Cooperative self-adaptive intelligent planning method for complex mixed path of carrier robot

Abstract

The invention discloses a collaborative self-adaptive intelligent planning method for a complex mixed path of a carrying robot, and relates to the technical field of path planning, and the method comprises the following implementation steps: configuring a terminal server of a far-end control region of the carrying robot; entering a carrying cooperation end, realizing data intercommunication between the building elevator and the carrying robot, and judging whether the angle of the carrying robot entering and exiting the elevator is abnormal; entering a carrying synchronization end, calculating the time of taking the elevator by each carrying robot, and planning a carrying path of the carrying robot; and the robot enters an obstacle avoidance planning end, obstacles appearing at multiple angles are dynamically recognized in the carrying process, and obstacle avoidance angle adjustment of the carrying robot is achieved according to the obstacle avoidance steering angle. According to the cooperative self-adaptive intelligent planning method for the complex mixed path of the carrying robot, the elevator can monitor whether the angle of the carrying robot entering and exiting the elevator door is abnormal in time, the mutual monitoring effect between the front carrying robot and the rear carrying robot is achieved, and the obstacle avoidance accuracy of the carrying robots is improved.

Description

Technical Field

[0001] This invention relates to the field of path planning technology, and in particular to a collaborative adaptive intelligent planning method for complex hybrid paths of transport robots. Background Technology

[0002] The collaborative adaptive intelligent planning for complex hybrid paths of transport robots is a top-level intelligent decision-making system that integrates environmental perception, decision optimization, multi-robot collaboration, and real-time response. Its core objective is to enable a group of transport robots in dynamic, uncertain, and structurally complex environments to not only find safe and efficient paths individually, but also cooperate with each other as a whole to optimally complete a series of transportation tasks.

[0003] Patent publication number CN107203214A discloses a collaborative adaptive intelligent planning method for complex hybrid paths of a transport robot. This method includes: Step 1: Constructing a global... Figure 3 Step 2: Divide the global map according to floor number to obtain a 2D map and distance matrix for each floor; Step 3: Obtain the starting and ending points of the transportation task in the global map according to the transportation task instructions. Figure 3 Based on the distance matrices of each floor and all corridors and rooms within each floor, the Floyd algorithm is used for path planning in a 3D coordinate system to obtain the planned transportation path. Step 4: Control the transport robot to move forward according to the planned path to complete the transportation task. This invention reduces the computational load of the algorithm by dividing the multi-floor environment into modules, including access control, elevator interaction, and obstacle avoidance strategies, making it easier for the transport robot to perform transportation tasks in an intelligent environment.

[0004] The aforementioned patent still has some shortcomings in collaborative adaptive intelligent planning for complex hybrid paths: 1. When the transport robot enters or exits the elevator, the elevator cannot monitor in real time whether the entry or exit angle is abnormal, which can easily cause friction between the transport robot and the goods, affecting the accuracy of the angle adjustment of the transport robot when entering or exiting the elevator; 2. When multiple transport robots are transporting goods, mutual monitoring between the two transport robots in front and behind cannot be achieved, which can lead to the inability to monitor whether the transported goods are tilted in a timely manner during the dynamic monitoring of the transport robots; 3. The transport robots cannot effectively perform distributed obstacle avoidance operations when avoiding obstacles in reverse, which can easily result in ineffective obstacle avoidance.

[0005] Therefore, a collaborative adaptive intelligent planning method for complex hybrid paths of transport robots is proposed to solve the above problems. Summary of the Invention

[0006] The main objective of this invention is to provide a collaborative adaptive intelligent planning method for complex hybrid paths of transport robots, in order to solve the problems mentioned in the background above.

[0007] To achieve the above objectives, the technical solution adopted by the present invention is: a collaborative adaptive intelligent planning method for complex hybrid paths of a transport robot, the method comprising the following implementation steps: Step 1: Configure the remote control area terminal server for the transport robot; Step 2: Enter the transportation collaboration terminal, set the transported goods and transport paths of different transport robots, realize data communication between the building elevator and the transport robots, the elevator automatically recognizes the color difference of the transport robots, judges whether the angle of the transport robots entering and leaving the elevator is abnormal, and performs adaptive turning and stopping with the minimum area occupied by the elevator. In case of abnormality, the angle of entering and leaving the transport robots is automatically corrected according to the angle deviation value. Step 3: Enter the transport synchronization terminal, receive the transported goods and transport routes of different transport robots, synchronously calculate the time for each transport robot to ride the elevator, dynamically monitor the transport process of each transport robot, dynamically warn of abnormalities in transport robot riding and transport, synchronously adjust the order of transport robots riding the elevator when the warning result is abnormal, and synchronously plan the transport route of the transport robots. Step 4: Enter the obstacle avoidance planning stage. During the transportation process, obstacles appearing from multiple angles are dynamically identified. Comprehensive obstacle avoidance planning is carried out based on obstacles in different directions. The obstacle avoidance turning angle is dynamically and distributedly detected, and the obstacle avoidance angle of the transportation robot is adjusted according to the obstacle avoidance turning angle.

[0008] The transportation coordination terminal includes an equipment association module, an elevator identification module, and an entry / exit angle module; The equipment association module includes an elevator management unit and a robot management unit; The elevator management unit is used to install an elevator outdoors in the building, with the elevator positioned in the center of the building, and to remotely control the elevator through a control system. The robot management unit is used to set up multiple transport robots. The transported goods and transport paths of the multiple transport robots are connected to the control system of the elevator via a wireless network. The control system communicates with the elevator and the transport robots through the Internet of Things protocol. The multiple transport robots are arranged in ascending order of Arabic numerals, and the transported goods and transport paths of the transport robots corresponding to different numbers are set.

