Intelligent collaborative building logistics robot and construction hoist system

Abstract

The invention discloses an intelligent collaborative building logistics robot and construction elevator system, which relates to the technical field of building construction collaboration and comprises a route acquisition unit, a data acquisition unit, a congestion analysis unit, a time analysis unit and a speed regulation unit. According to the invention, the sensor array collects the data of the occupied area of obstacles, the number of pedestrians and the potholes, and the congestion analysis unit calculates the congestion coefficient of the material transportation route, thereby effectively recognizing and avoiding a high-congestion region. Meanwhile, the time analysis unit accurately predicts the time required by the elevator to reach the material loading port based on the average running speed, the stopping time and the stroke height data of the elevator; the speed adjusting unit dynamically calculates the speed adjusting coefficient of the logistics robot through the preset weight coefficient, the congestion degree of the current transportation route is considered, the urgency of the arrival time of the elevator is combined, it is ensured that the logistics robot travels to the material loading port at the optimal speed, and the situation that the transportation capacity is idle due to waiting for the elevator is avoided.

Description

Technical Field

[0001] This invention relates to the field of collaborative construction technology, and in particular to an intelligent collaborative construction logistics robot and construction hoist system. Background Technology

[0002] In the field of modern construction, with the continuous expansion of project scale and the increasing complexity of construction, logistics efficiency has become one of the key factors affecting project progress and cost. Against this backdrop, logistics robots, with their automation, high efficiency, and precision, are playing an increasingly important role in material transportation within buildings. They can accurately and quickly transport various building materials from storage areas to designated locations according to preset paths, significantly improving material handling efficiency on construction sites. Meanwhile, construction hoists, as the core equipment for realizing the vertical transportation of materials across floors, are undeniably crucial. In the construction of high-rise buildings and complex structures, hoists are responsible for quickly and safely lifting materials from lower floors to the target floor, providing strong support for the continuity and efficiency of the construction process.

[0003] However, when logistics robots transport materials to the elevator, congestion on the transport path will affect the efficiency of material transport. At the same time, since the two types of equipment, logistics robots and construction elevators, usually operate independently and lack coordination, the logistics robots need to wait for the elevator to arrive for a long time after loading materials from the material storage area to transport them to the material loading port of the elevator, resulting in idle transport capacity of the logistics robots.

[0004] To address the aforementioned technical deficiencies, a solution is proposed. Summary of the Invention

[0005] The purpose of this invention is to solve the problem that when logistics robots transport materials to elevators, congestion in the transportation path affects the efficiency of material transportation. At the same time, since logistics robots and construction elevators usually operate independently and lack coordination, logistics robots need to wait for a long time for the elevator to arrive when they load materials from the material storage area to transport them to the material loading port of the elevator, resulting in idle transportation capacity of the logistics robots.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: an intelligent collaborative construction logistics robot and construction hoist system, including a route acquisition unit, a data acquisition unit, a congestion analysis unit, a time analysis unit, and a speed adjustment unit; The route acquisition unit is used to acquire the transportation route of the logistics robot from the material storage area to the material loading port of the elevator by integrating building information model data and real-time map of the construction site. The data acquisition unit is used to collect congestion data on the transportation route through sensor arrays deployed on the transportation route, to collect loading data during the transportation process of the elevator through IoT sensors deployed on the elevator, and to collect driving data of the logistics robot through the logistics robot database. The congestion analysis unit is used to receive congestion data on the transportation route and perform analysis and calculation to obtain the congestion coefficient of the material transportation route. The congestion coefficient is used to reflect the degree of congestion on the material transportation route. The time analysis unit is used to receive loading data during the elevator transportation process and perform analysis and calculation to determine the time required for the elevator to reach the material loading port; The speed adjustment unit receives the driving data of the logistics robot and analyzes and calculates it in conjunction with the congestion coefficient and the time required for the elevator to reach the material loading port, so as to obtain the speed adjustment coefficient of the logistics robot.

