Light-load indoor inspection robot autonomous charging system and method

Abstract

A kind of light load indoor inspection robot autonomous charging system and method, using steps are as follows: step one: robot navigation to charging point, identify charging pile and calculate the position and posture information of charging pile in map;Step two: according to the position and posture information of robot and charging pile, adjust the position and posture of robot, so that the positive and negative of robot align the positive and negative of charging pile;Step three: detect whether abnormal situation appears in charging process, if so, robot stops moving, sends alarm information, otherwise, enter next step;Step four: host computer sends control signal, controls motor movement, executes autonomous charging.The system is provided with lower computer controller, the first control end of the lower computer controller is connected with motor system, battery management end is connected with battery unit, first acquisition end is connected with laser radar unit, second acquisition end is connected with infrared sensor unit, communication end is connected with host computer controller.

Description

Technical Field

[0001] This invention relates to the field of inspection robot control technology, specifically to an autonomous charging system and method for a light-load indoor inspection robot. Background Technology

[0002] With the continuous development and advancement of intelligent technology, inspection robots have been applied in various fields. Lightweight indoor inspection robots are multifunctional integrated systems that combine environmental perception, dynamic decision-making, and planning. They are based on artificial intelligence and incorporate cutting-edge technologies such as sensors, information processing, electronic engineering, computer engineering, and automation. As the functions of inspection robots continue to expand, in addition to basic functions such as perception and positioning, path planning, and autonomous obstacle avoidance, their autonomous charging capabilities, safety, accuracy, and efficiency are also crucial.

[0003] Currently, there are three common autonomous charging methods for lightweight indoor inspection robots: infrared-based autonomous charging, vision-based autonomous charging, and LiDAR-based autonomous charging. Infrared-based autonomous charging relies on infrared sensors to dock the robot with the charging station. This method requires multiple adjustments to the robot's orientation to achieve precise docking, making it complex. Furthermore, infrared sensor signals are easily affected by external environmental interference, leading to charging failures. Vision-based autonomous charging primarily uses cameras to identify charging stations, which is unsuitable in bright light or darkness, significantly limiting the robot's autonomy. LiDAR-based autonomous charging can adapt to different environments and has strong anti-interference capabilities; however, this method relies on precise positioning algorithms, and charging safety, accuracy, and efficiency cannot be effectively guaranteed.

[0004] To address the above issues, the key challenges for the autonomous charging function of lightweight indoor inspection robots are ensuring charging safety and efficiency. Summary of the Invention

[0005] This invention addresses the shortcomings of existing technologies by proposing an autonomous charging system and method that combines lidar and infrared sensors. The system uses lidar point clouds to identify charging stations and infrared sensor signals to control a robot. This method is simple to operate, safe, reliable, and offers high charging efficiency. The specific technical solution is as follows:

[0006] A method for autonomous charging of a lightweight indoor inspection robot, comprising the following steps:

[0007] Step 1: The robot navigates to the charging point, identifies the charging station, and calculates the location and orientation information of the charging station on the map;

[0008] Step 2: Based on the position and posture information of the robot and the charging station, adjust the position and posture of the robot so that the positive and negative terminals of the robot are aligned with the positive and negative terminals of the charging station.

[0009] Step 3: Check for any abnormalities during the charging process. If any are found, the robot will stop moving and issue an alarm; otherwise, proceed to the next step.

[0010] Step 4: The host computer sends a control signal to control the motor to move and perform autonomous charging.

[0011] As a preferred embodiment, the specific method for identifying the charging pile in step one is as follows:

[0012] A single-line LiDAR is used to identify charging stations. If the robot's battery level is low, it first navigates to the charging point in front of the charging station and subscribes to the point cloud coordinate data (x, y, y) of the single-line LiDAR. n ,y n After obtaining the point cloud data, find the pair of points closest to each other. After filtering, use the least squares method to synthesize these points into a line segment. The formula for calculating the distance d_poin between two point clouds is:

[0013]

[0014] Based on a selected set of laser point cloud coordinates (x1, y1)(x2, y2)...(x n ,y n This can be fitted into a line segment, which can be obtained from the mathematical expression of a straight line:

[0015] y = a0 + a1x

[0016] Select the sum of squares of the residuals S r The minimum value is used as the "best fit" criterion, and the calculation formula is as follows:

[0017]

[0018] Then, it is determined from the fitted straight lines whether there are two line segments that conform to the "V" shape of the charging pile. The criteria for judging the charging pile line segments are as follows:

[0019] If the fitted line segment is less than 0.1 meters, it is considered that the line segment is not a charging pile line segment;

[0020] If the fitted line segment is longer than 0.25 meters, it is considered not to be a charging pile line segment.