[0009] The elevator identification module includes a color difference identification unit and a serial number identification unit; The color difference recognition unit is used to install a camera in the middle of the elevator car and set up standard color difference images of the transport robot with different serial numbers in the elevator control system. The standard color difference images represent the standard colors of the transport robot at different heights (here, it represents the standard colors at different heights and positions; the overall color of the transport robot is input into the elevator control system before transport to achieve recognition and comparison). When the transport robot moves to the elevator recognition area according to the transport path, the color difference of the transport robot is automatically recognized. The specific method is as follows: The color of the transport robot at different heights is captured by a camera, and the color difference between the captured color and the standard color is calculated in real time using the color difference method. The serial number recognition unit is used to intelligently dock on different floors based on the color difference and serial number of different transport robots. The camera captures the serial number of the transport robot and calculates the difference between the serial number of the elevator car at the current time. If the difference is equal to 0, it means that the transport robot used by the elevator is normal. If the difference is not equal to 0, it means that the transport robot used by the elevator is abnormal, thus realizing a transport verification. Color difference at three different locations at the same height Perform a comparison, set a color difference threshold, and if three... There are at least two If the difference in color difference exceeds the color difference threshold and the sequence number difference is not equal to 0, it indicates an abnormality in the robot's operation. The robot stops, the elevator car closes, and the system is immediately notified that there is an incorrect passenger. This is then relayed to manual verification. If three... There exists a value less than or equal to one If the color difference is less than or equal to the color difference threshold and the sequence number difference is 0, it indicates that the transport robot is riding normally, and the transport robot enters the elevator car and starts the elevator.

[0010] The entry / exit angle module includes an angle recognition unit, an entry / exit judgment unit, a minimum turning stop unit, and a bidirectional correction unit; The angle recognition unit is used to calculate the maximum directional deviation angle of the transport robot in real time when the transport robot enters the elevator car, and to determine whether the angle of the transport robot entering and exiting the elevator is abnormal. The entry / exit determination unit is used to obtain the current heading angle of the transport robot in real time through sensors. ,like The absolute value is greater than or equal to If the angle at which the transport robot enters or exits the elevator is abnormal, then calculate... absolute value and The difference is used as a correction angle to automatically adjust the movement angle of the transport robot; The minimum turning stop unit is used to stop at the corner of the elevator car based on the corner position inside the elevator car, using distance sensors at the front and sides of the transport robot, thereby minimizing the space occupied in the elevator car.

[0011] The carrier synchronization terminal includes a signal receiving module, a dynamic monitoring module, and an early warning self-planning unit; The signal receiving module is used to receive the cargo and transport path of different transport robots in real time through the signal receiver; The dynamic monitoring module includes a passenger sorting unit, a front and rear monitoring unit, and a dynamic judgment unit; The seating sorting unit is used to arrange the seating and alighting of the transport robots that ride the elevator according to the floor height of the goods transported by the transport robots corresponding to different serial numbers, in order from the floor height to the floor height. After replanning the route, the unit will simultaneously fill in the missing serial number of the transport robot to ride. The front and rear monitoring units are used to dynamically monitor whether the cargo tilts in each transport robot during the transport process from the front and rear perspectives, as follows: Visual cameras are installed at the front and rear of the transport robot. The front camera captures whether the cargo of another transport robot in front of the transport robot is tilted, and the rear camera captures whether the cargo of another transport robot behind the transport robot is tilted, so as to realize the simultaneous monitoring of whether the cargo is tilted at both the front and rear of the same transport robot.

[0012] The dynamic judgment unit is used when and When both are equal to 0, it means that the cargo carried by the robot has not tilted. and If at least one of the values ​​is not equal to 0, it indicates that the cargo being transported by the robot has tilted, and the reporting system will issue a voice alarm. The early warning self-planning module includes a dynamic early warning unit, a locking sequence number unit, a planning path unit, and an elevation synchronization unit; The dynamic early warning unit is used to continue tracking the tilt angle via a visual camera. and A safe tilt angle threshold is set, with each cycle lasting 2 seconds. The system continuously tracks for three cycles. If a tilt angle is observed at least twice within the three cycles, the system will detect the tilt angle. and If all tilt angles exceed the safe tilt angle threshold, it is predicted that the transport robot cannot successfully complete the transport. The reporting system immediately issues a voice alarm and sends a signal to communicate with other transport robots. It also issues a stop transport signal to the transport robot where the cargo tilts and provides feedback for manual handling. If not, it is predicted that the transport robot is normal and the cargo tilt tracking continues in the next cycle. The locking sequence number unit is used to automatically lock the real-time location of the transport robot that is tilting when the cargo tilts, using GPS positioning and the sequence number.

[0013] The path planning unit is used to simultaneously adjust the order in which the transport robots take the elevator and replan the transport path of the transport robots when it is predicted that the transport robots cannot successfully complete the transport result. If the cargo tilts, the transport robots behind will automatically switch to the transport channel to detour. The lifting synchronization unit is used to synchronously adjust the elevator passenger sequence number through signal transmission, and automatically fill in the missing sequence number with the next corresponding transport robot passenger.

[0014] The obstacle avoidance planning module includes a multi-angle recognition module, a comprehensive obstacle avoidance module, a distributed detection module, and an obstacle avoidance correction module. The multi-angle recognition module includes a dual-camera recognition unit and a multi-angle steering unit; The dual-camera recognition unit is used to install dual-view cameras on the transport robot. The dual-view cameras are set up in two layers: the upper layer is a fixed vision camera that looks directly at the area in front of the transport robot, and the lower layer is a 360° rotatable vision camera. The multi-angle steering unit is used to automatically rotate the angle of the lower-level vision camera to capture the road conditions of the transport robot from multiple angles as it moves.

[0015] The integrated obstacle avoidance module includes a single- and multi-angle obstacle avoidance unit and a reverse obstacle avoidance unit; The single-multi-angle obstacle avoidance unit is used to calculate the obstacle avoidance angle relative to the center of the transport robot's movement path when there is only an obstacle in front of the transport robot. Calculate the direction of the gravitational force exerted on the target point of the obstacle by the transport robot; The obstacle avoidance heading angle of the transport robot is calculated by combining the obstacle avoidance angle and the direction of gravity, and the obstacle avoidance angle of the transport robot's forward view is adjusted according to the obstacle avoidance heading angle.