[0007] Furthermore, the system also includes a data transmission unit, a logistics control unit, and a vertical transportation unit. The data transmission unit is used to send congestion data to the congestion analysis unit, loading data to the time analysis unit, and driving data to the speed regulation unit via 5G mobile communication technology. The logistics control unit is used to control the logistics robot, adjust the driving speed of the logistics robot, and select the transportation route of the logistics robot. The vertical transport unit is used to receive the vertical transport task of materials between floors and control the elevator to transport the materials from the material loading port to the designated floor.

[0008] Furthermore, the congestion data includes the area occupied by obstacles on the transportation route, the number of pedestrians on the transportation route, and the area occupied by potholes on the transportation route. The loading data includes the average operating speed of the elevator, the fixed time required for the elevator to stop at a floor, and the elevator travel height data. The travel data includes the estimated time for the logistics robot to travel to the material loading port at its actual speed and the standard time required for the logistics robot to travel to the material loading port at a preset rated speed.

[0009] Furthermore, the calculation process for the congestion coefficient of the material transportation route is as follows: S11. Obtain and analyze data on the area occupied by obstacles on the transportation route, the number of pedestrians on the transportation route, and the area occupied by potholes on the transportation route. S12. Calculate the congestion coefficient of the material transportation route according to the following formula. : ; in, This refers to the number of static obstacles present along the transportation route. For the first The effective area occupied by each obstacle on the transportation route. The total area of ​​the transportation route. This refers to the number of pedestrians present along the transportation route. This represents the maximum number of pedestrians allowed on the pre-defined transportation route. This refers to the number of potholes along the transportation route. For the first The effective area occupied by potholes on the transportation route. The congestion coefficient is used to reflect the degree of congestion on the material transportation route. The higher the value of the congestion coefficient, the higher the degree of congestion on the material transportation route. S13. Obtain the congestion coefficients of multiple transportation routes for the logistics robot from the material storage area to the material loading port of the elevator, and obtain the minimum congestion coefficient by sorting them in ascending order. Select the transportation route corresponding to the minimum congestion coefficient through the logistics control unit as the transportation route for the logistics robot from the material storage area to the material loading port of the elevator.

[0010] Furthermore, the calculation process for the time required for the elevator to reach the material loading port is as follows: S21. Obtain and analyze data on the average operating speed of the elevator, the fixed time required for the elevator to stop at a floor, and the elevator travel height. S22. Calculate the time required for the elevator to reach the material loading port using the following formula. : ; in, This represents the number of floors the elevator needs to stop at before reaching the material loading port in the current transport task queue. To reach the first The travel height of each floor to which the car stops. The average operating speed of the elevator. For the elevator in the The fixed time required for stopping at each floor. The remaining height from the last designated docking level to the material loading port.

[0011] Furthermore, the calculation process for the speed adjustment coefficient of the logistics robot is as follows: S31. Obtain the estimated time for the logistics robot to travel to the material loading port at its actual speed and the standard time required for the logistics robot to travel to the material loading port at the preset rated speed, and analyze and calculate the data in combination with the congestion coefficient and the time required for the elevator to reach the material loading port. S32. Calculate the speed adjustment coefficient of the logistics robot according to the following formula. : ; in, This represents the congestion coefficient of the material transportation route. This refers to the time required for the elevator to reach the material loading port. This refers to the standard time required for a logistics robot to travel to the material loading port at a preset rated speed, assuming zero congestion on the material transport route. This is the estimated time for the logistics robot to reach the material loading port at its actual speed. The preset congestion weighting coefficient, The preset time weighting coefficient; S33. The travel speed of the logistics robot is adjusted through the logistics control unit. After adjustment, the travel speed of the logistics robot is: ,in, This refers to the speed adjustment coefficient for logistics robots. This represents the highest safe speed allowed for the robot on the current path. These are the preset speed adjustment parameters.

