A method and apparatus for robotic pile buttressing based on lidar

Abstract

The application discloses a kind of method and device based on laser radar of robot to pile, comprising the following steps: when robot enters the preset pile of charging pile range, the surrounding environment information is scanned by laser radar, obtains several radar data point sets, according to the several radar data point sets, generate several intercept images;Wherein, each radar data point set corresponds to an image;Each of the intercept image is compared with template image respectively, and the center point position information of the charging pile is obtained;According to the first radar data point set with the highest template matching degree, the offset data of robot relative to charging pile is calculated, so that the pose of robot is adjusted to directly opposite charging pile;The distance between robot and charging pile is obtained by laser radar, and according to the distance between robot and charging pile, the robot advances the same distance to make robot realize the successful docking with the charging pile.

Description

Technical Field

[0001] This invention relates to the field of robotics, and in particular to a robot-based method and apparatus for aligning points using lidar. Background Technology

[0002] With the rise of the intelligent manufacturing industry in recent years, intelligent robots have been widely used in many fields such as industrial automation, logistics warehousing, and smart homes. Intelligent robots are typically powered by internal batteries, which need to be recharged at charging stations when depleted. Currently, the most common charging method is for the robot to autonomously locate and dock at a charging station.

[0003] Existing autonomous docking methods primarily rely on infrared sensors or GPS to guide the robot to the charging station, followed by touch sensors to determine successful docking. However, the emission angle of ordinary infrared LEDs is uncontrollable, typically requiring multiple LEDs and complex protocols for robot-charging station docking, resulting in complex calculations and lengthy adjustment processes. Furthermore, infrared devices are susceptible to environmental influences, causing docking failures and charging failures. GPS-based docking is heavily dependent on positioning accuracy; significant errors can lead to the robot failing to locate the charging station. Additionally, using touch sensors to control charging voltage output is prone to accidental electric shocks. Summary of the Invention

[0004] To address the shortcomings of the existing technology, this invention provides a robot-based pile-aligning method and device based on lidar, which greatly improves the efficiency and accuracy of robot pile alignment.

[0005] This invention provides a robot-based stake-aligning method based on lidar, comprising the following steps:

[0006] Once the robot enters the preset charging station's alignment range, it scans the surrounding environment using lidar to acquire several sets of radar data points. Based on these sets of radar data points, it generates several captured images; each set of radar data points corresponds to one image.

[0007] Each captured image is compared with the template image to obtain the center point location information of the charging pile;

[0008] Based on the first radar data point set with the highest matching degree with the template, the offset data of the robot relative to the charging pile is calculated, so that the robot's pose is adjusted to face the charging pile.

[0009] The distance between the robot and the charging station is obtained by using lidar. Based on the distance between the robot and the charging station, the robot is controlled to move forward the same distance so that the robot can successfully dock with the charging station.

[0010] Compared to existing technologies that guide robots to align with charging piles using infrared devices, this invention utilizes lidar to scan environmental information and obtain a set of radar data points. These data points are then used to generate corresponding cropped images. The cropped images are then compared, converted, and processed to obtain the robot's pose information relative to the charging pile. Finally, the robot is successfully aligned with the charging pile. This method is simple, provides more stable control of the robot during alignment, and significantly increases alignment efficiency.

[0011] Furthermore, the robot enters the preset charging station's alignment range, specifically including: when the robot is in a low-battery state and needs to be charged, it moves to the preset alignment point.

[0012] Furthermore, the step of scanning the surrounding environment information using lidar to acquire several sets of radar data points, and generating several cropped images based on these sets of radar data points, specifically includes:

[0013] Several laser beams are emitted by the lidar to obtain several laser points. Each laser point is used as the segmentation center of the several lidar data points. The data is traversed to both ends to extract data of a preset length as a set of lidar data points, thereby obtaining the several sets of lidar data points. Several one-to-one corresponding extracted images are generated from the several sets of lidar data points. The preset length is half the width of the feature area of ​​the charging pile.

[0014] The lidar scanning method used in this embodiment of the invention uses each lidar point as the segmentation center of the plurality of lidar data, traverses to both ends, and extracts data of a preset length. The lidar point and its neighboring points within the preset length range are combined to form a lidar data point set, thereby obtaining the plurality of lidar data point sets. The plurality of lidar data point sets are then used to generate a plurality of one-to-one corresponding extracted images, which can comprehensively obtain the environmental information between the robot and the charging pile, laying a good foundation for subsequently determining the center point of the charging pile and the position information of the robot relative to the charging pile.