[0021] If the distance from a point on the fitted line segment to the lidar is less than 0.1 meters, the line segment is considered not to be a charging pile line segment.

[0022] If the distance from a point on the fitted line segment to the lidar is greater than 1.2 meters, the line segment is considered not to be a charging pile line segment.

[0023] If there are fewer than 20 points on a line segment, the line segment is not considered a charging pile line segment.

[0024] If a line segment has more than 600 points, it is considered not to be a charging pile line segment.

[0025] Based on the above rules for judging charging pile line segments, two line segments conforming to the "V" shape characteristic of the charging pile can be obtained. Let the coordinates of two points on the two line segments line_0 and line_1 be (p0, p1) and (q0, q1), respectively, and the slopes be k0 and k1. Let goal_point be the target point of the charging pile, and corner_point be the corner point of the "V" shaped structure of the charging pile. The distance dis_goal from the target point goal_point to corner_point is 0.25 meters. The coordinates (l0, l1) of corner_point can be calculated as follows:

[0026]

[0027]

[0028] The target point coordinates (x, y) and pose θ0 of the charging pile are:

[0029]

[0030]

[0031]

[0032] As a preferred embodiment, step two specifically involves:

[0033] The robot uses a single-line lidar and infrared sensor to determine its relative position and attitude with the charging station, and controls the robot's movement to complete the charging docking.

[0034] After identifying the charging station and obtaining its location information, the robot can subscribe to its current position and posture information and continuously adjust its pose to face the charging station. The specific adjustment plan consists of three steps.

[0035] 2.1: The robot starts moving from the charging point, moves forward, approaches the charging pile, and stops about 0.5 meters in front of the charging pile; then it subscribes to the robot's posture. If the robot has a posture error, it rotates left and right in place to adjust the robot's posture to ensure that the robot is facing the charging pile, that is, the robot's posture is the same as the posture of the charging pile.

[0036] 2.2: After the first stage is completed, the robot's head is facing the charging station. Rotate the robot 180° in place. If the infrared sensor at the tail of the robot receives infrared data from the charging station, the robot will stop rotating.

[0037] 2.3: After the second stage is completed, the robot's tail is facing the charging station. At this time, control the robot to move backward until it docks with the electrodes of the charging station to complete the charging task.

[0038] In the lidar coordinate system, given the coordinates (x, y) of the charging station, the formulas for calculating the distance d between the robot and the charging station and the pose θ are as follows:

[0039]

[0040]

[0041] As a preferred embodiment, step three specifically involves:

[0042] Starting from 3.1;

[0043] 3.2 Determine whether the charging pile recognition was successful. If yes, proceed to the next step; otherwise, proceed to step 3.6.

[0044] 3.3 Determine if there are obstacles in front of or behind the charging station. If so, proceed to step 3.6.

[0045] 3.4 Determine if there is an infrared signal. If yes, proceed to the next step; otherwise, proceed to step 3.6.

[0046] 3.5 Execute the charging task; once charging is complete, the process ends.

[0047] 3.6 The robot stops moving, issues an alarm, and requires manual intervention.

[0048] A system for autonomous charging of a lightweight indoor inspection robot includes a lower-level controller. The lower-level controller has a first control terminal connected to the motor system, a battery management terminal connected to the battery unit, a first acquisition terminal connected to the lidar unit, a second acquisition terminal connected to the infrared sensor unit, and a communication terminal connected to the upper-level controller.

[0049] Preferably, the lower-level controller communicates with the motor system via the CAN protocol; the lower-level controller communicates with the battery unit via RS232; the infrared sensor is controlled by the lower-level controller via the I / O port of the microcontroller; the lidar transmits data to the upper-level controller via the UDP protocol; and the lower-level controller and the upper-level controller transmit data via the TCP protocol.

[0050] As a preferred embodiment: the motor in the motor system is a ZLLG65ASM250-L Zhongling brushless DC hub motor, and the motor system includes wheels, motor, reducer and encoder; the lithium battery in the battery unit is an LS-DL-24-40C Panasonic lithium battery; the lower-level controller is an STM32F407 microcontroller; the lidar is a SIMO-LS-10H star-second single-line lidar; the infrared sensor is a YIYA XLHW500CM phototransistor; and the upper-level controller is an I310 generation industrial computer.

