Robot obstacle avoidance method, device and equipment and storage medium

Abstract

The invention discloses a robot obstacle avoidance method, device and equipment and a storage medium. The method comprises the steps that whether the obstacle avoidance size of the robot changes or not is determined according to collected data of a sensor; under the condition that the obstacle avoidance size changes, updating the obstacle avoidance size according to the collected data to obtain the updated obstacle avoidance size; and controlling the robot to avoid the obstacle based on the updated obstacle avoidance size. According to the technical scheme of the embodiment of the invention, stable obstacle avoidance of the robot can be realized.

Description

Technical Field

[0001] The present invention relates to the field of robot technology, and in particular to a robot obstacle avoidance method, device, equipment and storage medium. Background Art

[0002] With the continuous development of science and technology, robots are being used more and more widely, providing great convenience for people’s work and life. For example, food delivery robots in the catering industry and material transportation robots in industrial production.

[0003] To ensure the safety of the application, the robot needs to detect and avoid obstacles during movement. When the robot moves in a complex environment, it often needs to avoid obstacles to the extreme, for example, passing through a narrow obstacle avoidance channel that is slightly smaller than the width of the robot.

[0004] In the prior art, for robots that need to load items for transportation, it is often the case that the items being transported are larger or placed improperly, causing them to exceed the robot's pallet range. At this time, the robot avoids obstacles according to the original size, and is prone to collisions due to the items that exceed the range. Summary of the invention

[0005] The present invention provides a robot obstacle avoidance method, device, equipment and storage medium to solve the problem that an object located on a robot body is identified as an obstacle, thereby affecting the operation of the robot.

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

[0007] According to the data collected by the sensor, determine whether the robot's obstacle avoidance size has changed;

[0008] When the obstacle avoidance size changes, the obstacle avoidance size is updated according to the collected data to obtain an updated obstacle avoidance size;

[0009] Based on the updated obstacle avoidance size, the robot is controlled to avoid obstacles.

[0010] According to another aspect of the present invention, there is provided a robot obstacle avoidance device, comprising:

[0011] The obstacle avoidance size detection module is used to determine whether the robot's obstacle avoidance size has changed based on the data collected by the sensor;

[0012] An obstacle avoidance size updating module, used to update the obstacle avoidance size according to the collected data when the obstacle avoidance size changes, so as to obtain an updated obstacle avoidance size;

[0013] The robot obstacle avoidance module is used to control the robot to avoid obstacles based on the updated obstacle avoidance size.

[0014] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

[0015] at least one processor; and

[0016] a memory communicatively connected to the at least one processor; wherein,

[0017] The memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the robot obstacle avoidance method described in any embodiment of the present invention.

[0018] According to another aspect of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the robot obstacle avoidance method described in any embodiment of the present invention when executed.

[0019] The technical solution of the embodiment of the present invention determines whether the obstacle avoidance size of the robot has changed based on the collected data of the sensor. When the obstacle avoidance size of the robot has changed, the obstacle avoidance size is updated according to the collected data. Finally, the robot is controlled to avoid obstacles based on the updated obstacle avoidance size, and stable obstacle avoidance of the robot is achieved based on the updated obstacle avoidance size.

[0020] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0022] Figure 1a is a flow chart of a robot obstacle avoidance method provided according to Embodiment 1 of the present invention;

[0023] Figure 1b is a schematic diagram of updating the obstacle avoidance size of a robot provided according to the first embodiment of the present invention;

[0024] Figure 2a is a flow chart of a robot obstacle avoidance method provided according to Embodiment 2 of the present invention;

[0025] Figure 2b is a flowchart of updating the obstacle avoidance size of the robot provided in the second embodiment of the present invention;

[0026] Figure 2c is a schematic diagram of the sensor installation position provided according to the second embodiment of the present invention;

[0027] Figure 3a is a flow chart of a robot obstacle avoidance method provided according to Embodiment 3 of the present invention;

[0028] Figure 3b is a flowchart of robot obstacle avoidance provided according to Embodiment 3 of the present invention;

[0029] Figure 4 is a schematic structural diagram of a robot obstacle avoidance device provided according to a fourth embodiment of the present invention;

[0030] Figure 5 It is a schematic diagram of the structure of an electronic device for implementing the robot obstacle avoidance method according to an embodiment of the present invention. DETAILED DESCRIPTION

[0031] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in 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. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0032] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0033] Embodiment 1

[0034] Figure 1aA flowchart of a robot obstacle avoidance method is provided for the first embodiment of the present invention. This embodiment can be applied to update the robot's obstacle avoidance size according to the sensor collection data, and control the robot's obstacle avoidance based on the updated obstacle avoidance size. The method can be executed by a robot obstacle avoidance device, which can be implemented in the form of hardware and / or software. The robot obstacle avoidance device can be configured in various general-purpose computing devices, for example, the general-purpose computing device can be a robot processor. Figure 1a As shown, the method includes:

[0035] S110: Determine whether the obstacle avoidance size of the robot has changed based on the data collected by the sensor.

