacent to point P5 on the fourth following path is point P7 and the point adjacent to point P6 is point P8.

[0125] Then, by combining points P1 to P8, we can obtain the trajectory planning for supplementary work on the area to be re-inspected. The trajectory planning is, for example, P7->P2->P1->P4->P3->P5->P6->P8->P7. Figure 7 Taking this as an example; it can also be combined in the manner of inner circle first and outer circle later, then the trajectory planning is: P7->P5->P6->P4->P3->P2->P1->P8->P7.

[0126] After completing the supplementary work in the area to be re-inspected according to the trajectory plan, the autonomous operating equipment returns to the starting point P7 of the supplementary work and continues to work on the remaining part of the 4th following path from point P7, that is, working from point P7 to point P9 on the 4th following path.

[0127] It should also be noted that in both of the above situations, Figure 4 The obstacle Z1 and Figure 6 The obstacles Z2 in the figure are all Class I obstacles, but they are two different obstacles detected by the autonomous working equipment during the following path operation. For example, they are two different Class I obstacles detected by the autonomous working equipment when it is working in two different work areas. Therefore, different reference numerals are used to represent these two Class I obstacles respectively.

[0128] Therefore, this application enables the autonomous operating equipment to promptly perform supplementary operations on the area previously occupied by the first type of obstacle (where no work had been done before) if the first type of obstacle is detected to have disappeared during the continued operation after obstacle avoidance. This improves the operating efficiency of the autonomous operating equipment and avoids missed operations caused by obstacles temporarily occupying space, thus increasing the operational coverage. In summary, this invention combines dynamic obstacle avoidance with supplementary cutting strategies for the first type of obstacle, effectively improving the obstacle avoidance flexibility and timeliness of supplementary operations of the autonomous operating equipment, thereby enhancing the applicable scenarios and user experience of the autonomous operating equipment.

[0129] In some embodiments, if the autonomous operating equipment has completed the operation of the preset working area, but there are still areas to be re-inspected that have not been re-operated, then obstacle detection can be performed again on the areas to be re-inspected that have not been re-operated, and the areas to be re-inspected where the obstacles have disappeared can be uniformly re-cut; for the areas to be re-inspected where there are still obstacles, the relevant information of the areas to be re-inspected can also be recorded and sent to the user's electronic device to remind the user to manually inspect the areas to be re-inspected.

[0130] The second embodiment of the present invention relates to an obstacle avoidance control method. Compared with the first embodiment, this embodiment provides an obstacle avoidance processing method for autonomous operating equipment for identifiable obstacles in a predefined obstacle library.

[0131] The specific process of the obstacle avoidance control method in this embodiment is as follows: Figure 8 As shown, steps 201 to 205 are largely the same as steps 101 to 105 in the first embodiment. The relevant content can be referred to the corresponding positions in the first embodiment, and will not be repeated here. The steps in the second embodiment that are different from those in the first embodiment will be described in detail later.

[0132] Step 201: During path following operation, obstacles in the surrounding environment are detected in real time based on sensors, and the detected obstacles are identified.

[0133] Step 202: When the detected obstacle cannot be identified, the obstacle is identified as a first type of obstacle, and a first obstacle avoidance strategy is executed to avoid the first type of obstacle; wherein, the first type of obstacle is an obstacle that cannot be identified.

[0134] Step 203: Mark the smallest area where the first type of obstacle is located on the working map as the area to be re-inspected; wherein, the first type of obstacle is at least on the pre-planned Nth following path, and the Nth following path is the following path when the first type of obstacle is first detected during the path following operation.

[0135] Step 204: After the autonomous operating equipment completes the pre-planned Nth following path, it continues to follow the (N+1)th following path and continuously monitors whether the first type of obstacle detected on the Nth following path has disappeared. If the first type of obstacle has disappeared, supplementary operations are performed on the area to be re-inspected during the operation of the (N+1)th following path; if the first type of obstacle has not disappeared, the obstacle-not-disappeared strategy is executed.