[0016] The distributed detection module is used to dynamically and distributedly detect the multi-angle obstacle avoidance angle deviation value when obstacles from multiple angles appear (here, distributed detection means dividing the transport robot into upper body area and lower body area for collaborative detection), determine whether multi-angle obstacle avoidance is effective, set an obstacle avoidance deviation safety threshold, and if the obstacle avoidance deviation value between the transport robot's movement trajectory and multiple obstacles is less than or equal to the obstacle avoidance deviation safety threshold, then the multi-angle obstacle avoidance is determined to be ineffective, a signal command for the transport robot to decelerate by 5% is issued, and the obstacle avoidance deviation value between the transport robot at the decelerated position and the multi-angle obstacles is continuously detected; The obstacle avoidance correction module includes an obstacle avoidance self-correction unit and a correction self-tracking unit; The obstacle avoidance self-correction unit is used to automatically correct the obstacle avoidance angle based on the angle difference between the obstacle avoidance deviation value between the transport robot's movement trajectory and multiple obstacles and the obstacle avoidance deviation safety threshold if the obstacle avoidance deviation value between the transport robot's movement angle and multiple obstacles is still less than or equal to the obstacle avoidance deviation safety threshold after three consecutive decelerations. The self-tracking correction unit is used to track the movement trajectory of the transport robot as it corrects the obstacle avoidance angle in real time using a data tracker, and calculate the difference between the value after obstacle avoidance correction and the value before correction. If the difference is equal to 0, it means that the obstacle avoidance correction is invalid and a second obstacle avoidance correction is performed. If the difference is not equal to 0, it means that the correction is valid.

[0017] The present invention has the following beneficial effects: 1. In this invention, by setting up a transport collaboration terminal, during the complex mixed path collaborative adaptive intelligent planning operation of the transport robot, by setting the transported goods and transport paths of different transport robots, the building elevator and the transport robot can achieve data communication. When the transport robot moves into the elevator's recognition area, the color difference and serial number of the transport robot are automatically identified. The elevator intelligently stops according to the color difference and serial number of different transport robots, and adaptively turns and stops at the position that occupies the smallest area of ​​the elevator. At the same time, the angle of entry and exit of the transport robot is automatically corrected according to the angle deviation value, so that when the transport robot enters and exits the elevator, the elevator can monitor in time whether the angle of the transport robot entering and exiting the elevator door is abnormal, avoiding the situation of goods rubbing when the transport robot enters and exits the elevator, and improving the accuracy of the angle adjustment of the transport robot entering and exiting the elevator. 2. In this invention, by setting up a transport synchronization terminal, during the complex hybrid path collaborative adaptive intelligent planning operation of the transport robot, the system dynamically monitors whether the cargo tilts in each transport robot from the perspectives before and after transport. Based on the monitoring results, it dynamically warns whether there are any abnormalities in the riding and transporting of the transport robot. This enables multiple transport robots to achieve mutual monitoring between the two transport robots when transporting cargo. It can also monitor whether the cargo is tilted in a timely manner during the dynamic monitoring of the transport robot, further improving the accuracy and timeliness of the monitoring of the transport robot's transport process. 3. In this invention, by setting up an obstacle avoidance planning end, during the complex hybrid path collaborative adaptive intelligent planning operation of the transport robot, dual cameras are used to identify the entire transport process and realize multi-angle turning recognition during the recognition process. For obstacles that appear during the transport process, multi-angle obstacle avoidance is performed according to different directions. During multi-angle obstacle avoidance, dynamic distributed detection of obstacle avoidance turning angle is adopted, and the obstacle avoidance angle of the transport robot is adjusted according to the obstacle avoidance turning angle. This enables the transport robot to achieve distributed obstacle avoidance operation when avoiding obstacles in the opposite direction, preventing ineffective obstacle avoidance and minimizing the damage caused by obstacle avoidance. Attached Figure Description

[0018] Figure 1 This is an overall flowchart of a collaborative adaptive intelligent planning method for complex hybrid paths of a transport robot according to the present invention; Figure 2 This is a schematic diagram of the architecture of the transport collaboration end of the complex hybrid path cooperative adaptive intelligent planning method for transport robots of the present invention; Figure 3 This is a schematic diagram of the architecture of the carrier synchronization end of the complex hybrid path cooperative adaptive intelligent planning method for a carrier robot according to the present invention; Figure 4 This is a schematic diagram of the obstacle avoidance planning end of the collaborative adaptive intelligent planning method for complex hybrid paths of a transport robot according to the present invention. Detailed Implementation

[0019] To make the technical means, creative features, objectives and effects of this invention easier to understand, the invention will be further described below in conjunction with specific embodiments.

[0020] Example 1, please refer to Figures 1 to 2 As shown: A collaborative adaptive intelligent planning method for complex hybrid paths of a transport robot, comprising the following implementation steps: Step 1: Configure the remote control area terminal server for the transport robot; Step 2: Enter the transportation collaboration terminal, set the transported goods and transport paths of different transport robots, realize data communication between the building elevator and the transport robots, the elevator automatically recognizes the color difference of the transport robots, judges whether the angle of the transport robots entering and leaving the elevator is abnormal, and performs adaptive turning and stopping with the minimum area occupied by the elevator. In case of abnormality, the angle of entering and leaving the transport robots is automatically corrected according to the angle deviation value. Step 3: Enter the transport synchronization terminal, receive the transported goods and transport routes of different transport robots, synchronously calculate the time for each transport robot to ride the elevator, dynamically monitor the transport process of each transport robot, dynamically warn of abnormalities in transport robot riding and transport, synchronously adjust the order of transport robots riding the elevator when the warning result is abnormal, and synchronously plan the transport route of the transport robots. Step 4: Enter the obstacle avoidance planning stage. During the transportation process, obstacles appearing from multiple angles are dynamically identified. Comprehensive obstacle avoidance planning is carried out based on obstacles in different directions. The obstacle avoidance turning angle is dynamically and distributedly detected, and the obstacle avoidance angle of the transportation robot is adjusted according to the obstacle avoidance turning angle.