[0036] Sensors can be installed on the left and right sides of the robot to detect obstacle information in the robot's environment. For example, the sensors are visual sensors or laser radars.

[0037] In a specific example, the sensor is a visual sensor installed on both sides of the robot's top storage tray, with one side of the stereoscopic vision cone close to the robot's storage tray and tilted downward. In this case, the sensor can be used to detect obstacles on the left and right sides of the robot. When the robot is an omnidirectional mobile robot, the sensor can avoid obstacles and prevent falling when the robot moves left and right. In addition, the visual sensor can also be installed on both sides of the robot's bottom storage tray and tilted upward. In this case, the sensor can be used to detect obstacles on the left and right sides of the robot, or for obstacle detection when the robot moves left and right.

[0038] The robot's obstacle avoidance size is used to indicate the size of obstacles that the robot needs to avoid. The robot generally moves forward, so the robot's obstacle avoidance size is the maximum width of the robot's left and right sides.

[0039] In an embodiment of the present invention, during the movement of the robot, the data collected by the sensor is used to determine whether the obstacle avoidance size of the robot has changed. Specifically, the data collected by the sensor is used to determine whether there is an obstacle close to the robot, that is, to detect whether there is an obstacle with a distance of 0 from the robot. When there is an obstacle close to the robot, it is further determined whether the obstacle is located above the robot body, for example, whether the obstacle is a decoration or extension of the robot itself, and whether the obstacle is an item placed in the robot tray that exceeds the edge of the tray. If the obstacle is located above the robot body, it is determined that the obstacle avoidance size of the robot has changed, otherwise, it is determined that the obstacle avoidance size of the robot has not changed. Optionally, object recognition, such as dish recognition, and the distance between the object and the robot can also be performed based on the data collected by the sensor to determine whether the obstacle is a dish placed on the robot.

[0040] Among them, it is possible to determine whether the obstacle is located on the robot body by obtaining the signal output by the robot extension detection device. For example, if the robot extension detection device outputs a high-level signal, it is determined that the obstacle is an extension of the robot itself. It is also possible to determine whether the obstacle is located on the robot body by controlling the movement of the robot. For example, during the movement of the robot, it is determined whether the shape and size of the obstacle collected by the sensor have changed. If there is no change, it is determined that the detected obstacle is located on the robot body.

[0041] In a specific example, Figure 1b As shown, for a food delivery robot with multiple layers of trays, data is collected by visual sensors arranged on both sides of the top tray of the robot and tilted downward. It is determined whether the obstacle point cloud data close to the edge of the robot tray is collected. If so, the size, shape and relative position of the obstacle point cloud at the edge of the current tray are recorded. If not, it is determined that the robot's obstacle avoidance size and obstacle avoidance center have not changed. Further, after recording the size, shape and relative position of the obstacle point cloud at the edge of the current tray, it is possible to further move in the opposite direction of the obstacle and determine whether the size, position and shape of the obstacle have changed during the movement. If so, it is determined that the robot's obstacle avoidance size has not changed. Otherwise, it is determined that the obstacle is located above the robot body, and the robot's obstacle avoidance size and obstacle avoidance center have changed due to the obstacle.

[0042] The reverse movement along the obstacle means that when the obstacle is located on the left side of the robot's storage tray, the robot moves to the right; when the obstacle is located on the right side of the robot's storage tray, the robot moves to the left.

[0043] S120: When the obstacle avoidance size changes, the obstacle avoidance size is updated according to the collected data to obtain an updated obstacle avoidance size.

[0044] In the embodiment of the present invention, when it is determined that the obstacle avoidance size of the robot has changed, the obstacle avoidance size of the robot is further updated according to the collected data of the sensor to obtain an updated obstacle avoidance size. Specifically, the size of the obstacle close to the edge of the robot is determined according to the collected data, and the current obstacle avoidance size of the robot is updated according to the size of the obstacle to obtain an updated obstacle avoidance size.