[0136] Step 205: Perform follow-up operations sequentially on the Nth to N+Yth follow-up paths. During the operation on each designated follow-up path from the Nth to the N+Yth follow-up path: if the area to be re-inspected has completed the supplementary operation, there is no need to detect in real time whether the first type of obstacle in the area to be re-inspected has disappeared; if the area to be re-inspected has not completed the supplementary operation, then detect in real time whether the first type of obstacle in the area to be re-inspected has disappeared; if the first type of obstacle is detected to have disappeared, then supplementary operation is performed on the area to be re-inspected during the operation on the designated follow-up path; if the first type of obstacle is detected to have not disappeared, then the first obstacle avoidance strategy is executed again to avoid the first type of obstacle.

[0137] Step 206: When the detected obstacle is identified as a dynamic obstacle, the autonomous operating device is controlled to execute the second obstacle avoidance strategy.

[0138] Step 207: When the detected obstacle is identified as a static obstacle, the autonomous operating device is controlled to execute the third obstacle avoidance strategy.

[0139] Specifically, the control module compares the detected obstacles with a predefined obstacle library to determine whether the obstacle is in the predefined obstacle library, that is, whether the detected obstacle is an identifiable obstacle in the obstacle library or a first-class obstacle.

[0140] If the detected obstacle is within a predefined obstacle library, and the obstacles in the predefined obstacle library are classified into dynamic obstacles and static obstacles according to their type, then after determining the identifiable obstacle corresponding to the detected obstacle in the predefined obstacle library, the obstacle type to which the detected obstacle belongs can be obtained, that is, whether the detected obstacle is a dynamic obstacle or a static obstacle; and then, the obstacle avoidance strategy to be executed can be determined based on the type of the detected obstacle.

[0141] When a detected obstacle is identified as a dynamic obstacle, the autonomous operating equipment is controlled to execute a second obstacle avoidance strategy. The second obstacle avoidance strategy is a multi-level deceleration obstacle avoidance strategy, specifically as follows:

[0142] During the process of the autonomous operating equipment moving towards the detected dynamic obstacle:

[0143] If the distance between the autonomous operating equipment and the detected dynamic obstacle is detected in real time to meet the Kth deceleration condition among P deceleration levels, the current driving speed is reduced for the Kth time before driving continues, and the state of the dynamic obstacle is detected in real time; wherein, if the state of the dynamic obstacle is detected as having disappeared, the speed before the first deceleration is restored; if the state of the dynamic obstacle is detected as not having disappeared, the driving speed after the Kth deceleration is maintained and driving continues; 1≤K<P, P is an integer greater than 1, and each deceleration level condition is: the distance between the autonomous operating equipment and the dynamic obstacle reaches the corresponding preset distance, and the preset distance corresponding to the P deceleration levels decreases sequentially;

[0144] If the distance between the autonomous operating equipment and the detected dynamic obstacle is detected in real time and meets the deceleration condition of level P, then the non-contact obstacle avoidance strategy is executed.

[0145] In other words, the autonomous operating equipment has P levels of deceleration conditions preset in advance. Each level of deceleration condition is met and deceleration occurs once. Each level of deceleration condition is: the distance between the autonomous operating equipment and the dynamic obstacle reaches the corresponding preset distance. That is, the autonomous operating equipment is satisfied when the distance between itself and the dynamic obstacle reaches the preset distance corresponding to a certain level of deceleration condition. The preset distances corresponding to the P levels of deceleration conditions decrease sequentially.

[0146] As the autonomous operating equipment travels along the path towards a detected dynamic obstacle, it continuously monitors the distance between itself and the obstacle. When this distance reaches a preset distance corresponding to a certain level of deceleration, the autonomous operating equipment decelerates once and continues traveling, while continuously monitoring the state of the dynamic obstacle. If the dynamic obstacle is detected as having disappeared, it resumes traveling at the speed before the first deceleration. If the dynamic obstacle remains in its current state until the next level of deceleration is met (i.e., the distance between itself and the dynamic obstacle reaches the preset distance corresponding to the next level of deceleration), and if this level of deceleration is the last level of deceleration, then a non-contact obstacle avoidance strategy is executed to avoid the dynamic obstacle. The specific details of the non-contact obstacle avoidance strategy can be found in the detailed description of the non-contact obstacle avoidance strategy in the first embodiment, and will not be repeated here.