[0015] Furthermore, the step of comparing each captured image with the template image to obtain the center point location information of the charging pile specifically includes: subtracting each captured image from the preset template image, taking the absolute value of the difference, and determining the geometric center point of the captured image with the smallest absolute value as the center point of the charging pile, thereby obtaining the center point location information of the charging pile.

[0016] By subtracting the captured image data from the template image data and using this data to determine the center point of the charging pile, the relative position of the charging pile and the robot can be obtained more clearly, thus determining the robot's final docking target point and improving the docking accuracy.

[0017] Furthermore, the step of calculating the robot's offset data relative to the charging pile based on the first radar data point set with the highest matching degree to the template, and adjusting the robot's pose to face the charging pile, specifically includes:

[0018] Extract the first image from the first radar data point set;

[0019] The point set corresponding to the first image is converted from polar coordinates to rectangular coordinates. The left and right endpoints of the corresponding point set are connected by a line. The angle between the line connecting the endpoints and the horizontal axis in the rectangular coordinate system is calculated. The angle is the offset data required for robot pose adjustment. The robot can be determined to be facing the charging pile after the pose is adjusted according to the offset data.

[0020] By performing coordinate system transformation on the LiDAR data, which is closer to the real situation, the offset angle of the robot relative to the charging pile can be calculated more efficiently, thereby controlling the robot to adjust its posture.

[0021] Furthermore, the step of obtaining the distance between the robot and the charging station using lidar, and controlling the robot to advance the same distance based on this distance to achieve successful docking with the charging station, specifically includes:

[0022] Using lidar and a preset laser ranging method, the distance between the robot and the charging station is obtained, and the distance between the robot and the charging station is input into the internal system. The internal system then controls the robot to move forward the same distance so that the robot can successfully dock with the charging station.

[0023] Based on the above method embodiments, the present invention provides corresponding apparatus embodiments;

[0024] This invention provides a robot-based pile-aligning device based on lidar, comprising: an image capture module, an image comparison module, a calibration module, and a motion control module;

[0025] The image capture module is used to scan the surrounding environment information with lidar after the robot enters the preset charging pile alignment range, obtain several radar data point sets, and generate several captured images based on the several radar data point sets; wherein, each radar data point set corresponds to one image.

[0026] The image comparison module is used to compare each of the captured images with the template image to obtain the center point location information of the charging pile;

[0027] The calibration module calculates the robot's offset data relative to the charging pile based on the first radar data point set with the highest matching degree with the template, so that the robot's pose is adjusted to face the charging pile.

[0028] The motion control module is used to control the robot to move forward the same distance based on the distance between the robot and the charging pile obtained through lidar, so that the robot can successfully dock with the charging pile.

[0029] Furthermore, the image capture module is used to scan the surrounding environment information using lidar, acquire several sets of lidar data points, and generate several captured images based on the sets of lidar data points, specifically including:

[0030] Several laser beams are emitted by a lidar to obtain several laser points. Each laser point is used as the segmentation center of the several lidar data points. The data is traversed to both ends to extract data of a preset length. The laser point and its neighboring points within the preset length range are combined to form a lidar data point set, thereby obtaining the several lidar data point sets. Several one-to-one corresponding extracted images are generated from the several lidar data point sets. The preset length is half the width of the feature area of ​​the charging pile.

[0031] Furthermore, the image comparison module is used to compare each captured image with the template image to obtain the center point location information of the charging pile. Specifically, it includes: subtracting each captured image from the preset template image, taking the absolute value of the difference, and determining the geometric center point of the captured image with the smallest absolute value as the center point of the charging pile, thereby obtaining the center point location information of the charging pile.

[0032] Based on the above method embodiments, the present invention provides corresponding device embodiments;

[0033] This invention provides a robot, including a LiDAR-based robot-to-pile system, wherein the LiDAR-based robot-to-pile system performs the LiDAR-based robot-to-pile method as provided in the embodiments of the invention. Attached Figure Description

[0034] Figure 1 This is a schematic flowchart of a robot-based pile-setting method based on lidar provided in an embodiment of the present invention.