[0045] In a specific example, for a food delivery robot with a multi-layer tray, when an obstacle point cloud is detected at the edge of the tray and it is determined that the obstacle point cloud is located above the robot body, the robot's current obstacle avoidance size is updated according to the obstacle point cloud to obtain an updated obstacle avoidance size. For example, the current obstacle avoidance size is the width of the robot body, and the updated obstacle avoidance size is the sum of the robot body width and the size of the obstacle point cloud in the robot width direction.

[0046] S130: Control the robot to avoid obstacles based on the updated obstacle avoidance size.

[0047] In the embodiment of the present invention, after the obstacle avoidance size of the robot is updated, the robot is controlled to avoid obstacles based on the updated obstacle avoidance size. Specifically, the robot's obstacle avoidance can be divided into ordinary obstacle avoidance situations such as avoiding obstacles that are far away or small in size, running in a wider channel, and extreme obstacle avoidance situations such as passing through a narrow channel that is slightly different from the robot's width.

[0048] In the case of normal obstacle avoidance, when the robot's obstacle avoidance size changes slightly, the obstacle avoidance effect is less affected. In the case of extreme obstacle avoidance, a slight change in the robot's obstacle avoidance size may cause a collision or obstacle avoidance failure. Therefore, when performing extreme obstacle avoidance, for example, when passing through a narrow channel, it is possible to determine whether the robot can pass through the narrow channel based on the updated obstacle avoidance size. If it can pass, the robot is controlled to pass through the narrow channel to achieve stable obstacle avoidance of the robot. Among them, a narrow channel can be a channel where the difference between the channel width and the robot width is less than the width threshold.

[0049] In a specific example, after obtaining the updated obstacle avoidance size, if the robot detects through sensors such as radar that there is a narrow passage with a width less than a set width threshold in the robot's route, it first determines whether the width of the narrow passage is greater than the updated obstacle avoidance size. If so, the robot is controlled to pass through the narrow passage to avoid collision with the edge of the narrow passage. When the robot is running in the narrow passage, the robot is controlled to avoid obstacles according to the updated obstacle avoidance size to achieve stable obstacle avoidance of the robot.

[0050] The technical solution of the embodiment of the present invention determines whether the obstacle avoidance size of the robot has changed based on the collected data of the sensor. When the obstacle avoidance size of the robot has changed, the obstacle avoidance size is updated according to the collected data. Finally, the robot is controlled to avoid obstacles based on the updated obstacle avoidance size, which solves the problem that objects located on the robot body are identified as obstacles and thus affect the normal movement of the robot. The robot can achieve stable obstacle avoidance based on the updated obstacle avoidance size.

[0051] Embodiment 2

[0052] Figure 2aThis is a flowchart of a robot obstacle avoidance method provided in Embodiment 2 of the present invention. This embodiment further refines the above embodiment and provides specific steps for determining whether the robot's obstacle avoidance size has changed based on the collected data of the sensor, and updating the obstacle avoidance size based on the collected data to obtain the updated obstacle avoidance size. Figure 2a As shown, the method includes:

[0053] S210: In response to a change in the items in the storage tray on the robot body, determine whether there is a close obstacle on the edge of the storage tray based on the collected data.

[0054] Close-range obstacles refer to obstacles that may be at a distance of 0 from the edge of the storage tray according to the collected data, that is, obstacles that are in contact with the edge of the storage tray. For example, it may be a table and chair placed on the ground captured by the sensor, and the table and chair are located at the edge of the storage tray in the collected image.

[0055] For example, for robots equipped with a tray, users are often required to place items to be delivered in the tray, for example, placing dishes on the tray of a food delivery robot. If the user does not operate properly, or the dishes are large, or multiple dishes are placed on the same layer, part of the items to be delivered may be inside the tray, while the other part may exceed the edge of the tray. At this time, the robot's sensor will also detect close obstacles.

[0056] In an embodiment of the present invention, a method for detecting obstacles located above the robot body and beyond the edge of the storage tray is provided, such as Figure 2b As shown: when the items in the storage tray on the robot body change, the sensor first collects data, and determines whether there are close obstacles on the edge of the storage tray based on the collected data, so as to determine whether the placed items exceed the edge of the storage tray. Specifically, the change of the items in the storage tray can be determined by the user's placement or retrieval completion command, and the built-in item detection sensor of the storage tray can also be used to detect whether the items in the storage tray have changed.

[0057] After the items change, there may be a situation where the items exceed the edge of the storage tray. At this time, the sensor can collect data and determine whether there are close obstacles on the edge of the storage tray based on the collected data. Only performing close obstacle detection when the items in the storage tray change can save computing resources while ensuring the detection effect, compared with continuous close obstacle detection.