[0021] The transportation coordination module includes an equipment association module, an elevator identification module, and an entry / exit angle module. The equipment association module includes an elevator management unit and a robot management unit; The elevator management unit is used to install an elevator outdoors in a building, with the elevator positioned in the center of the building, and to remotely control the elevator through a control system (existing technology). The robot management unit is used to set up multiple transport robots. The transported goods and transport paths of the multiple transport robots are connected to the control system of the elevator via a wireless network. The control system communicates with the elevator and the transport robots through the Internet of Things protocol. The multiple transport robots are arranged in ascending order of Arabic numerals, and the transported goods and transport paths of the transport robots corresponding to different numbers are set (existing technology).

[0022] The elevator identification module includes a color difference identification unit and a serial number identification unit; The color difference recognition unit is used to install a camera in the middle of the elevator car and set up standard color difference images of the transport robot with different serial numbers in the elevator control system. The standard color difference images represent the standard colors of the transport robot at different heights. When the transport robot moves to the recognition area of ​​the elevator according to the transport path, the color difference of the transport robot is automatically recognized. The specific method is as follows: The robot's color is captured at different heights using a camera, and the color difference between the captured color and a standard color is calculated in real time using a color difference method. The calculation formula is as follows: ; in, This represents the color difference between two color data points. This indicates the position coordinates of the first color data. This indicates the position coordinates of the second color data. This indicates the difference in brightness between two captures of the transport robot; The serial number recognition unit is used to match floors and intelligently dock based on the color difference and serial number of different transport robots. The camera captures the serial number of the transport robot and calculates the difference between the serial number of the elevator car at the current time. If the difference is equal to 0, it means that the transport robot used by the elevator is normal. If the difference is not equal to 0, it means that the transport robot used by the elevator is abnormal, thus realizing a transport verification. Color difference at three different locations at the same height Perform a comparison, set a color difference threshold, and if three... There are at least two If the difference in color difference exceeds the color difference threshold and the sequence number difference is not equal to 0, it indicates an abnormality in the robot's operation. The robot stops, the elevator car closes, and the system is immediately notified that there is an incorrect passenger. This is then relayed to manual verification. If three... There exists a value less than or equal to one If the color difference is less than or equal to the color difference threshold and the sequence number difference is 0, it indicates that the transport robot is riding normally, and the transport robot enters the elevator car and starts the elevator.

[0023] The entry / exit angle module includes an angle recognition unit, an entry / exit judgment unit, a minimum turning stop unit, and a two-way correction unit; The angle recognition unit is used to calculate the maximum directional deviation angle of the transport robot's movement in real time when the transport robot enters the elevator car, and to determine whether the angle at which the transport robot enters or exits the elevator is abnormal, as detailed below: Calculate the maximum directional deviation angle of the transport robot entering and exiting the elevator. The formula is as follows: ; in, This indicates the maximum permissible directional deviation angle for a transport robot to safely enter and exit the elevator car. Represents the arctangent function. This indicates the maximum width of the transport robot. This indicates the safety distance margin (including 5-10 centimeters). This indicates the preset safe distance from the front of the transport robot to the side of the elevator door frame; The entry / exit judgment unit is used to obtain the current heading angle of the transport robot in real time through sensors. ,like The absolute value is greater than or equal to If the angle at which the transport robot enters or exits the elevator is abnormal, then calculate... absolute value and The difference is used as a correction angle to automatically adjust the movement angle of the transport robot; The minimum corner stopping unit is used to stop at the corner of the elevator car based on the corner position of the robot, using distance sensors at the front and sides of the robot, so as to occupy the minimum space in the elevator car (in existing technology, the position can also be adjusted in real time to be close to the corner of the elevator car based on the distance sensors).

[0024] The elevator intelligently matches and docks robots based on their color differences and serial numbers. When a robot enters or exits the elevator, it automatically determines whether the robot's angle is abnormal and adaptively stops at the position that occupies the least area of ​​the elevator. If the robot's angle is abnormal, it automatically corrects the angle based on the deviation value. This allows the elevator to monitor whether the angle of the robot entering or exiting the elevator door is abnormal, thus avoiding friction between the robot and the cargo when the robot enters or exits the elevator.

[0025] Example 2, please refer to Figure 3As shown: Based on Embodiment 1, the carrier synchronization terminal includes a signal receiving module, a dynamic monitoring module, and an early warning self-planning unit; The signal receiving module is used to receive the cargo and transport path of different transport robots in real time through the signal receiver; The dynamic monitoring module includes a passenger sorting unit, a front and rear monitoring unit, and a dynamic judgment unit; The ride sequencing unit is used to arrange the ride-on robots of the elevator according to the floor height of the goods transported by the different sequence numbers of the transport robots, in order of the floor height from the lower floor height to the higher floor height, and to simultaneously fill in the next sequence number of the transport robot to ride after the path is replanned (existing technology, adjusted according to actual needs). The front and rear monitoring units are used to dynamically monitor whether the cargo is tilted by each transport robot from the front and rear perspectives during the transport process, as detailed below: Visual cameras are installed at the front and rear of the transport robot. The front camera detects whether the cargo of another transport robot in front of the transport robot is tilted, and the rear camera detects whether the cargo of another transport robot behind the transport robot is tilted. This allows for simultaneous monitoring of cargo tilting at both the front and rear of the same transport robot. The specific method is as follows: The forward tilt angle is calculated by simultaneously detecting the bounding rectangle of the cargo carried by the transport robot using both front-end and rear-end vision cameras. and rear tilt angle The formula is as follows: ; ; in, This indicates the angle between the top edge of the cargo captured by the rear transport robot and the horizontal axis of the image. This indicates the angle between the top edge of the cargo captured by the forward-moving robot and the horizontal axis of the image. , This indicates the pixel coordinates of the top-left corner of the bounding box of the detected cargo. , This represents the pixel coordinates of the upper right corner of the bounding box of the detected cargo. , This indicates the pixel coordinates of the top-left corner of the bounding box of the detected cargo. , This represents the pixel coordinates of the upper right corner of the bounding box of the detected cargo.