[0051] The beneficial effects of this invention are as follows: strong environmental adaptability, capable of performing autonomous charging tasks 24 hours a day, regardless of day or night; high charging efficiency, employing a combination of single-line lidar and infrared sensors to accurately and quickly identify charging piles and precisely connect to the charging pile electrodes, thereby improving charging efficiency; good stability, with a simple method and convenient parameter debugging, facilitating rapid product development; and high charging safety, with corresponding decision control and safety strategy modules designed to make autonomous charging safer and more reliable. Attached Figure Description

[0052] Figure 1 This is a schematic diagram of the structure of the present invention.

[0053] Figure 2 This is a schematic diagram of the inspection robot structure in the invention machine.

[0054] Figure 3 This is a schematic diagram of the charging pile structure in this invention.

[0055] Figure 4 This is a schematic diagram of the decision control process in this invention.

[0056] Figure 5 This is a schematic diagram of the security strategy process in this invention.

[0057] Figure 6 This is a schematic diagram of the process in this invention. Detailed Implementation

[0058] The preferred embodiments of the present invention will now be described in detail with reference to the accompanying drawings, so that the advantages and features of the present invention can be more easily understood by those skilled in the art, thereby providing a clearer and more explicit definition of the scope of protection of the present invention.

[0059] like Figure 4 , Figure 5 and Figure 6 The following is a method for autonomous charging of a lightweight indoor inspection robot, comprising the following steps:

[0060] Step 1: The robot navigates to the charging point, identifies the charging station, and calculates the location and orientation information of the charging station on the map;

[0061] A single-line LiDAR is used to identify charging stations. If the robot's battery level is low, it first navigates to the charging point in front of the charging station and subscribes to the point cloud coordinate data (x, y, y) of the single-line LiDAR. n ,y n After obtaining the point cloud data, find the pair of points closest to each other. After filtering, use the least squares method to synthesize these points into a line segment. The formula for calculating the distance d_poin between two point clouds is:

[0062]

[0063] Based on a selected set of laser point cloud coordinates (x1, y1)(x2, y2)...(x n ,y n This can be fitted into a line segment, which can be obtained from the mathematical expression of a straight line:

[0064] y = a0 + a1x

[0065] Select the sum of squares of the residuals S r The minimum value is used as the "best fit" criterion, and the calculation formula is as follows:

[0066]

[0067] Then, it is determined from the fitted straight lines whether there are two line segments that conform to the "V" shape of the charging pile. The criteria for judging the charging pile line segments are as follows:

[0068] If the fitted line segment is less than 0.1 meters, it is considered that the line segment is not a charging pile line segment;

[0069] If the fitted line segment is longer than 0.25 meters, it is considered not to be a charging pile line segment.

[0070] If the distance from a point on the fitted line segment to the lidar is less than 0.1 meters, the line segment is considered not to be a charging pile line segment.

[0071] If the distance from a point on the fitted line segment to the lidar is greater than 1.2 meters, the line segment is considered not to be a charging pile line segment.

[0072] If there are fewer than 20 points on a line segment, the line segment is not considered a charging pile line segment.

[0073] If a line segment has more than 600 points, it is considered not to be a charging pile line segment.

[0074] Based on the above rules for judging charging pile line segments, two line segments conforming to the "V" shape characteristic of the charging pile can be obtained. Let the coordinates of two points on the two line segments line_0 and line_1 be (p0, p1) and (q0, q1), respectively, and the slopes be k0 and k1. Let goal_point be the target point of the charging pile, and corner_point be the corner point of the "V" shaped structure of the charging pile. The distance dis_goal from the target point goal_point to corner_point is 0.25 meters. The coordinates (l0, l1) of corner_point can be calculated as follows:

[0075]

[0076]

[0077] The target point coordinates (x, y) and pose θ0 of the charging pile are:

[0078]

[0079]

[0080]

[0081] Step 2: Based on the position and posture information of the robot and the charging station, adjust the position and posture of the robot so that the positive and negative terminals of the robot are aligned with the positive and negative terminals of the charging station.

[0082] The robot uses a single-line lidar and infrared sensor to determine its relative position and attitude with the charging station, and controls the robot's movement to complete the charging docking.

[0083] After identifying the charging station and obtaining its location information, the robot can subscribe to its current position and posture information and continuously adjust its pose to face the charging station. The specific adjustment plan consists of three steps.