[0058] In a specific example, for a food delivery robot with a multi-layer storage tray, after receiving a meal placement completion instruction or a meal pickup completion instruction initiated by a user, the robot uses a visual sensor to detect whether there are any close obstacles on both sides of the robot that are connected to the edge of the storage tray.

[0059] Optionally, the sensor includes a visual sensor;

[0060] Optionally, the sensors are installed on both sides of the top storage tray of the robot, the sensors are tilted downward, and the robot is provided with an omnidirectional mobile chassis.

[0061] In the above two optional embodiments, the types and installation methods of sensors are provided, such as Figure 2c As shown, the sensor includes a visual sensor, which can be installed on both sides of the robot's top storage tray and tilted downward so that the detection area can cover the edges of the lower storage trays, thereby detecting whether there are items placed beyond the edge of the storage tray. The robot is provided with an omnidirectional mobile chassis, so that its movement is not limited to the front and back directions, but can also move left and right. During the robot's left and right movement, it can also avoid obstacles and prevent falling left and right through the data collected by the visual sensor. Compared with the setting on the head, the detection range of the tray edge is larger, and the obstacle avoidance and anti-falling functions during lateral movement can be better realized.

[0062] S220: When there is a short-distance obstacle at the edge of the storage tray, determine whether the short-distance obstacle is located above the robot body through the movement of the robot.

[0063] In the embodiment of the present invention, when a close-range obstacle is detected at the edge of the storage tray, in order to determine whether the current close-range obstacle is located on the robot body, the robot can be controlled to move, and the sensor continues to collect data during the movement. According to the collected data, if it is determined that the close-range obstacle changes its relative position with the storage tray, or changes its shape or size during the movement of the robot, it can be determined that the close-range obstacle is not located on the robot body. Otherwise, it is determined that the close-range obstacle is located on the robot body.

[0064] When a close-range obstacle is detected, the robot's movement is used to determine whether the obstacle is located on the robot body. No additional sensors are required, and the robot's own movement can be used to determine whether the obstacle is on the robot body, saving costs. In the prior art, in order to avoid misidentifying detected objects beyond the tray as obstacles on the road and affecting the normal movement of the robot, the ability to detect close obstacles is usually sacrificed, resulting in the robot being unable to stably complete extreme obstacle avoidance such as narrow passages. The embodiments of the present invention can promptly determine whether the obstacle is located on the robot body, avoiding the problem of misidentifying close-range obstacles on the robot body as obstacles on the road and affecting the normal movement of the robot, without sacrificing the close-range detection capability and without affecting the robot's extreme obstacle avoidance.

[0065] Optionally, determining whether a close-range obstacle is located above the robot body through the movement of the robot includes:

[0066] According to the relative position of the close-range obstacle and the storage tray, the robot's moving direction is determined, and the robot moves according to the moving direction;

[0067] Get the size and shape of nearby obstacles while moving;

[0068] If the size and shape of the close-range obstacle do not change during the movement of the robot, it is determined that the close-range obstacle is located above the robot body.

[0069] In this optional embodiment, a specific method is provided for determining whether a close-range obstacle is located above the robot body through the movement of the robot: first, the size and shape of the close-range obstacle is recorded, and the movement direction of the robot is determined based on the relative position of the close-range obstacle and the storage tray, and the robot moves in the direction of movement according to the movement direction, and the size and shape of the close-range obstacle are continuously detected by the sensor during the movement. If the size and shape of the close-range obstacle do not change during the movement of the robot, it is determined that the close-range obstacle is located above the robot body. By determining whether a close-range obstacle is located on the robot body through the movement of the robot, the state of the close-range obstacle can be detected with a small amount of calculation, thereby improving the accuracy of obstacle detection.

[0070] In a specific example, the opposite direction of the close-range obstacle can be determined as the moving direction of the robot. For example, when the close-range obstacle is located on the left side of the storage tray, the moving direction of the robot is determined to be the right; when the close-range obstacle is located on the right side of the storage tray, the moving direction of the robot is determined to be the left. If there are close-range obstacles on both the left and right sides of the storage tray, the moving direction of the robot can be determined to be forward or backward. In addition, the moving speed of the robot can be set to 0.1 m / s, and the moving distance can be set to 0.2 m. Using the opposite direction of the close-range obstacle as the moving direction of the robot can improve safety and avoid accidents such as collisions when the close-range obstacle is an obstacle on the road.

[0071] S230: When a close-range obstacle is located above the robot body, determine whether the obstacle avoidance size of the robot has changed.