[0012] Furthermore, the sensor array includes a camera sensor and a lidar sensor, which uses image recognition technology to identify obstacles, pedestrians, and potholes, and works in conjunction with the lidar sensor to analyze and obtain the area occupied by obstacles and potholes. The IoT sensor includes a speed sensor, a time sensor, and a displacement sensor.

[0013] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are: This intelligent collaborative construction logistics robot and construction hoist system integrates building information modeling and real-time map data, combined with data collected by sensor arrays on obstacle occupancy area, pedestrian count, and pothole locations. A congestion analysis unit calculates the congestion coefficient of the material transport route, effectively identifying and avoiding highly congested areas. Simultaneously, a time analysis unit accurately predicts the time required for the hoist to reach the material loading port based on the hoist's average operating speed, stopping time, and travel height data. A speed adjustment unit dynamically calculates the logistics robot's speed adjustment coefficient using preset weighting coefficients, considering both the current congestion level of the transport route and the urgency of the hoist's arrival time, ensuring the logistics robot reaches the material loading port at the optimal speed and avoiding idle capacity due to waiting for the hoist. Furthermore, a data transmission unit uses 5G communication technology to achieve high-speed data transmission and real-time interaction between units. The logistics control unit comprehensively adjusts the robot's speed and route selection based on the congestion coefficient and hoist arrival time, while the vertical transport unit precisely controls the hoist to complete the material transfer task between floors. Attached Figure Description

[0014] Figure 1 A schematic diagram of the system flow of the present invention is shown. Detailed Implementation

[0015] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention. Example

[0016] like Figure 1 As shown, an intelligent collaborative construction logistics robot and construction hoist system first uses a route acquisition unit to obtain the transportation route of the logistics robot from the material storage area to the material loading port of the hoist by integrating building information model data and a real-time map of the construction site. Then, a data acquisition unit collects congestion data along the transportation route using a sensor array deployed along the route, collects loading data during the hoist's transportation process using IoT sensors deployed on the hoist, and collects the logistics robot's driving data using a logistics robot database. The congestion data includes the area occupied by obstacles on the transportation route, the number of pedestrians on the transportation route, and the area occupied by potholes on the transportation route. The loading data includes the average operating speed of the elevator, the fixed time required for the elevator to stop at each floor, and the elevator travel height. The travel data includes the estimated time for the logistics robot to travel to the material loading port at its actual speed and the standard time required for the logistics robot to travel to the material loading port at its preset rated speed. It should be further noted that the sensor array includes camera sensors and lidar sensors, which use image recognition technology to identify obstacles, pedestrians, and potholes, and use lidar sensors to analyze and obtain the area occupied by obstacles and potholes. The IoT sensors include speed sensors, time sensors, and displacement sensors.

[0017] Then, using the data transmission unit and 5G mobile communication technology, congestion data is sent to the congestion analysis unit, loading data is sent to the time analysis unit, and driving data is sent to the speed regulation unit. The congestion analysis unit receives and analyzes the congestion data on the transportation route to obtain the congestion coefficient of the material transportation route. The congestion coefficient is used to reflect the degree of congestion on the material transportation route. The calculation process for the congestion coefficient of the material transportation route is as follows: S11. Obtain and analyze data on the area occupied by obstacles on the transportation route, the number of pedestrians on the transportation route, and the area occupied by potholes on the transportation route. S12. Calculate the congestion coefficient of the material transportation route according to the following formula. : ; in, This refers to the number of static obstacles present along the transportation route. For the first The effective area occupied by each obstacle on the transportation route. The total area of ​​the transportation route. This refers to the number of pedestrians present along the transportation route. This represents the maximum number of pedestrians allowed on the pre-defined transportation route. This refers to the number of potholes along the transportation route. For the first The effective area occupied by potholes on the transportation route. The congestion coefficient is used to reflect the degree of congestion on the material transportation route. The higher the value of the congestion coefficient, the higher the degree of congestion on the material transportation route. S13. Obtain the congestion coefficients of multiple transportation routes for the logistics robot from the material storage area to the material loading port of the elevator, and obtain the minimum congestion coefficient by sorting them in ascending order. Select the transportation route corresponding to the minimum congestion coefficient through the logistics control unit as the transportation route for the logistics robot from the material storage area to the material loading port of the elevator.