[0147] If the deceleration condition is not the final deceleration condition, then deceleration is performed once, and the vehicle continues to travel after deceleration. The state of the dynamic obstacle is monitored in real time, and the above process is repeated until the final deceleration condition is met. Then, a non-contact obstacle avoidance strategy is executed to avoid the dynamic obstacle.

[0148] The following example uses a multi-level deceleration obstacle avoidance strategy, specifically a two-level deceleration obstacle avoidance strategy. The autonomous operating equipment pre-sets three levels of deceleration conditions. The preset distance corresponding to the first level of deceleration condition is the first preset distance, the preset distance corresponding to the second level of deceleration condition is the second preset distance, and the preset distance corresponding to the third level of deceleration condition is the third preset distance. The first preset distance > the second preset distance > the third preset distance. For example, the first preset distance is 2m, the second preset distance is 1m, and the third preset distance is 0.5m. The specific process is as follows:

[0149] When an obstacle is identified as a dynamic obstacle, and the distance between the autonomous operating device and the detected dynamic obstacle reaches a first preset distance, the current driving speed (referred to as the original driving speed) is reduced to a second speed. The deceleration method can be to directly decelerate to the preset second speed, or to reduce the speed to a fixed value before reaching the second speed, or to decelerate by a percentage based on the current driving speed, such as reducing the speed to 75% of the current driving speed, i.e., the second speed is 75% of the current driving speed. In some embodiments, the autonomous operating device can immediately control the autonomous operating device to decelerate to the second speed when the obstacle is first identified as a dynamic obstacle.

[0150] The autonomous operating equipment continues to follow the path at a second speed while simultaneously monitoring the status of the dynamic obstacle in real time. If the dynamic obstacle is detected to have disappeared, the second speed is restored to the original driving speed and the equipment continues to travel. If the dynamic obstacle is detected to have not disappeared, the equipment maintains the second speed until the distance between the autonomous operating equipment and the detected dynamic obstacle reaches a second preset distance. At this point, the second speed is reduced to a third speed while the status of the dynamic obstacle is monitored in real time.

[0151] If the dynamic obstacle is detected to have disappeared, the third speed is restored to the original driving speed and the vehicle continues to drive. If the dynamic obstacle is detected to have not disappeared, the vehicle continues to drive at the third speed until the distance between the autonomous operating equipment and the detected dynamic obstacle is detected to meet the third preset distance. At this point, a non-contact obstacle avoidance strategy is executed to avoid the dynamic obstacle.

[0152] During the above process, when the autonomous operating equipment detects a dynamic obstacle, it adopts a corresponding two-stage deceleration and obstacle avoidance strategy, regardless of whether the obstacle is in motion. For example, if the obstacle in the environmental image is identified as a hedgehog through visual recognition, it is marked as a dynamic obstacle, and a two-stage deceleration and obstacle avoidance strategy is adopted regardless of whether the hedgehog is static or moving. If the autonomous operating equipment is far from the dynamic obstacle (i.e., the distance reaches the first preset distance), the first stage of deceleration is used. This avoids excessive deceleration that could affect the operating efficiency of the autonomous operating equipment, and after the first stage of deceleration, there is enough time to wait for the dynamic obstacle to leave, so that the autonomous operating equipment can promptly resume normal operating speed after the dynamic obstacle leaves. If the dynamic obstacle persists and the distance between the autonomous operating equipment and the dynamic obstacle reaches the second preset distance, it means that the distance between the autonomous operating equipment and the dynamic obstacle is too close. Due to the unpredictable movement of the dynamic obstacle, a second stage of deceleration is required. After the second stage of deceleration, the speed of the autonomous operating equipment is lower, which can prevent the dynamic obstacle from suddenly moving towards the autonomous operating equipment and causing a serious collision, thus protecting the safety of the dynamic obstacle. Subsequently, when the distance between the autonomous operating equipment and the dynamic obstacle reaches the third preset distance, it is considered that the dynamic obstacle has reached the preset obstacle avoidance range, and the obstacle avoidance is immediately performed to further protect the safety of the dynamic obstacle.