[0072] In the embodiment of the present invention, when it is determined that the short-distance obstacle is located above the robot body, it means that the short-distance obstacle is an item placed in the storage tray that exceeds the edge of the storage tray. At this time, due to the influence of the item exceeding the edge of the storage tray, the obstacle avoidance size of the robot changes.

[0073] S240: When the obstacle avoidance size changes, determine the size of the close-range obstacle at the edge of the storage tray according to the collected data.

[0074] In the embodiment of the present invention, when the obstacle avoidance size changes, in order to ensure stable obstacle avoidance of the robot, the obstacle avoidance size is updated, so as to control the robot to avoid obstacles according to the updated obstacle avoidance size. Specifically, the size of the close-range obstacle at the edge of the storage tray is determined through the data collected by the sensor. Exemplarily, the current obstacle avoidance size is the width of the robot, and the size of the close-range obstacle in the width direction of the robot is obtained through the data collected by the visual sensor.

[0075] S250: updating the obstacle avoidance size according to the size of the close-range obstacle to obtain an updated obstacle avoidance size.

[0076] In an embodiment of the present invention, after obtaining the size of a close-range obstacle, the obstacle avoidance size is updated according to the size of the close-range obstacle to obtain an updated obstacle avoidance size. For example, the current obstacle avoidance size is the width of the robot body, and the updated obstacle avoidance size is the sum of the width of the robot body and the size of the obstacle point cloud in the width direction of the robot. By updating the obstacle avoidance size of the robot according to the size of the close-range obstacle at the edge of the storage tray, it is possible to avoid the close-range obstacle located on the tray from being identified as an obstacle that needs to be avoided, thereby affecting the normal operation of the robot, without sacrificing the close-range obstacle detection capability.

[0077] S260: Control the robot to avoid obstacles based on the updated obstacle avoidance size.

[0078] The technical solution of the embodiment of the present invention is that when the items in the storage tray on the robot body change, it is determined whether there is a close-range obstacle on the edge of the storage tray based on the sensor data collected. When there is a close-range obstacle on the edge of the storage tray, it is determined whether the close-range obstacle is located above the robot body through the movement of the robot. When the close-range obstacle is located above the robot body, it is determined that the obstacle avoidance size of the robot has changed, which can prevent the sensor from always identifying the close-range obstacle on the robot body and affecting the normal movement of the robot. In addition, when the obstacle avoidance size changes, the size of the close-range obstacle on the edge of the storage tray is determined based on the collected data, and the obstacle avoidance size is updated based on the size of the close-range obstacle. When there is a close-range obstacle on the robot body that exceeds the edge of the tray, stable obstacle avoidance can be achieved based on the updated obstacle avoidance size to avoid robot collision.

[0079] Embodiment 3

[0080] Figure 3a This is a flowchart of a robot obstacle avoidance method provided in Embodiment 3 of the present invention. This embodiment further refines the above embodiment and provides specific steps for controlling the robot to avoid obstacles based on the updated obstacle avoidance size. Figure 3a As shown, the method includes:

[0081] S310: Determine whether the obstacle avoidance size of the robot has changed based on the data collected by the sensor.

[0082] S320: When the obstacle avoidance size changes, the obstacle avoidance size is updated according to the collected data to obtain an updated obstacle avoidance size.

[0083] S330: Detect whether there is an extreme passage in the current route of the robot by using an obstacle avoidance sensor provided on the robot.

[0084] The limit passage refers to a passage where the remaining space between the robot and the obstacle on both sides is less than a threshold when the robot passes through. Exemplarily, the limit passage may be a passage where the passage width is less than a set width threshold, for example, the set width threshold is 0.9 meters, or a passage where the difference between the passage width and the robot width is less than a set threshold, for example, the set threshold is 0.2 meters.

[0085] The obstacle avoidance sensor is used to detect obstacles in the robot's route, and the obstacle avoidance sensor can be a laser radar and / or a stereo vision sensor. Exemplarily, the obstacle avoidance sensor is a laser radar arranged in front of the robot for detecting obstacles in front of the robot during its travel.

[0086] In the embodiment of the present invention, Figure 3b As shown, during the movement of the robot, the obstacle avoidance sensor is used to detect in real time whether there is an extreme passage in the current route of the robot. Specifically, the point cloud data of the laser radar is used to detect whether there is an extreme passage with a width value less than a set threshold in the robot's route. It is also possible to detect whether there is an extreme passage with a width value less than a set threshold in the robot's route based on the updated obstacle avoidance size.