[0018] Then, the loading data during the elevator transportation process is received and analyzed by the time analysis unit to obtain the time required for the elevator to reach the material loading port; The calculation process for the time required for the elevator to reach the material loading port is as follows: S21. Obtain and analyze data on the average operating speed of the elevator, the fixed time required for the elevator to stop at a floor, and the elevator travel height. S22. Calculate the time required for the elevator to reach the material loading port using the following formula. : ; in, This represents the number of floors the elevator needs to stop at before reaching the material loading port in the current transport task queue. To reach the first The travel height of each floor to which the car stops. The average operating speed of the elevator. For the elevator in the The fixed time required for stopping at each floor (including door opening, closing, loading and unloading time). The remaining height from the last designated docking level to the material loading port.

[0019] Finally, the speed adjustment unit receives the driving data of the logistics robot and analyzes and calculates it in combination with the congestion coefficient and the time required for the elevator to reach the material loading port, thus obtaining the speed adjustment coefficient of the logistics robot. The calculation process for the speed adjustment coefficient of a logistics robot is as follows: S31. Obtain the estimated time for the logistics robot to travel to the material loading port at its actual speed and the standard time required for the logistics robot to travel to the material loading port at the preset rated speed, and analyze and calculate the data in combination with the congestion coefficient and the time required for the elevator to reach the material loading port. S32. Calculate the speed adjustment coefficient of the logistics robot according to the following formula. : ; in, This represents the congestion coefficient of the material transportation route. This refers to the time required for the elevator to reach the material loading port. This refers to the standard time required for a logistics robot to travel to the material loading port at a preset rated speed, assuming zero congestion on the material transport route. This is the estimated time for the logistics robot to reach the material loading port at its actual speed. The preset congestion weighting coefficient, The preset time weighting coefficient; S33. The travel speed of the logistics robot is adjusted through the logistics control unit. After adjustment, the travel speed of the logistics robot is: ,in, This refers to the speed adjustment coefficient for logistics robots. This represents the highest safe speed allowed for the robot on the current path. With preset speed adjustment parameters, when the logistics robot transports the materials to the material loading port, and then unloads the materials into the construction hoist, the vertical transport unit controls the hoist to transport the materials from the material loading port to the designated floor.

[0020] This invention integrates building information modeling (BIM) with real-time map data, combined with data on obstacle occupancy area, pedestrian numbers, and potholes collected by a sensor array. A congestion analysis unit calculates the congestion coefficient of the material transport route, effectively identifying and avoiding highly congested areas. Simultaneously, a time analysis unit accurately predicts the time required for the elevator to reach the material loading port based on the elevator's average operating speed, stopping time, and travel height data. A speed adjustment unit dynamically calculates the logistics robot's speed adjustment coefficient using preset weighting coefficients, considering both the current congestion level of the transport route and the urgency of the elevator's arrival time, ensuring the logistics robot reaches the material loading port at the optimal speed and avoiding idle capacity due to waiting for the elevator. Furthermore, a data transmission unit uses 5G communication technology to achieve high-speed data transmission and real-time interaction between units. The logistics control unit comprehensively adjusts the robot's speed and route selection based on the congestion coefficient and elevator arrival time, while the vertical transport unit precisely controls the elevator to complete the material transfer task between floors.

[0021] The size of the interval and threshold is set to facilitate comparison. The size of the threshold depends on the amount of sample data and the number of bases set by those skilled in the art for each set of sample data; as long as it does not affect the ratio between the parameter and the quantized value.