[0035] Figure 2 This is a schematic diagram of a robot-based pile-setting device based on lidar provided in an embodiment of the present invention.

[0036] Figure 3This is a schematic diagram of the workflow of an autonomous charging mode for a charging pile provided in an embodiment of the present invention.

[0037] Figure 4 This is a schematic diagram of the manual charging mode workflow of a charging pile provided in an embodiment of the present invention. Detailed Implementation

[0038] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0039] Currently, intelligent robots widely adopt autonomous recharging to replenish their power. This means that when the robot is idle or its battery level is below a certain threshold, it automatically returns to the charging station to continue its operation, reducing human intervention and improving work efficiency. Currently, most robots on the market use infrared sensors or GPS to guide them to the charging station, and then use touch sensors to determine if the docking was successful.

[0040] LiDAR is an advanced detection method that combines laser technology with modern optoelectronic detection technology. It consists of a transmitting system, a receiving system, and information processing components. The working principle of lidar is very similar to that of radar. It uses laser as a signal source. The pulsed laser emitted by the laser device hits trees, roads, bridges, and buildings on the ground, causing scattering. Some of the light waves are reflected back to the lidar receiver. Based on the principle of laser ranging, the distance from the lidar to the target point is calculated. By continuously scanning the target object with pulsed laser, data on all target points on the object can be obtained. After image processing using this data, a precise three-dimensional image can be obtained.

[0041] See Figure 1 This is a flowchart illustrating a robot-based stake-aligning method using lidar according to an embodiment of the present invention, comprising the following steps:

[0042] S101: When the robot enters the preset charging station range, it scans the surrounding environment using LiDAR to obtain several sets of radar data points, and generates several captured images based on the sets of radar data points; wherein, each set of radar data points corresponds to one image.

[0043] S102: Compare each of the captured images with the template image to obtain the center point location information of the charging pile;

[0044] S103: Based on the first radar data point set with the highest matching degree with the template, calculate the offset data of the robot relative to the charging pile, and adjust the robot's pose to face the charging pile.

[0045] S104: Obtain the distance between the robot and the charging station using LiDAR, and control the robot to move forward the same distance based on the distance between the robot and the charging station so that the robot can successfully dock with the charging station.

[0046] Compared to existing technologies that guide robots to align with charging piles using infrared devices, this invention utilizes lidar to scan environmental information and obtain a set of radar data points. These data points are then used to generate corresponding cropped images. The cropped images are then compared, converted, and processed to obtain the robot's pose information relative to the charging pile. Finally, the robot is successfully aligned with the charging pile. This method is simple, provides more stable control of the robot during alignment, and significantly increases alignment efficiency.

[0047] Specifically, in step S101, when the robot is in a low-battery state or idle without tasks, it autonomously returns to the charging station to replenish its power. The robot will close the relay on the robot charging circuit in advance and navigate to the alignment point 30cm away from the charging station. The LiDAR will then begin scanning the surrounding environment. Each LiDAR data point can capture a set of points, and these sets of points are used to generate an image for matching. The number of images captured depends on the number of LiDAR data points.

[0048] In a preferred embodiment, the surrounding environment is scanned by a lidar to obtain several sets of radar data points. Based on the several sets of radar data points, several cropped images are generated. This includes: emitting several laser beams by the lidar to obtain several laser points, and using each laser point as the segmentation center of the several sets of radar data points, traversing to both ends to crop data points that are half the width (30cm) of the characteristic area of ​​the charging pile. The laser points and their neighboring points within a preset length range are combined to form a set of radar data points, thereby obtaining the several sets of radar data points. Several one-to-one cropped images are generated from the several sets of radar data points, and the width of these cropped images is 30cm.

[0049] The lidar scanning method used in this embodiment of the invention uses each lidar point as the segmentation center of the plurality of radar data, traverses to both ends respectively, and extracts data of a preset length as a set of radar data points, thereby obtaining the plurality of radar data point sets, and generating a plurality of one-to-one corresponding extracted images from the plurality of radar data point sets, which can comprehensively obtain the environmental information between the robot and the charging pile, laying a good foundation for subsequently determining the center point of the charging pile and the position information of the robot relative to the charging pile.