[0087] Optionally, an obstacle avoidance sensor provided on the robot is used to detect whether there is an extreme passage in the current route of the robot, including at least one of the following:

[0088] The obstacle avoidance sensor is used to detect whether there is a limit passage whose width is less than a set width threshold in the robot's route;

[0089] The obstacle avoidance sensor is used to detect whether there is a limit passage in the robot's route, the difference between the width value and the updated obstacle avoidance size being less than the set pass threshold.

[0090] In this optional embodiment, a specific method is provided for detecting whether there is an extreme passing channel in the current route of the robot by means of an obstacle avoidance sensor provided on the robot: the obstacle avoidance sensor can be used to detect whether there is an extreme passing channel in the route of the robot whose width value is less than a set width threshold. The set width threshold can be a threshold determined according to the width of the robot, for example, the sum of the robot width and a constant, and the constant can be determined according to multiple experiments. The obstacle avoidance sensor can also be used to detect whether there is an extreme passing channel in the route of the robot whose width value and the difference between the updated obstacle avoidance size are less than the set passage threshold. By pre-detecting whether there is an extreme passing channel in the route of the robot, it can be determined in advance whether the robot can pass through the extreme passing channel to avoid collisions or scratches during travel.

[0091] S340: When there is a limit passage in the travel route, control the robot to avoid obstacles based on the size of the limit passage and the updated obstacle avoidance size.

[0092] In the embodiment of the present invention, when there is a limit passage in the route, before the robot enters the limit passage, it can be determined whether the size L of the limit passage is greater than the updated obstacle avoidance size M. If so, it is determined that the robot can pass through the limit passage, and the robot is controlled to avoid obstacles. Obstacle avoidance is performed according to the updated obstacle avoidance size, ensuring that the robot passes through the limit passage smoothly, and improving the robot's passage stability in complex environments.

[0093] It is worth noting that when the robot passes through the limit passage, it can reduce its moving speed to ensure safe operation. If there is no limit passage on the robot's route, for example, when the passage is wide, the dishes that exceed the limit have little impact on the robot's operation, and the robot's obstacle avoidance size does not need to be updated. The robot can avoid obstacles according to the original obstacle avoidance size. At this time, the robot can be guaranteed to run quickly in the center and improve efficiency.

[0094] Optionally, based on the size of the limit passage and the updated obstacle avoidance size, control the robot to avoid obstacles, including:

[0095] Determining whether the robot can pass through the limit passage according to the size of the limit passage and the updated obstacle avoidance size;

[0096] In the case where the robot can pass through the limit passage, the obstacle avoidance center of the robot is determined according to the updated obstacle avoidance size, and the passage center of the limit passage is determined according to the size of the limit passage;

[0097] After aligning the obstacle avoidance center of the robot with the passage center of the extreme passing channel, the robot is controlled to pass through the extreme passing channel.

[0098] In this optional embodiment, a specific method for controlling the robot to avoid obstacles based on the size of the limit passage and the updated obstacle avoidance size is provided, as follows: Figure 3b As shown: First, according to the size of the limit passage and the updated obstacle avoidance size, determine whether the robot can pass through the limit passage. Specifically, the difference between the size of the limit passage and the updated obstacle avoidance size can be calculated. If the difference is greater than 0, it indicates that the robot can pass through the limit passage. Further, the obstacle avoidance center of the robot is determined according to the updated obstacle avoidance size, and the passage center of the limit passage is determined according to the size of the limit passage. For example, the robot passes through the limit passage by moving forward, and the robot obstacle avoidance center is obtained by calculating the center of the robot width (including the size of close obstacles located on the robot body and beyond the edge of the robot storage tray), and the center of the limit passage is the passage center of the passage. Finally, it is necessary to align the robot obstacle avoidance center with the passage center of the limit passage, and then control the robot to pass through the limit passage. Based on the updated obstacle avoidance size, the robot can be controlled to stably pass through narrow passages when the difference between the robot width and the passage width is small, thereby improving motion stability and reducing collisions.

[0099] It is worth noting that when the robot's obstacle avoidance size changes, the obstacle avoidance center also changes accordingly. For example, the robot's initial obstacle avoidance size is the width of the robot body, and the obstacle avoidance center is the center of the robot's width. If the items placed in the robot's storage tray exceed the left edge of the storage tray, the robot's obstacle avoidance size increases, and the obstacle avoidance center also moves accordingly. Updating the robot's obstacle avoidance center can control the robot to keep the obstacle avoidance center aligned with the center of the channel when passing through the limit channel. That is, if the robot was running in the center before, it may now run closer to one side of the channel to ensure that the robot can pass through the channel stably.