[0153] When a detected obstacle is identified as a static obstacle, the autonomous operating device is controlled to execute a third obstacle avoidance strategy. A static obstacle is an object that cannot move autonomously. For example, if the autonomous operating device identifies a chair as the current obstacle, it determines it to be a static obstacle. The third obstacle avoidance strategy for static obstacles includes, for example, controlling the autonomous operating device to execute a non-contact obstacle avoidance strategy to avoid the static obstacle. That is, directly controlling the autonomous operating device to bypass the static obstacle. Since static obstacles cannot move autonomously, the bypassing method can be to follow the edge of the static obstacle to reduce missed cuts at the edge of the static obstacle. The specific details of the non-contact obstacle avoidance strategy can be found in the detailed description of the non-contact obstacle avoidance strategy in the first embodiment, and will not be repeated here.

[0154] In some embodiments, during the process of controlling the autonomous operating device to execute the third obstacle avoidance strategy, static obstacles may be moved, such as a chair being dragged. Therefore, it is necessary to detect the state of the static obstacle in real time, that is, to detect whether the static obstacle is in a moved state. If the static obstacle is detected to be in a stationary state (not moved), the third obstacle avoidance strategy continues to be executed. If the static obstacle is detected to be in a moved state, the process switches to executing the fourth obstacle avoidance strategy.

[0155] The execution of the fourth obstacle avoidance strategy includes: obtaining the direction of movement of the static obstacle in the moving state; when the direction of movement is towards the autonomous operating equipment, controlling the autonomous operating equipment to detour around the static obstacle according to a preset obstacle avoidance range; when the direction of movement is away from the autonomous operating equipment, controlling the autonomous operating equipment to stop executing the third obstacle avoidance strategy and return to the following path to continue operation.

[0156] In other words, during the process of the autonomous operating equipment bypassing static obstacles, it is possible to detect in real time whether the static obstacle is being moved. Specifically, this can be achieved by detecting the movement of the static obstacle through real-time captured environmental images. If the static obstacle is detected as being moved, it indicates that the obstacle is being transported. The direction of movement of the obstacle is then determined to determine whether it is moving towards or away from the autonomous operating equipment. If the direction of movement is towards the autonomous operating equipment, it indicates that the distance between the obstacle and the equipment is decreasing. At this point, the autonomous operating equipment triggers a pre-set obstacle avoidance mode and bypasses the obstacle within a preset obstacle avoidance range. This preset range is a fixed distance (e.g., 1m) in all directions from the point where the obstacle avoidance is triggered. Furthermore, after bypassing the obstacle within the preset range, the autonomous operating equipment ends the obstacle avoidance process and, starting from its current position, replans its operating path, subsequently continuing its work along the replanned path.

[0157] If the static obstacle is being moved away from the autonomous working equipment, it means that the distance between the static obstacle and the autonomous working equipment is increasing. There is no risk of collision between the autonomous working equipment and the static obstacle. The autonomous working equipment can be controlled to stop detouring around the static obstacle and return to the predetermined working path to continue working.

[0158] The third embodiment of the present invention relates to an autonomous operating device for performing the obstacle avoidance control method in the first or second embodiment.

[0159] Autonomous robots are robots capable of moving autonomously within a pre-defined work area enclosed by boundaries and performing specific tasks. Typical examples include intelligent sweeping / vacuum cleaners for cleaning and intelligent lawnmowers for mowing. This pre-defined work area can be formed by pre-embedded electrical wires at the boundary, with the autonomous robot using its built-in inductive sensors to detect the inductive signals at the boundary wires to identify the boundary line. Alternatively, the autonomous robot may be equipped with a vision module (e.g., a camera), allowing it to identify the pre-defined work area enclosed by the boundary during its first operation, its first operation after initialization and reset, or when triggered by the user. Additionally, a docking station for charging the autonomous robot is located at the boundary.