[0050] For step S102, specifically, the difference between each of the captured images and the preset template image is calculated, and the absolute value of the difference is taken. When the absolute value is less than a certain parameter value, the degree of matching between the two is relatively high. The image with the highest degree of matching can be basically determined to be consistent with the template, and the center data of its point set is the center of the charging pile.

[0051] By subtracting the captured image data from the template image data and using this data to determine the center point of the charging pile, the relative position of the charging pile and the robot can be obtained more clearly, thus determining the robot's final docking target point and improving the docking accuracy.

[0052] For step S103, specifically, an image is generated from the first radar data point set, and the point set corresponding to the image is converted from polar coordinates to Cartesian coordinates. After the coordinate system conversion, the left and right endpoints of the point set are connected, and the angle (0° to 180°) between the line connecting the endpoints and the horizontal axis in the Cartesian coordinate system is calculated. The angle is the offset data required for robot pose adjustment, and the pose is adjusted according to the offset data.

[0053] By performing coordinate system transformation on the LiDAR data, which is closer to the real situation, the offset angle of the robot relative to the charging pile can be calculated more efficiently, thereby controlling the robot to adjust its posture.

[0054] In a preferred embodiment, after adjustment, the robot needs to use LiDAR to scan and determine whether a charging station can be detected directly in front, to avoid the adjusted pose being backwards from the charging station. Using this method, the robot can determine that it is facing the charging station.

[0055] For step S104, specifically, the distance between the robot and the charging pile is obtained using LiDAR and a preset laser ranging method, and the distance between the robot and the charging pile is input into the internal system. The internal system then controls the robot to move forward the same distance so that the robot can successfully dock with the charging pile.

[0056] Based on the above method embodiments, the present invention provides corresponding apparatus embodiments;

[0057] See Figure 2 This is a schematic diagram of a robot-based pile-aligning device based on lidar provided in an embodiment of the present invention, including: an image capture module 201, an image comparison module 202, a calibration module 203, and a motion control module 204;

[0058] The image capture module 201 is used to scan the surrounding environment information with lidar after the robot enters the preset charging pile alignment range, obtain several radar data point sets, and generate several captured images based on the several radar data point sets; wherein, each radar data point set corresponds to one image.

[0059] The image comparison module 202 is used to compare each of the captured images with the template image to obtain the center point location information of the charging pile;

[0060] The calibration module 203 generates a first image based on the first radar data point set with the highest matching degree with the template, performs coordinate transformation on the first image, obtains the offset data of the robot relative to the charging pile by calculating the angle between the line connecting the endpoints of the first image and the horizontal axis, and adjusts the robot's pose to face the charging pile.

[0061] The motion control module 204 is used to control the robot to move forward the same distance based on the distance between the robot and the charging pile obtained by the lidar, so that the robot can successfully dock with the charging pile.

[0062] Furthermore, the image capture module 201 is used to scan the surrounding environment information using lidar, acquire several sets of lidar data points, and generate several captured images based on the several sets of lidar data points, specifically including:

[0063] Several laser beams are emitted by a lidar to obtain several laser points. Each laser point is used as the segmentation center of the several lidar data points. The data is traversed to both ends to extract data of a preset length. The laser point and its neighboring points within the preset length range are combined to form a lidar data point set, thereby obtaining the several lidar data point sets. Several one-to-one corresponding extracted images are generated from the several lidar data point sets. The preset length is half the width of the feature area of ​​the charging pile.

[0064] Furthermore, the image comparison module 202 is used to compare each captured image with the template image to obtain the center point location information of the charging pile. Specifically, it includes: subtracting each captured image from the preset template image, taking the absolute value of the difference, and determining the geometric center point of the captured image with the smallest absolute value as the center point of the charging pile, thereby obtaining the center point location information of the charging pile.

[0065] Furthermore, the calibration module 203 generates an image from the first radar data point set with the highest matching degree to the template, and converts the point set corresponding to the image from polar coordinates to Cartesian coordinates. After the coordinate system conversion, the left and right endpoints of the point set are connected, and the angle (0° to 180°) between the line connecting the endpoints and the horizontal axis in the Cartesian coordinate system is calculated. The angle is the offset data required for robot pose adjustment, and the pose is adjusted according to the offset data.