[0026] The dynamic judgment unit is used when and When both are equal to 0, it means that the cargo carried by the robot has not tilted. and If at least one of the values ​​is not equal to 0, it indicates that the cargo being transported by the robot has tilted, and the reporting system will issue a voice alarm. The early warning self-planning module includes a dynamic early warning unit, a locking sequence number unit, a planning path unit, and an elevation synchronization unit; The dynamic warning unit is used to continue tracking the tilt angle via a visual camera. and A safe tilt angle threshold is set, with each cycle lasting 2 seconds. The system continuously tracks for three cycles. If a tilt angle is observed at least twice within the three cycles, the system will detect the tilt angle. and If all tilt angles exceed the safe tilt angle threshold, it is predicted that the transport robot cannot successfully complete the transport. The reporting system immediately issues a voice alarm and sends a signal to communicate with other transport robots. It also issues a stop transport signal to the transport robot where the cargo tilts and provides feedback for manual handling. If not, it is predicted that the transport robot is normal and the cargo tilt tracking continues in the next cycle. The locking sequence number unit is used to automatically lock the real-time position of the transport robot that tilted when the goods tilted, using GPS positioning and sequence number (existing technology).

[0027] The path planning unit is used to simultaneously adjust the order in which the transport robots ride the elevator and replan the transport path of the transport robots when it is predicted that the transport robots will not be able to successfully complete the transport. If the cargo tilts, the transport robots behind will automatically switch to the transport channel to detour (existing technology). The lifting synchronization unit is used to synchronously adjust the elevator passenger sequence number through signal transmission, and automatically fill in the missing sequence number with the next corresponding transport robot (existing technology, if the sequence number is incorrect, it will automatically fill in the missing sequence number with the next corresponding transport robot).

[0028] During the transport process, the system dynamically monitors whether the cargo tilts on each transport robot from the perspectives before and after transport. Based on the monitoring results, it dynamically issues warnings about whether there are any abnormalities in the robot's riding and transport (if it is predicted that the transport robot cannot successfully complete the transport, it means that both the robot's riding sequence and the transport are abnormal, and the two are interconnected). When the warning results are abnormal, the system simultaneously adjusts the order in which the transport robots ride the elevator and simultaneously plans the transport path of the transport robots, so that when multiple transport robots are transporting goods, they can achieve mutual monitoring between the two transport robots in front and behind.

[0029] Example 3, please refer to Figure 4 As shown: Based on Embodiment 1, the obstacle avoidance planning module includes a multi-angle recognition module, a comprehensive obstacle avoidance module, a distributed detection module, and an obstacle avoidance correction module; The multi-angle recognition module includes a dual-camera recognition unit and a multi-angle steering unit; The dual-camera recognition unit is used to install dual-view cameras on the transport robot. The dual-view cameras are set up in two layers: the upper layer is a fixed vision camera that looks directly at the area in front of the transport robot, and the lower layer is a 360° rotatable vision camera. The multi-angle steering unit is used to automatically rotate the angle of the transport robot as it moves, using the lower-level vision camera to capture the road conditions of the transport robot from multiple angles.

[0030] The integrated obstacle avoidance module includes single and multi-angle obstacle avoidance units and reverse obstacle avoidance units; The single / multi-angle obstacle avoidance unit is used to calculate the obstacle avoidance angle relative to the center of the transport robot's movement path when an obstacle only appears in front of the transport robot. The formula is as follows: ; in, This represents the obstacle avoidance angle of an obstacle relative to the robot's movement path within the same transport lane. , Represents the coordinates of the obstacle. , This represents the coordinates of the transport robot (here, the transport robot represents the origin, and the formula calculates the angle between the vector pointing from the transport robot to the obstacle and the positive X-axis direction (usually the direction of the transport robot's front). The formula for calculating the direction of the gravitational force exerted on the transport robot by the obstacle target point is as follows: ; in, This indicates the direction of the gravitational force exerted on the target point by the obstacle by the transport robot. , This indicates the coordinates of the target point. If the obstacle is in the left front ( If the value is greater than 0, the transport robot should adjust its angle to the right, that is, to a more negative direction. If the obstacle is in front and to the right ( If the value is less than 0, the transport robot should adjust its angle to the left, that is, adjust in the correct direction; Combination and Calculate the obstacle avoidance heading angle that the transport robot will ultimately execute. The formula is as follows: ; in, Indicates according to The adjustment amount is calculated based on the distance to the obstacle (the closer the distance, the larger the adjustment; the formula for calculating the adjustment amount here is existing technology and can be adjusted according to actual needs). Adjust the obstacle avoidance angle from the front view of the transport robot.