[0160] Please refer to Figure 9 This application also provides an autonomous operation system 1, including an autonomous operation device 100, a docking station 900, and a boundary 800. The autonomous operation device is the same as the autonomous operation device in the third embodiment.

[0161] The autonomous operating device, in particular, is a robot capable of autonomously moving within a preset area and performing specific tasks, typically such as a smart sweeper / vacuum cleaner for cleaning or a smart lawnmower for mowing. The specific tasks specifically refer to actions that treat the work surface and alter its state. This invention uses a smart lawnmower as an example for detailed explanation. The autonomous operating device can autonomously move on the surface of the work area, and in particular, as a smart lawnmower, it can autonomously perform lawnmowing on the ground. The autonomous operating device includes at least a main body mechanism, a moving mechanism, a working mechanism, an energy module, a detection module, an interaction module, and a control module.

[0162] Please refer to Figure 10 The main body typically includes a chassis 20, which is used to install and house functional mechanisms and modules such as a moving mechanism, a working mechanism, an energy module, a detection module, an interaction module, and a control module. Typically, the chassis includes an upper chassis cover and a lower chassis cover, which are fastened together to form a sealed cavity for housing functional mechanisms and modules requiring waterproofing and / or dustproofing. In some embodiments, the main body also includes a housing 10, which is typically constructed to at least partially cover the chassis 20, primarily to enhance the aesthetics and recognizability of the autonomous operating equipment. In this embodiment, the housing is constructed to be able to translate and / or rotate relative to the chassis repositionably under external force. Combined with an appropriate detection module, such as a Hall sensor, it can further detect events such as collisions and lifting. In this embodiment, the upper chassis cover and the housing are the same structural component.

[0163] The mobile mechanism is configured to support the main body on the ground and drive it to move on the ground. It typically includes wheeled, tracked, or half-tracked mobile mechanisms and walking mobile mechanisms. In this embodiment, the mobile mechanism is a wheeled mobile mechanism, including at least one drive wheel 2001 and at least one prime mover 2002. The prime mover is preferably an electric motor, but in other embodiments it can be an internal combustion engine or a machine powered by other types of energy. In this embodiment, preferably, a left drive wheel, a left prime mover driving the left drive wheel, a right drive wheel, and a right prime mover driving the right drive wheel are provided. In this embodiment, the straight-line movement of the autonomous operating device is achieved by the same-speed rotation of the left and right drive wheels in the same direction, and turning movement is achieved by differential rotation or opposite rotation of the left and right drive wheels in the same direction. In other embodiments, the mobile mechanism may also include a steering mechanism independent of the drive wheels and a steering prime mover independent of the prime mover. In this embodiment, the moving mechanism further includes at least one driven wheel, which is typically constructed as a caster wheel, and the drive wheel and the driven wheel are located at the front and rear ends of the autonomous operating device, respectively.

[0164] The working mechanism is configured to perform specific tasks and includes working parts and a prime mover that drives the working parts. For example, in a smart sweeper / vacuum cleaner, the working parts include a roller brush, a suction pipe, and a dust collection chamber; in a smart lawnmower, the working parts include cutting blades or a cutting disc, and further include other components such as a height adjustment mechanism for adjusting the mowing height to optimize or adjust the mowing effect. The prime mover is preferably an electric motor, but in other embodiments it can also be an internal combustion engine or a machine powered by other types of energy. In some other embodiments, the prime mover and the driving prime mover are constructed as the same prime mover.

[0165] The energy module is configured to provide power for various tasks of the autonomous operating equipment. In this embodiment, the energy module includes a battery and a charging connection structure, wherein the battery is preferably a rechargeable battery, and the charging connection structure is preferably a charging electrode that can be exposed to the outside of the autonomous operating equipment.