[0066] In a preferred embodiment, after adjustment, the robot needs to use LiDAR to scan and determine whether a charging station can be detected directly in front, to avoid the adjusted pose being backwards from the charging station. Using this method, the robot can determine that it is facing the charging station.

[0067] Based on the above method embodiments, the present invention provides corresponding device embodiments;

[0068] This invention provides a robot, including: a controller and a lidar connected to the controller; the controller is used to execute the lidar-based robot staking method according to any one of the present invention.

[0069] In addition, this embodiment of the invention also provides a charging pile, in which both the charging pile and the robot are equipped with current monitoring circuits, mainly used to determine whether the robot is fully charged or has left the charging pile, and to determine whether to disconnect the relays of the charging circuits of both parties. When the charging current of the charging pile is lower than a certain threshold, it can be determined that the robot has left the charging pile. At this time, the charging pile will disconnect the corresponding relay, stop the charging pile brush block from outputting voltage, and avoid safety issues such as electric shock.

[0070] The charging station uses a voltage detection circuit to determine if the robot has successfully docked, and a current detection circuit to determine if the robot is fully charged or has left the charging station. This is because when the robot is fully charged but hasn't left the charging station, the charging station will stop charging the battery to protect it, only supplying power to the robot. In this case, the robot's power comes from the charging station, and its current is much lower than the charging current, but the voltage remains constant. Therefore, using voltage fluctuations to determine docking status ensures that the robot's battery doesn't overcharge after full charge and remains fully charged, while the robot is still powered normally. Furthermore, during normal operation of the charging station, the voltage and current detection modules continuously monitor the circuit's current and voltage. In case of overcurrent or overvoltage, they promptly issue alarms and disconnect the corresponding relays, improving the charging station's safety.

[0071] As a preferred embodiment, the user can choose between automatic charging mode and manual charging mode during the robot charging process;

[0072] See Figure 3In automatic charging mode, when the robot is in a low battery state or idle without tasks, it autonomously returns to the charging station to replenish its power. At this time, the robot will pre-close the relay on its charging circuit and navigate to the preset charging station range, using the LiDAR-based robot charging station method provided in this embodiment of the invention to autonomously align with and charge the robot. When the voltage of the charging station's brush block changes, the relay inside the charging station closes, starting charging the robot. During this time, the voltage detection module and current detection module inside the charging station continuously monitor the current and voltage in the circuit. When overvoltage or overcurrent occurs in the circuit, the relay of the charging station will automatically disconnect, stopping charging the robot and issuing an alarm signal.

[0073] See Figure 4 For the manual charging mode, the main consideration is when the robot is unable to return to the charging station autonomously due to extremely low battery or being powered off. This allows for manual docking between the robot and the charging station by pushing the robot. Pressing and holding the charging button on the charging station closes the relay. When the robot detects that the voltage of the charging brushes on its end is at the specified voltage, it will close the relay in its own charging circuit to initiate charging, without requiring the robot to be powered on. If the robot fails to successfully dock with the charging station within the specified time after pressing the charging button, the charging station will disconnect the relay and stop outputting the charging voltage.

[0074] This invention addresses the problems of complex robot-charging pile docking and lack of charging safety in existing technologies by providing a robot-charging pile docking method and corresponding device and equipment based on lidar, which improves the efficiency and accuracy of robot docking while also greatly enhancing safety.

[0075] It should be noted that the device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Furthermore, in the accompanying drawings of the device embodiments provided by this invention, the connection relationships between modules indicate that they have communication connections, which can be specifically implemented as one or more communication buses or signal lines. Those skilled in the art can understand and implement this without any creative effort.