[0031] The distributed detection module is used to dynamically and distributedly detect the deviation value of multi-angle obstacle avoidance when obstacles appear at multiple angles, and to determine whether multi-angle obstacle avoidance is effective, as detailed below: Multiple obstacles are distributed for obstacle avoidance in ascending order of their distance values. The obstacle avoidance method is as follows: S1: Calculate the coefficient of the linear term in the regression equation, using the following formula: ; in, Let be the coefficient of the first-order term, representing the quadratic relationship between the robot's movement angle and the obstacle's angle data, as detailed below: This represents the base value indicating the first deviation from the obstacle avoidance angle. This represents the base value indicating the deviation from the designated point when the first obstacle avoidance angle is reached. This represents the base value indicating the deviation of the second obstacle avoidance angle. This represents the base value indicating the deviation of the second obstacle avoidance angle from the designated point. This represents the base value of the obstacle avoidance angle deviation at the current moment. Here, it represents the deviation value at different time points and different obstacle avoidance angles. The obstacle avoidance angle represents the obstacle avoidance angle between the upper and lower parts of the transport robot and the obstacle with the corresponding number. S1: Calculate the coefficient of the quadratic term in the regression equation, using the following formula: ; in, It represents the coefficient of the quadratic term and also represents the binary quadratic relationship between the pitch angle value of the transport robot and the obstacle angle data when the robot moves; ; in, Represents the coefficient of the constant term. This represents the average value of the obstacle avoidance angle deviation at the current moment. The obstacle avoidance angle here refers to the pitch angle of obstacle avoidance and the obstacle avoidance angle relative to the specified number obstacle. Indicates the first The deviation value of each obstacle avoidance angle This represents the average value of all obstacle avoidance deformation data in the pitch angle dataset when the transport robot is moving. This represents the average value of all obstacle avoidance angle data in the angle dataset (here, pitch angle refers to the body changes caused by inertia during the acceleration, deceleration, and movement of the transport robot). S1: Based on the coefficients of the first term, the second term, and the constant term, a regression equation is established to obtain the obstacle avoidance deviation value between the moving trajectory of the transport robot and multiple obstacles. An obstacle avoidance deviation safety threshold is set. If the obstacle avoidance deviation value between the moving trajectory of the transport robot and multiple obstacles is less than or equal to the obstacle avoidance deviation safety threshold, it is determined that multi-angle obstacle avoidance is invalid. A signal command for the transport robot to decelerate by 5% is issued, and the obstacle avoidance deviation value between the transport robot and multi-angle obstacles at the decelerated position is continuously detected. The obstacle avoidance correction module includes an obstacle avoidance self-correction unit and a correction self-tracking unit; The obstacle avoidance self-correction unit is used to automatically correct the obstacle avoidance angle if the obstacle avoidance deviation value between the robot's movement trajectory and multiple obstacles is still less than or equal to the obstacle avoidance deviation safety threshold after three consecutive decelerations. This is done based on the angle difference between the obstacle avoidance deviation value between the robot's movement angle and multiple obstacles at different angles and the obstacle avoidance deviation safety threshold. (Here, when the obstacle avoidance deviation value is still less than or equal to the obstacle avoidance deviation safety threshold, obstacle avoidance adjustment is first performed according to the nearest corresponding number of obstacle, and then distributed obstacle avoidance adjustment is performed according to distance. This achieves effective switching when simultaneous obstacle avoidance at multiple angles is ineffective and further improves obstacle avoidance safety stability.) The self-tracking correction unit is used to track the movement trajectory of the transport robot in real time as it corrects the obstacle avoidance angle using a data tracker. It calculates the difference between the value after obstacle avoidance correction and the value before correction. If the difference is equal to 0, it means that the obstacle avoidance correction is invalid and a second obstacle avoidance correction is performed. If the difference is not equal to 0, it means that the correction is valid.

[0032] For obstacles encountered during transport, multi-angle obstacle avoidance is performed according to different directions. During multi-angle obstacle avoidance, dynamic distributed detection of obstacle avoidance turning angle is adopted, and the obstacle avoidance angle of the transport robot is adjusted according to the obstacle avoidance turning angle.

[0033] This invention discloses a collaborative adaptive intelligent planning method for complex hybrid paths of transport robots. First, a terminal server is configured in the remote control area of ​​the transport robot. Then, the transport collaboration terminal is accessed, and the transported goods and paths of different transport robots are set. Data communication is established between the building elevator and the transport robots. The elevator automatically identifies color differences in the transport robots, determines whether the angles at which the transport robots enter and exit the elevator are abnormal, and performs adaptive turning and stopping with minimal occupation of the elevator area. In case of abnormalities, the entry and exit angles are automatically corrected based on the angle deviation value. By setting the transported goods and paths of different transport robots, the method achieves the desired intelligent planning. The building elevator and the transport robot achieve data interoperability. When the transport robot moves into the elevator's recognition area, the elevator automatically identifies the robot's color difference and serial number. The elevator intelligently matches the floor based on the color difference and serial number of different transport robots and stops accordingly. When a transport robot enters or exits the elevator, the elevator automatically judges whether the angle of entry or exit is abnormal and adaptively stops at a position that occupies the minimum area of ​​the elevator. If the angle of entry or exit is abnormal, the elevator automatically corrects the angle based on the deviation value, enabling the elevator to monitor the transport robot's entry and exit in a timely manner. The system monitors the angle at which robots enter and exit the elevator doors to prevent cargo friction during robot entry and exit, thus improving the accuracy of angle adjustments. It also integrates with the transport synchronization system to receive cargo and transport paths from different robots, simultaneously calculates the time each robot takes to ride the elevator, and dynamically monitors the transport process. The system provides dynamic warnings for robot rides and transport anomalies, and adjusts the robot's order of elevator rides and plans transport paths in real time when anomalies are detected. This is achieved by receiving real-time cargo data from different robots. The system monitors the cargo tilting of each transport robot from both front and rear perspectives during transport, and provides dynamic warnings based on the monitoring results to detect any abnormalities in the robot's riding and transport. If an abnormality is detected, the system simultaneously adjusts the order in which the robots ride the elevator and plans the transport path accordingly. This allows multiple transport robots to monitor each other during cargo transport, enabling timely detection of cargo tilting and further improving the accuracy, timeliness, and effectiveness of monitoring the transport process.Upon entering the obstacle avoidance planning stage, obstacles appearing from multiple angles are dynamically identified during transport. Comprehensive obstacle avoidance planning is performed based on obstacles from different directions. The obstacle avoidance turning angle is dynamically and distributedly detected, and the robot's obstacle avoidance angle is adjusted accordingly. Dual cameras identify the entire transport process from all directions, enabling multi-angle turning recognition. For obstacles encountered during transport, multi-angle obstacle avoidance is performed based on different directions. During multi-angle obstacle avoidance, the turning angle is dynamically and distributedly detected, and the robot's obstacle avoidance angle is adjusted accordingly. This allows the robot to perform distributed obstacle avoidance operations during reverse obstacle avoidance, preventing ineffective obstacle avoidance and minimizing damage caused by obstacle avoidance.