[0100] The technical solution of the embodiment of the present invention is to detect whether there is a limit passing channel in the current route of the robot through an obstacle avoidance sensor arranged on the robot after determining that the obstacle avoidance size of the robot has changed and obtaining an updated obstacle avoidance size. When there is a limit passing channel in the route, the robot is controlled to avoid obstacles based on the size of the limit passing channel and the updated obstacle avoidance size. When the obstacle avoidance size of the robot has changed, the robot can stably pass through the limit passing channel, thereby improving the robot's ability to pass through complex environments.

[0101] Embodiment 4

[0102] Figure 4 This is a schematic diagram of the structure of a robot obstacle avoidance device provided in Embodiment 4 of the present invention. Figure 4 As shown, the device comprises:

[0103] The obstacle avoidance size detection module 410 is used to determine whether the obstacle avoidance size of the robot has changed based on the data collected by the sensor;

[0104] The obstacle avoidance size updating module 420 is used to update the obstacle avoidance size according to the collected data when the obstacle avoidance size changes, so as to obtain an updated obstacle avoidance size;

[0105] The robot obstacle avoidance module 430 is used to control the robot to avoid obstacles based on the updated obstacle avoidance size.

[0106] The technical solution of the embodiment of the present invention determines whether the obstacle avoidance size of the robot has changed based on the collected data of the sensor. When the obstacle avoidance size of the robot has changed, the obstacle avoidance size is updated according to the collected data. Finally, the robot is controlled to avoid obstacles based on the updated obstacle avoidance size, which solves the problem that objects located on the robot body are identified as obstacles and thus affect the normal movement of the robot. The robot can achieve stable obstacle avoidance based on the updated obstacle avoidance size.

[0107] Optionally, the sensor includes a visual sensor, and the obstacle avoidance size detection module 410 includes:

[0108] An obstacle detection unit, configured to respond to a change in the items in the storage tray on the robot body and determine whether there is a close-range obstacle at the edge of the storage tray based on the collected data;

[0109] A body obstacle judgment unit, used to determine whether a close-range obstacle is located on the robot body by moving the robot when there is a close-range obstacle at the edge of the storage tray;

[0110] The obstacle avoidance size detection unit is used to determine that the obstacle avoidance size of the robot changes when the close-range obstacle is located above the robot body.

[0111] Optionally, the main body obstacle judgment unit is specifically used to:

[0112] Determining a moving direction of the robot according to a relative position between the close-range obstacle and the storage tray, and moving according to the moving direction;

[0113] Acquire the size and shape of the close-range obstacle during the movement;

[0114] If the size and shape of the short-distance obstacle do not change during the movement of the robot, it is determined that the short-distance obstacle is located above the robot body.

[0115] Optionally, the robot obstacle avoidance module 430 includes:

[0116] The limit passage detection unit is used to detect whether there is a limit passage in the current route of the robot through an obstacle avoidance sensor arranged on the robot;

[0117] The robot obstacle avoidance unit is used to control the robot to avoid obstacles based on the size of the limit passage and the updated obstacle avoidance size when there is a limit passage in the travel route.

[0118] Optional, robot obstacle avoidance unit, specifically used for:

[0119] Determining whether the robot can pass through the limit passage according to the size of the limit passage and the updated obstacle avoidance size;

[0120] In the case where the robot can pass through the limit passage, determining the obstacle avoidance center of the robot according to the updated obstacle avoidance size, and determining the passage center of the limit passage according to the size of the limit passage;

[0121] After the obstacle avoidance center of the robot is aligned with the passage center of the extreme passage, the robot is controlled to pass through the extreme passage.

[0122] Optionally, the limit channel detection unit is specifically configured to perform at least one of the following operations:

[0123] By using the obstacle avoidance sensor, it is detected whether there is a limit passage with a width value less than a set width threshold in the robot's travel route;

[0124] The obstacle avoidance sensor is used to detect whether there is a limit passage in the robot's route, the difference between the width value and the updated obstacle avoidance size being less than a set passage threshold.

[0125] Optionally, the obstacle avoidance size updating module 420 is specifically used for:

[0126] Determining the size of the obstacles at a close distance to the edge of the storage tray according to the collected data;

[0127] The obstacle avoidance size is updated according to the size of the close-range obstacle to obtain an updated obstacle avoidance size.

[0128] Optionally, sensors are installed on both sides of the top storage tray of the robot, the sensors are tilted downward, and the robot is provided with an omnidirectional mobile chassis.