[0084] 2.1: The robot starts moving from the charging point, moves forward, approaches the charging pile, and stops about 0.5 meters in front of the charging pile; then it subscribes to the robot's posture. If the robot has a posture error, it rotates left and right in place to adjust the robot's posture to ensure that the robot is facing the charging pile, that is, the robot's posture is the same as the posture of the charging pile.

[0085] 2.2: After the first stage is completed, the robot's head is facing the charging station. Rotate the robot 180° in place. If the infrared sensor at the tail of the robot receives infrared data from the charging station, the robot will stop rotating.

[0086] 2.3: After the second stage is completed, the robot's tail is facing the charging station. At this time, control the robot to move backward until it docks with the electrodes of the charging station to complete the charging task.

[0087] In the lidar coordinate system, given the coordinates (x, y) of the charging station, the formulas for calculating the distance d between the robot and the charging station and the pose θ are as follows:

[0088]

[0089]

[0090] Step 3: Check for any abnormalities during the charging process. If any are found, the robot will stop moving and issue an alarm; otherwise, proceed to the next step.

[0091] Starting from 3.1;

[0092] 3.2 Determine whether the charging pile recognition was successful. If yes, proceed to the next step; otherwise, proceed to step 3.6.

[0093] 3.3 Determine if there are obstacles in front of or behind the charging station. If so, proceed to step 3.6.

[0094] 3.4 Determine if there is an infrared signal. If yes, proceed to the next step; otherwise, proceed to step 3.6.

[0095] 3.5 Execute the charging task; once charging is complete, the process ends.

[0096] 3.6 The robot stops moving, issues an alarm, and requires manual intervention.

[0097] Step 4: The host computer sends a control signal to control the motor to move and perform autonomous charging.

[0098] like Figure 1 , Figure 2 and Figure 3 As shown: A system for autonomous charging of a light-load indoor inspection robot is provided, which includes a lower-level controller. The first control terminal of the lower-level controller is connected to the motor system, the battery management terminal is connected to the battery unit, the first acquisition terminal is connected to the lidar unit, the second acquisition terminal is connected to the infrared sensor unit, and the communication terminal is connected to the upper-level controller.

[0099] The lower-level controller communicates with the motor system via the CAN protocol; the lower-level controller communicates with the battery unit via RS232; the infrared sensor is controlled by the lower-level controller via the microcontroller's I / O port; the lidar transmits data to the upper-level controller via the UDP protocol; and the lower-level controller and the upper-level controller transmit data via the TCP protocol.

[0100] The motor system uses a ZLLG65ASM250-L Zhongling brushless DC hub motor, which includes wheels, a motor, a reducer, and an encoder. The battery unit uses a Panasonic LS-DL-24-40C lithium battery. The lower-level controller is an STM32F407 microcontroller. The lidar is a SIMO-LS-10H satellite-second single-line lidar. The infrared sensor is a YIYA XLHW500CM phototransistor. The upper-level controller is an I310 generation industrial computer.