[0076] The above description represents the preferred embodiments of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of the present invention, and these improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. A robot-based method for aligning piles using lidar, characterized in that, Includes the following steps: Once the robot enters the preset charging station's alignment range, it scans the surrounding environment using lidar to acquire several sets of radar data points. Based on these sets of radar data points, it generates several captured images; each set of radar data points corresponds to one image. The process of scanning the surrounding environment using lidar to obtain several sets of radar data points, and generating several cropped images based on these sets of radar data points, specifically includes: emitting several laser beams through the lidar to obtain several laser points; using each laser point as the segmentation center of the radar data; traversing both ends to crop data of a preset length; combining each laser point with its neighboring points within the preset length range to form a set of radar data points, thereby obtaining the several sets of radar data points; and generating several one-to-one cropped images from these sets of radar data points; wherein the preset length is half the width of the characteristic area of ​​the charging pile. Each captured image is compared with the template image to obtain the center point location information of the charging pile; Based on the first radar data point set with the highest matching degree to the template, the offset data of the robot relative to the charging pile is calculated, so that the robot pose is adjusted to face the charging pile. Specifically, this includes: extracting a first image from the first radar data point set; converting the point set corresponding to the first image from a polar coordinate system to a rectangular coordinate system; connecting the left and right endpoints of the point set corresponding to the first image; calculating the angle between the line connecting the endpoints and the horizontal axis in the rectangular coordinate system; the included angle is the offset data required for robot pose adjustment; and the robot can be determined to be facing the charging pile after adjusting its pose according to the offset data. The distance between the robot and the charging station is obtained by using lidar. Based on the distance between the robot and the charging station, the robot is controlled to move forward the same distance so that the robot can successfully dock with the charging station.

2. The robot-based stake-aligning method based on lidar as described in claim 1, characterized in that, The robot enters the preset charging station's alignment range, specifically including: when the robot is in a low-battery state and needs to be charged, it moves to the preset alignment point.

3. The robot-based stake-aligning method based on lidar as described in claim 1, characterized in that, The center point location information of the charging pile is obtained by comparing each captured image with the template image. Specifically, this includes: subtracting each captured image from the preset template image, taking the absolute value of the difference, and determining the geometric center point of the captured image with the smallest absolute value as the center point of the charging pile, thereby obtaining the center point location information of the charging pile.

4. The robot-based stake-aligning method based on lidar as described in claim 1, characterized in that, The process of obtaining the distance between the robot and the charging station using lidar, and controlling the robot to advance the same distance based on this distance to achieve successful docking with the charging station, specifically includes: Using lidar and a preset laser ranging method, the distance between the robot and the charging station is obtained, and the distance between the robot and the charging station is input into the internal system. The internal system then controls the robot to move forward the same distance so that the robot can successfully dock with the charging station.

5. A robot-based pile-aligning device using lidar, characterized in that, include: Image capture module, image comparison module, calibration module, and motion control module; The image capture module is used to scan the surrounding environment information with lidar after the robot enters the preset charging pile alignment range, obtain several radar data point sets, and generate several captured images based on the several radar data point sets; wherein, each radar data point set corresponds to one image. The process of scanning the surrounding environment using lidar to obtain several sets of radar data points, and generating several cropped images based on these sets of radar data points, specifically includes: emitting several laser beams through the lidar to obtain several laser points; using each laser point as the segmentation center of the radar data; traversing both ends to crop data of a preset length; combining each laser point with its neighboring points within the preset length range to form a set of radar data points, thereby obtaining the several sets of radar data points; and generating several one-to-one cropped images from these sets of radar data points; wherein the preset length is half the width of the characteristic area of ​​the charging pile. The image comparison module is used to compare each of the captured images with the template image to obtain the center point location information of the charging pile; The calibration module calculates the robot's offset data relative to the charging pile based on the first radar data point set with the highest matching degree with the template, so that the robot's pose is adjusted to face the charging pile. Specifically, this includes: extracting a first image from the first radar data point set; converting the point set corresponding to the first image from a polar coordinate system to a rectangular coordinate system; connecting the left and right endpoints of the point set corresponding to the first image; calculating the angle between the line connecting the endpoints and the horizontal axis in the rectangular coordinate system; the angle is the offset data required for robot pose adjustment; and the robot can be determined to be facing the charging pile after adjusting its pose according to the offset data. The motion control module is used to control the robot to move forward the same distance based on the distance between the robot and the charging pile obtained through lidar, so that the robot can successfully dock with the charging pile.

6. The robot-based pile-aligning device based on lidar as described in claim 5, characterized in that, The image comparison module is used to compare each captured image with the template image to obtain the center point location information of the charging pile. Specifically, it includes: subtracting each captured image from the preset template image, taking the absolute value of the difference, and determining the geometric center point of the captured image with the smallest absolute value as the center point of the charging pile, thereby obtaining the center point location information of the charging pile.

7. A robot, characterized in that, include: Controller and lidar connected to the controller; The controller is used to execute the laser radar-based robot staking method as described in any one of claims 1-4.

Images