[0034] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of this invention is defined by the appended claims and their equivalents.

Claims

1. A collaborative adaptive intelligent planning method for complex hybrid paths of a transport robot, characterized in that, The method includes the following implementation steps: Step 1: Configure the remote control area terminal server for the transport robot; Step 2: Enter the transportation collaboration terminal, set the transported goods and transport paths of different transport robots, realize data communication between the building elevator and the transport robots, the elevator automatically recognizes the color difference of the transport robots, judges whether the angle of the transport robots entering and leaving the elevator is abnormal, and performs adaptive turning and stopping with the minimum area occupied by the elevator. In case of abnormality, the angle of entering and leaving the transport robots is automatically corrected according to the angle deviation value. Step 3: Enter the transport synchronization terminal, receive the transported goods and transport routes of different transport robots, synchronously calculate the time for each transport robot to ride the elevator, dynamically monitor the transport process of each transport robot, dynamically warn of abnormalities in transport robot riding and transport, synchronously adjust the order of transport robots riding the elevator when the warning result is abnormal, and synchronously plan the transport route of the transport robots. Step 4: Enter the obstacle avoidance planning stage. During the transportation process, obstacles appearing from multiple angles are dynamically identified. Comprehensive obstacle avoidance planning is carried out based on obstacles in different directions. The obstacle avoidance turning angle is dynamically and distributedly detected, and the obstacle avoidance angle of the transportation robot is adjusted according to the obstacle avoidance turning angle.

2. The method according to claim 1, characterized in that: The transportation coordination terminal includes an equipment association module, an elevator identification module, and an entry / exit angle module; The equipment association module includes an elevator management unit and a robot management unit; The elevator management unit is used to install an elevator outdoors in the building, with the elevator positioned in the center of the building, and to remotely control the elevator through a control system. The robot management unit is used to set up multiple transport robots. The transported goods and transport paths of the multiple transport robots are connected to the control system of the elevator via a wireless network. The control system communicates with the elevator and the transport robots through the Internet of Things protocol. The multiple transport robots are arranged in ascending order of Arabic numerals, and the transported goods and transport paths of the transport robots corresponding to different numbers are set.

3. The method according to claim 2, characterized in that: The elevator identification module includes a color difference identification unit and a serial number identification unit; The color difference recognition unit is used to install a camera at the center position inside the elevator car, and to set up standard color difference images of the transport robot with different serial numbers in the elevator control system. The standard color difference images represent the standard colors of the transport robot at different heights. When the transport robot moves to the elevator recognition area according to the transport path, the color difference of the transport robot is automatically recognized. The specific method is as follows: The robot's color is captured at different heights using a camera, and the color difference between the captured color and a standard color is calculated in real time using a color difference method. The calculation formula is as follows: ； in, This represents the color difference between two color data points. This indicates the position coordinates of the first color data. This indicates the position coordinates of the second color data. This indicates the difference in brightness between two captures of the transport robot; The serial number recognition unit is used to intelligently dock on different floors based on the color difference and serial number of different transport robots. The camera captures the serial number of the transport robot and calculates the difference between the serial number of the elevator car at the current time. If the difference is equal to 0, it means that the transport robot used by the elevator is normal. If the difference is not equal to 0, it means that the transport robot used by the elevator is abnormal, thus realizing a transport verification. Color difference at three different locations at the same height Perform a comparison, set a color difference threshold, and if three... There are at least two If the difference in color difference exceeds the color difference threshold and the sequence number difference is not equal to 0, it indicates an abnormality in the robot's operation. The robot stops, the elevator car closes, and the system is immediately notified that there is an incorrect passenger. This is then relayed to manual verification. If three... There exists a value less than or equal to one If the color difference is less than or equal to the color difference threshold and the sequence number difference is 0, it indicates that the transport robot is riding normally, and the transport robot enters the elevator car and starts the elevator.

4. The method according to claim 3, characterized in that: The entry / exit angle module includes an angle recognition unit, an entry / exit judgment unit, a minimum turning stop unit, and a bidirectional correction unit. The angle recognition unit is used to calculate the maximum directional deviation angle of the transport robot's movement in real time when the transport robot enters the elevator car, and to determine whether the angle of the transport robot entering or exiting the elevator is abnormal, as detailed below: Calculate the maximum directional deviation angle of the transport robot entering and exiting the elevator. The formula is as follows: ； in, This indicates the maximum permissible directional deviation angle for a transport robot to safely enter and exit the elevator car. Represents the arctangent function. This indicates the maximum width of the transport robot. Indicates the safety distance margin. This indicates the preset safe distance from the front of the transport robot to the side of the elevator door frame; The entry / exit determination unit is used to obtain the current heading angle of the transport robot in real time through sensors. ,like The absolute value is greater than or equal to If the angle at which the transport robot enters or exits the elevator is abnormal, then calculate... absolute value and The difference is used as a correction angle to automatically adjust the movement angle of the transport robot; The minimum turning stop unit is used to stop at the corner of the elevator car based on the corner position inside the elevator car, using distance sensors at the front and sides of the transport robot, thereby minimizing the space occupied in the elevator car.