[0166] The detection module is constructed as at least one sensor that senses environmental parameters of the autonomous operating equipment or its own operating parameters. Typically, the detection module may include sensors related to the defined working area, such as magnetic induction, impact, ultrasonic, infrared, and radio sensors, with the sensor type corresponding to the location and number of the corresponding signal generating devices. The detection module may also include sensors related to positioning and navigation, such as GPS positioning devices, laser positioning devices, electronic compasses, accelerometers, odometers, angle sensors, and geomagnetic sensors. The detection module may also include sensors related to its own operational safety, such as obstacle sensors, lift sensors, and battery pack temperature sensors. The detection module may also include sensors related to the external environment, such as ambient temperature sensors, ambient humidity sensors, light sensors, and rain sensors.

[0167] The interaction module is configured to at least receive user-input control commands, issue information that the user needs to perceive, and communicate with other systems or devices to send and receive information. In this embodiment, the interaction module includes an input device installed on the autonomous operating device for receiving user-input control commands, typically such as a control panel or emergency stop button; the interaction module also includes a display screen, indicator lights, and / or a buzzer installed on the autonomous operating device to make the information perceptible to the user through light or sound. In other embodiments, the interaction module includes a communication module installed on the autonomous operating device and a terminal device independent of the autonomous operating device, such as a mobile phone, computer, or network server; user control commands or other information can be input on the terminal device and reach the autonomous operating device via wired or wireless communication modules.

[0168] The control module typically includes at least one processor and at least one non-volatile memory. The memory stores pre-written computer programs or instruction sets, and the processor controls the execution of actions such as movement and operation of the autonomous operating device according to the computer programs or instruction sets. Furthermore, the control module can also control and adjust the corresponding behavior of the autonomous operating device and modify parameters in the memory based on signals from the detection module and / or user control commands.

[0169] The boundary is used to define the working area of ​​the robot system and typically includes an outer boundary. In some embodiments, the boundary also includes an inner boundary. The autonomous operating device is confined to move and operate within the outer boundary, outside the inner boundary, or between the outer and inner boundaries. The boundary can be physical, typically such as a wall, fence, or railing; the boundary can also be virtual, typically such as a virtual boundary signal emitted by a boundary signal generator, which is usually an electromagnetic or optical signal, or, for autonomous operating devices equipped with positioning devices (such as satellite positioning devices, visual positioning devices, lidar positioning devices, etc.), a virtual boundary set in an electronic map, exemplarily formed by two-dimensional or three-dimensional coordinates. In some embodiments, the boundary is constructed as a closed energized wire electrically connected to the boundary signal generator, which is typically located within a docking station. In some embodiments, the autonomous operating device is equipped with a vision module capable of distinguishing between grass and non-grass boundaries, using the vision module to determine the boundary of the working area.

[0170] The docking stations are typically constructed on or within the boundary to provide parking for autonomous operating equipment, and in particular, to supply energy to the autonomous operating equipment parked at the docking stations.

[0171] The third embodiment of the present invention relates to a non-transitory computer-readable storage medium storing processor-executable instructions configured to enable the processor of an autonomous operating device to execute an obstacle avoidance control method as described in the first or second embodiment.

[0172] The fourth embodiment of the present invention relates to a computer software product, including a computer program / instruction, which, when executed by a processor, implements the obstacle avoidance control method in the first or second embodiment.

[0173] The preferred embodiments of the present invention have been described in detail above, but it should be understood that, if necessary, aspects of the embodiments can be modified to utilize aspects, features, and concepts from various patents, applications, and publications to provide other embodiments.

[0174] In light of the detailed description above, these and other changes can be made to the embodiments. Generally, the terminology used in the claims should not be considered limited to the specific embodiments disclosed in the specification and claims, but should be understood to include all possible embodiments together with the full scope of equivalents enjoyed by these claims.