Claims

1. A method for autonomous charging of a lightweight indoor inspection robot, characterized in that, The steps are as follows: Step 1: The robot navigates to the charging point, identifies the charging station, and calculates the location and orientation information of the charging station on the map; Step 2: Based on the position and posture information of the robot and the charging station, adjust the position and posture of the robot so that the positive and negative terminals of the robot are aligned with the positive and negative terminals of the charging station. Step 3: Check for any abnormalities during the charging process. If any are found, the robot will stop moving and issue an alarm; otherwise, proceed to the next step. Step 4: The host computer sends a control signal to control the motor to move and perform autonomous charging; In step one, the specific method for identifying the charging pile is as follows: The robot uses a single-line LiDAR to identify charging stations. If the robot's battery level is low, it first navigates to the charging point in front of the charging station and subscribes to the point cloud coordinate data of the single-line LiDAR. ; After obtaining the point cloud data, find the pair of points with the shortest distance between them. After filtering, use the least squares method to synthesize these points into a line segment. The distance between the two point clouds is... The calculation formula is: Based on a selected set of laser point cloud coordinates … This is fitted into a line segment, which is obtained based on the mathematical expression of a straight line: Select the sum of squares of the residuals The minimum value is used as the "best fit" criterion, and the calculation formula is as follows: Then, it is determined from the fitted straight lines whether there are two line segments that conform to the "V" shape of the charging pile. The criteria for judging the charging pile line segments are as follows: If the fitted line segment is less than 0.1 meters, it is considered that the line segment is not a charging pile line segment; If the fitted line segment is longer than 0.25 meters, it is considered not to be a charging pile line segment. If the distance from a point on the fitted line segment to the lidar is less than 0.1 meters, the line segment is considered not to be a charging pile line segment. If the distance from a point on the fitted line segment to the lidar is greater than 1.2 meters, the line segment is considered not to be a charging pile line segment. If there are fewer than 20 points on a line segment, the line segment is not considered a charging pile line segment. If a line segment has more than 600 points, it is considered not to be a charging pile line segment. Based on the above rules for judging charging pile line segments, two line segments that conform to the "V" shape characteristic of charging piles can be obtained. Let the coordinates of the two points of the two line segments line_0 and line_1 be... and The slopes are respectively and Let goal_point be the target point of the charging station, and corner_point be the corner point of the charging station's "V"-shaped structure. The distance from goal_point to corner_point is... With a value of 0.25 meters, the coordinates of the corner_point can be calculated. for: Coordinates of the target point of the charging station and position for: 。 2. The autonomous charging method for a lightweight indoor inspection robot according to claim 1, characterized in that: Step two specifically involves: The robot uses a single-line lidar and infrared sensor to determine its relative position and attitude with the charging station, and controls the robot's movement to complete the charging docking. After identifying the charging station and obtaining its location information, the robot can subscribe to its current position and posture information and continuously adjust its pose to face the charging station. The specific adjustment plan consists of three steps. 2.1: The robot starts moving from the charging point, moves forward, approaches the charging pile, and stops about 0.5 meters in front of the charging pile; then it subscribes to the robot's posture. If the robot has a posture error, it rotates left and right in place to adjust the robot's posture to ensure that the robot is facing the charging pile, that is, the robot's posture is the same as the posture of the charging pile. 2.2: After the first stage is completed, the robot's head is facing the charging station. Rotate the robot 180° in place. If the infrared sensor at the tail of the robot receives infrared data from the charging station, the robot will stop rotating. 2.3: After the second stage is completed, the robot's tail is facing the charging station. At this time, control the robot to move backward until it docks with the electrodes of the charging station to complete the charging task. Given the coordinates of the charging station in the lidar coordinate system. The distance between the robot and the charging station Formula for calculating pose θ: 。 3. The autonomous charging method for a lightweight indoor inspection robot according to claim 1, characterized in that: Step three specifically involves: Starting from 3.1; 3.2 Determine whether the charging pile recognition was successful. If yes, proceed to the next step; otherwise, proceed to step 3.

6. 3.3 Determine if there are obstacles in front of or behind the charging station; otherwise, proceed to the next step; otherwise, proceed to step 3.

6. 3.4 Determine if there is an infrared signal. If yes, proceed to the next step; otherwise, proceed to step 3.

6. 3.5 Execute the charging task; charging complete; end. 3.6 The robot stops moving, issues an alarm, and requires manual intervention.

4. The system for the autonomous charging method of the lightweight indoor inspection robot according to any one of claims 1 to 3, characterized in that: A lower-level controller is provided. The first control terminal of the lower-level controller is connected to the motor system, the battery management terminal is connected to the battery unit, the first acquisition terminal is connected to the lidar unit, the second acquisition terminal is connected to the infrared sensor unit, and the communication terminal is connected to the upper-level controller.

5. The system for the autonomous charging method of the lightweight indoor inspection robot according to claim 4, characterized in that: The lower-level controller communicates with the motor system via the CAN protocol; the lower-level controller communicates with the battery unit via RS232; the infrared sensor is controlled by the lower-level controller via the microcontroller's I / O port; the lidar transmits data to the upper-level controller via the UDP protocol; and the lower-level controller and the upper-level controller transmit data via the TCP protocol.

6. The system for the autonomous charging method of the lightweight indoor inspection robot according to claim 4, characterized in that: The motor system uses a ZLLG65ASM250-L Zhongling brushless DC hub motor, which includes wheels, a motor, a reducer, and an encoder. The battery unit uses a Panasonic LS-DL-24-40C lithium battery. The lower-level controller is an STM32F407 microcontroller. The lidar is a SIMO-LS-10H satellite-second single-line lidar. The infrared sensor is a YIYA XLHW500CM phototransistor. The upper-level controller is an I310 generation industrial computer.

Images