5. The method according to claim 1, characterized in that: The carrier synchronization terminal includes a signal receiving module, a dynamic monitoring module, and an early warning self-planning unit; The signal receiving module is used to receive the cargo and transport path of different transport robots in real time through the signal receiver; The dynamic monitoring module includes a passenger sorting unit, a front and rear monitoring unit, and a dynamic judgment unit; The seating sorting unit is used to arrange the seating and alighting of the transport robots that ride the elevator according to the floor height of the goods transported by the transport robots corresponding to different serial numbers, in order from the floor height to the floor height. After replanning the route, the unit will simultaneously fill in the missing serial number of the transport robot to ride. The front and rear monitoring units are used to dynamically monitor whether the cargo tilts in each transport robot during the transport process from the front and rear perspectives, as follows: Visual cameras are installed at the front and rear of the transport robot. The front camera detects whether the cargo of another transport robot in front of the transport robot is tilted, and the rear camera detects whether the cargo of another transport robot behind the transport robot is tilted. This allows for simultaneous monitoring of cargo tilting at both the front and rear of the same transport robot. The specific method is as follows: The forward tilt angle is calculated by simultaneously detecting the bounding rectangle of the cargo carried by the transport robot using both front-end and rear-end vision cameras. and rear tilt angle The formula is as follows: ； ； in, This indicates the angle between the top edge of the cargo captured by the rear transport robot and the horizontal axis of the image. This indicates the angle between the top edge of the cargo captured by the forward-moving robot and the horizontal axis of the image. , This indicates the pixel coordinates of the top-left corner of the bounding box of the detected cargo. , This represents the pixel coordinates of the upper right corner of the bounding box of the detected cargo. , This indicates the pixel coordinates of the top-left corner of the bounding box of the detected cargo. , This represents the pixel coordinates of the upper right corner of the bounding box of the detected cargo.

6. The method according to claim 5, characterized in that: The dynamic judgment unit is used when and When both are equal to 0, it means that the cargo carried by the robot has not tilted. and If at least one of the values ​​is not equal to 0, it indicates that the cargo being transported by the robot has tilted, and the reporting system will issue a voice alarm. The early warning self-planning module includes a dynamic early warning unit, a locking sequence number unit, a planning path unit, and an elevation synchronization unit; The dynamic early warning unit is used to continue tracking the tilt angle via a visual camera. and A safe tilt angle threshold is set, with each cycle lasting 2 seconds. The system continuously tracks for three cycles. If a tilt angle is observed at least twice within the three cycles... and If all tilt angles exceed the safe tilt angle threshold, it is predicted that the transport robot cannot successfully complete the transport. The reporting system immediately issues a voice alarm and sends a signal to communicate with other transport robots. It also issues a stop transport signal to the transport robot where the cargo tilts and provides feedback for manual handling. If not, it is predicted that the transport robot is normal and the cargo tilt tracking continues in the next cycle. The locking sequence number unit is used to automatically lock the real-time location of the transport robot that is tilting when the cargo tilts, using GPS positioning and the sequence number.

7. The method according to claim 6, characterized in that: The path planning unit is used to simultaneously adjust the order in which the transport robots take the elevator and replan the transport path of the transport robots when it is predicted that the transport robots cannot successfully complete the transport result. If the cargo tilts, the transport robots behind will automatically switch to the transport channel to detour. The lifting synchronization unit is used to synchronously adjust the elevator passenger sequence number through signal transmission, and automatically fill in the missing sequence number with the next corresponding passenger robot.

8. The method according to claim 1, characterized in that: The obstacle avoidance planning module includes a multi-angle recognition module, a comprehensive obstacle avoidance module, a distributed detection module, and an obstacle avoidance correction module. The multi-angle recognition module includes a dual-camera recognition unit and a multi-angle steering unit; The dual-camera recognition unit is used to install dual-view cameras on the transport robot. The dual-view cameras are set up in two layers: the upper layer is a fixed vision camera that looks directly at the area in front of the transport robot, and the lower layer is a 360° rotatable vision camera. The multi-angle steering unit is used to automatically rotate the angle of the lower-level vision camera to capture the road conditions of the transport robot from multiple angles as it moves.

9. The method according to claim 8, characterized in that: The integrated obstacle avoidance module includes a single- and multi-angle obstacle avoidance unit and a reverse obstacle avoidance unit; The single / multi-angle obstacle avoidance unit is used to calculate the obstacle avoidance angle relative to the center of the transport robot's movement path when an obstacle only appears in front of the transport robot. The formula is as follows: ； in, This represents the obstacle avoidance angle of an obstacle relative to the robot's movement path within the same transport lane. , Represents the coordinates of the obstacle. , Indicates the coordinates of the transport robot; The formula for calculating the direction of the gravitational force exerted on the transport robot by the obstacle target point is as follows: ； in, This indicates the direction of the gravitational force exerted on the target point by the obstacle by the transport robot. , Represents the coordinates of the target point; Combination and Calculate the obstacle avoidance heading angle that the transport robot will ultimately execute. The formula is as follows: ； in, Indicates according to The adjustment amount calculated based on the distance to the obstacle, according to Adjust the obstacle avoidance angle from the front view of the transport robot.

10. The method according to claim 9, characterized in that: The distributed detection module is used to dynamically and distributedly detect the multi-angle obstacle avoidance angle deviation value when obstacles at multiple angles appear, determine whether multi-angle obstacle avoidance is effective, and set an obstacle avoidance deviation safety threshold. If the obstacle avoidance deviation value between the moving trajectory of the transport robot and multiple obstacles is less than or equal to the obstacle avoidance deviation safety threshold, it is determined that multi-angle obstacle avoidance is invalid, and a signal command for the transport robot to decelerate by 5% is issued. The module also continuously detects the obstacle avoidance deviation value between the transport robot and the multi-angle obstacles at the decelerated position. The obstacle avoidance correction module includes an obstacle avoidance self-correction unit and a correction self-tracking unit; The obstacle avoidance self-correction unit is used to automatically correct the obstacle avoidance angle based on the angle difference between the obstacle avoidance deviation value between the transport robot's movement trajectory and multiple obstacles and the obstacle avoidance deviation safety threshold if the obstacle avoidance deviation value between the transport robot's movement angle and multiple obstacles is still less than or equal to the obstacle avoidance deviation safety threshold after three consecutive decelerations. The self-tracking correction unit is used to track the movement trajectory of the transport robot as it corrects the obstacle avoidance angle in real time using a data tracker, and calculate the difference between the value after obstacle avoidance correction and the value before correction. If the difference is equal to 0, it means that the obstacle avoidance correction is invalid and a second obstacle avoidance correction is performed. If the difference is not equal to 0, it means that the correction is valid.

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