Claims

1. An obstacle avoidance control method, characterized in that, Applied to autonomous operating equipment; the method includes: During path following operations, obstacles in the surrounding environment are detected in real time based on sensors, and the detected obstacles are identified. When an obstacle cannot be identified, it is classified as a first type of obstacle, and a first obstacle avoidance strategy is executed to avoid the first type of obstacle; wherein, the first type of obstacle is an obstacle that cannot be identified.

2. The obstacle avoidance control method according to claim 1, characterized in that, The process of executing the first obstacle avoidance strategy to avoid the first type of obstacle includes the following steps: The current driving speed is reduced to the first speed, while the status of the first type of obstacle is detected in real time based on the sensor. When the first type of obstacle is detected to have disappeared, the current driving speed will be restored from the first speed to the original driving speed before the deceleration and the vehicle will continue to drive. When the state of the first type of obstacle is detected as not having disappeared, continue driving at the first speed until a collision occurs with the first type of obstacle, then perform obstacle avoidance maneuver.

3. The obstacle avoidance control method according to claim 1, characterized in that, The process of executing the first obstacle avoidance strategy to avoid the first type of obstacle includes the following steps: Directly implement non-contact obstacle avoidance strategies.

4. The obstacle avoidance control method according to claim 1, characterized in that, After executing the first obstacle avoidance strategy to avoid the first type of obstacle, the method further includes: Mark the smallest area containing the first type of obstacle in the working map as the area to be re-inspected; wherein, the first type of obstacle is at least on the pre-planned Nth following path, and the Nth following path is the following path when the first type of obstacle is first detected during the path following operation, and N is a positive integer.

5. The obstacle avoidance control method according to claim 4, further comprising: After the autonomous operating equipment completes the pre-planned Nth following path, it continues to follow the N+1th following path and monitors in real time whether the first type of obstacle detected on the Nth following path has disappeared. If the first type of obstacle is detected to have disappeared, then supplementary work will be carried out on the area to be re-inspected during the operation of following the N+1th following path; If the first type of obstacle is detected to have not disappeared, the obstacle-not-disappeared strategy is executed.

6. The obstacle avoidance control method according to claim 5, characterized in that, If the first type of obstacle is detected as not having disappeared, the execution of the obstacle not-disappeared strategy includes: If the first type of obstacle is detected to have not disappeared and is on the N+1th following path, the first obstacle avoidance strategy is executed again to avoid the first type of obstacle.

7. The obstacle avoidance control method according to claim 5, characterized in that, If the first type of obstacle is detected as not having disappeared, the execution of the obstacle not-disappeared strategy includes: If the first type of obstacle is detected to have not disappeared and is not on the N+1 following path, then continue to follow the N+1 following path for operation.

8. The obstacle avoidance control method according to claim 4, characterized in that, The area to be re-inspected occupies part of the following path from the Nth to the (N+Yth)th following path in the working map, where Y is an integer greater than or equal to 1; Follow the Nth to the (N+Y)th follow paths sequentially, and during the process of performing the follow operation on each specified follow path from the Nth to the (N+Y)th follow path: If the area to be re-inspected has been repaired, there is no need to detect in real time whether the first type of obstacle in the area to be re-inspected has disappeared; If the re-inspection area has not completed the supplementary work, the system will detect in real time whether the first type of obstacle in the re-inspection area has disappeared; if the first type of obstacle has been detected to have disappeared, the system will perform supplementary work on the re-inspection area while following the specified follow path; if the first type of obstacle has not been detected to have disappeared, the system will execute the first obstacle avoidance strategy again to avoid the first type of obstacle.

9. The obstacle avoidance control method according to claim 5 or 8, characterized in that, The specific method for performing supplementary work on the area to be re-inspected during the operation following the Mth follow path is as follows: Based on the following path covered by the area to be re-inspected and the trajectory position of the Mth following path adjacent to the area to be re-inspected, a trajectory plan for supplementary work on the area to be re-inspected is obtained; The re-inspection area is supplemented according to the trajectory planning; wherein, the Mth following path is the following path when the first type of obstacle is first detected to disappear, and M is an integer greater than 1.