[0129] The robot obstacle avoidance device provided in the embodiment of the present invention can execute the robot obstacle avoidance method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0130] Embodiment 5

[0131] Figure 5 A schematic diagram of the structure of an electronic device 10 that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0132] like Figure 5As shown, the electronic device 10 includes at least one processor 11, and a memory connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 to the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0133] A number of components in the electronic device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0134] The processor 11 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as a robot obstacle avoidance method.

[0135] In some embodiments, the robot obstacle avoidance method may be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the robot obstacle avoidance method described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to execute the robot obstacle avoidance method in any other appropriate manner (e.g., by means of firmware).

[0136] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0137] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0138] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in combination with an instruction execution system, device or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0139] To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0140] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0141] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0142] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0143] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A robot obstacle avoidance method, It is characterized in that include: According to the data collected by the sensor, determine whether the robot's obstacle avoidance size has changed; When the obstacle avoidance size changes, the obstacle avoidance size is updated according to the collected data to obtain an updated obstacle avoidance size; Based on the updated obstacle avoidance size, the robot is controlled to avoid obstacles.

2. The method according to claim 1, It is characterized in that The sensor includes a visual sensor, and determining whether the obstacle avoidance size of the robot changes according to the collected data of the sensor includes: In response to a change in the items in the storage tray on the robot body, determining whether there is a close-range obstacle at the edge of the storage tray based on the collected data; In the case where there is a close-range obstacle at the edge of the storage tray, determining whether the close-range obstacle is located on the robot body through the movement of the robot; When the short-range obstacle is located above the robot body, it is determined that the obstacle avoidance size of the robot changes.

3. The method according to claim 2, It is characterized in that Determining whether the short-range obstacle is located above the robot body by moving the robot includes: Determining a moving direction of the robot according to a relative position between the close-range obstacle and the storage tray, and moving according to the moving direction; Acquire the size and shape of the close-range obstacle during the movement; If the size and shape of the short-distance obstacle do not change during the movement of the robot, it is determined that the short-distance obstacle is located above the robot body.

4. The method according to claim 1, It is characterized in that Based on the updated obstacle avoidance size, controlling the robot to avoid obstacles includes: By using the obstacle avoidance sensor installed on the robot, it is detected whether there is an extreme passage in the robot's current route; When there is a limit passage in the travel route, the robot is controlled to avoid obstacles based on the size of the limit passage and the updated obstacle avoidance size.

5. The method according to claim 4, It is characterized in that Based on the size of the limit passage and the updated obstacle avoidance size, controlling the robot to avoid obstacles includes: Determining whether the robot can pass through the limit passage according to the size of the limit passage and the updated obstacle avoidance size; In the case where the robot can pass through the limit passage, determining the obstacle avoidance center of the robot according to the updated obstacle avoidance size, and determining the passage center of the limit passage according to the size of the limit passage; After the obstacle avoidance center of the robot is aligned with the passage center of the extreme passage, the robot is controlled to pass through the extreme passage.

6. The method according to claim 4, It is characterized in that By using the obstacle avoidance sensor set on the robot, it is detected whether there is an extreme passage in the current route of the robot, including at least one of the following: By using the obstacle avoidance sensor, it is detected whether there is a limit passage with a width value less than a set width threshold in the robot's travel route; The obstacle avoidance sensor is used to detect whether there is a limit passage in the robot's route, the difference between the width value and the updated obstacle avoidance size being less than a set passage threshold.

7. The method according to claim 2, It is characterized in that The obstacle avoidance size is updated according to the collected data to obtain an updated obstacle avoidance size, including: Determining the size of the obstacles at a close distance to the edge of the storage tray according to the collected data; The obstacle avoidance size is updated according to the size of the close-range obstacle to obtain an updated obstacle avoidance size.

8. The method according to any one of claims 1 to 7, It is characterized in that The sensors are installed on both sides of the uppermost storage tray of the robot, the sensors are arranged to tilt downward, and the robot is provided with an omnidirectional mobile chassis.

9. A robot obstacle avoidance device, It is characterized in that include: The obstacle avoidance size detection module is used to determine whether the robot's obstacle avoidance size has changed based on the data collected by the sensor; An obstacle avoidance size updating module, used to update the obstacle avoidance size according to the collected data when the obstacle avoidance size changes, so as to obtain an updated obstacle avoidance size; The robot obstacle avoidance module is used to control the robot to avoid obstacles based on the updated obstacle avoidance size.

10. An electronic device, It is characterized in that The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the robot obstacle avoidance method according to any one of claims 1 to 8.

11. A computer-readable storage medium, It is characterized in that The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the robot obstacle avoidance method according to any one of claims 1 to 8 when executed.

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