10. The obstacle avoidance control method according to claim 9, characterized in that, The method further includes: after completing the supplementary work on the area to be re-inspected according to the trajectory plan, the autonomous operating equipment returns to the trajectory position adjacent to the area to be re-inspected on the Mth following path, and continues to follow the remaining Mth following path to perform following path work.

11. The obstacle avoidance control method according to claim 1, characterized in that, The method further includes: When a detected obstacle is identified as a dynamic obstacle, the autonomous operating device is controlled to execute a second obstacle avoidance strategy. When a detected obstacle is identified as a static obstacle, the autonomous operating device is controlled to execute a third obstacle avoidance strategy.

12. The obstacle avoidance control method according to claim 11, characterized in that, Controlling the autonomous operating equipment to execute the second obstacle avoidance strategy includes: During the process of the autonomous operating equipment moving towards the detected dynamic obstacle: If the distance between the autonomous operating equipment and the detected dynamic obstacle is detected in real time to meet the Kth deceleration condition among P deceleration levels, the current driving speed is reduced for the Kth time before driving continues, and the state of the dynamic obstacle is detected in real time; wherein, if the state of the dynamic obstacle is detected as having disappeared, the speed before the first deceleration is restored; if the state of the dynamic obstacle is detected as not having disappeared, the driving speed after the Kth deceleration is maintained and driving continues; 1≤K<P, P is an integer greater than 1, and each deceleration level condition is: the distance between the autonomous operating equipment and the dynamic obstacle reaches the corresponding preset distance, and the preset distance corresponding to the P deceleration levels decreases sequentially; If the distance between the autonomous operating equipment and the detected dynamic obstacle is detected in real time and meets the deceleration condition of level P, then the non-contact obstacle avoidance strategy is executed.

13. The obstacle avoidance control method according to claim 11, characterized in that, Controlling the autonomous operating equipment to execute a third obstacle avoidance strategy includes: Control the autonomous operating equipment to execute a non-contact obstacle avoidance strategy.

14. The obstacle avoidance control method according to claim 11, characterized in that, The process of controlling the autonomous operating equipment to execute the third obstacle avoidance strategy also includes: The state of the static obstacle is detected in real time. If the static obstacle is detected to be in a moved state, the system switches to execute the fourth obstacle avoidance strategy; otherwise, the third obstacle avoidance strategy continues to be executed.

15. The obstacle avoidance control method according to claim 14, characterized in that, The execution of the fourth obstacle avoidance strategy includes: Obtain the direction of movement of the static obstacle in the moving state; When the direction of movement is towards the autonomous operating equipment, the autonomous operating equipment is controlled to detour around the static obstacle according to a preset obstacle detour range; When the direction of movement is away from the autonomous operating device, the autonomous operating device is controlled to stop executing the third obstacle avoidance strategy and return to the following path to continue operation.

16. The obstacle avoidance control method according to claim 1, characterized in that, The identification of detected obstacles includes: The detected obstacles are compared with a predefined obstacle library; If the currently detected obstacle is not found in the predefined obstacle library, then the currently detected obstacle is determined to be a Class I obstacle.

17. The obstacle avoidance control method according to claim 11, characterized in that, The sensor is a non-contact obstacle detector.

18. The obstacle avoidance control method according to claim 17, characterized in that, The non-contact obstacle detector is a vision module.

19. An autonomous operating device, characterized in that, Used to perform the obstacle avoidance control method according to any one of claims 1 to 18.

20. A non-transitory computer-readable storage medium, characterized in that, The non-transitory computer-readable storage medium stores processor-executable instructions configured to enable the processor of the autonomous operating device to execute the obstacle avoidance control method as described in any one of claims 1 to 18.

21. A computer software product, comprising a computer program / instructions, characterized in that, When the computer program / instruction is executed by the processor, it implements the obstacle avoidance control method as described in any one of claims 1 to 18.

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