[0022] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters in the formulas are set by those skilled in the art according to the actual situation. The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. A smart collaborative building flow robot and construction hoist system, characterized in that, The system comprises a route acquisition unit, a data acquisition unit, a congestion analysis unit, a time analysis unit, and a speed adjustment unit. The route acquisition unit is configured to acquire a transportation route of the logistics robot from a material storage area to a material loading port of an elevator by integrating building information model data and a real-time map of a construction site. The data acquisition unit is configured to acquire congestion data on the transportation route through a sensor array arranged on the transportation route, acquire loading data in the transportation process of the elevator through an Internet of Things sensor arranged on the elevator, and acquire driving data of the logistics robot through a logistics robot database. The congestion analysis unit is configured to receive and analyze the congestion data on the transportation route to obtain a congestion coefficient of the material transportation route, which reflects the congestion degree of the material transportation route. The time analysis unit is configured to receive and analyze the loading data in the transportation process of the elevator to obtain a time required for the elevator to arrive at the material loading port. The speed adjustment unit is configured to receive the driving data of the logistics robot and analyze the driving data in combination with the congestion coefficient and the time required for the elevator to arrive at the material loading port to obtain a speed adjustment coefficient of the logistics robot.

2. The intelligent, coordinated building logistics robot and construction elevator system of claim 1, wherein, The system further comprises a data transmission unit, a logistics control unit, and a vertical transportation unit. The logistics control unit is configured to control the logistics robot, adjust the driving speed of the logistics robot, and select the transportation route of the logistics robot. The vertical transportation unit is configured to receive a vertical transportation task of the material between floors, and control the elevator to transport the material from the material loading port to a specified floor.

3. The intelligent, coordinated building logistics robot and construction elevator system of claim 1, wherein, The congestion data includes obstacle occupation area on the transportation route, the number of pedestrians on the transportation route, and pothole occupation area data on the transportation route.

4. The intelligent, coordinated building logistics robot and construction elevator system of claim 1, wherein, The loading data includes average running speed of the elevator, fixed time required for the elevator to stop at a floor, and travel height data of the elevator. The driving data includes expected time for the logistics robot to travel to the material loading port at an actual speed, and standard time data required for the logistics robot to travel to the material loading port at a preset rated speed. S12, calculate the congestion coefficient of the material transportation route according to the following formula : ； wherein, is a number of static obstacles existing on the transportation route, is an effective occupation area of the th obstacle to the transportation route, is a total area of the transportation route, is a number of pedestrians existing on the transportation route, is a preset maximum number of pedestrians allowed on the transportation route, is a number of potholes existing on the transportation route, is an effective occupation area of the th pothole to the transportation route, the congestion coefficient is used to reflect the congestion degree of the material transportation route, and the larger the value of the congestion coefficient is, the higher the congestion degree of the material transportation route is. The congestion coefficient of the material transportation route is calculated as follows:

5. The intelligent, coordinated building logistics robot and construction elevator system of claim 1, wherein, S11, obtain and analyze the obstacle occupation area on the transportation route, the number of pedestrians on the transportation route, and the pothole occupation area data on the transportation route. S13, obtain the congestion coefficients of multiple transportation routes of the logistics robot from the material storage area to the material loading port of the elevator, and obtain the minimum congestion coefficient through ascending arrangement. S22. Calculate the time required for the elevator to reach the material loading port according to the following formula : ； wherein, is the number of stops the lift needs to make before reaching the material loading portal in the current transport task queue of the lift, is the travel height to the stop floor, is the average running speed of the lift, is the fixed time the lift needs to stop at the floor, is the remaining height from the last intended stop floor to the material loading portal.

6. The intelligent, coordinated building logistics robot and construction elevator system of claim 1, wherein, The time required for the elevator to arrive at the material loading port is calculated as follows: S21, obtain and analyze the average running speed of the elevator, the fixed time required for the elevator to stop at a floor, and the travel height data of the elevator. The speed adjustment coefficient of the logistics robot is calculated as follows: S31, the logistics robot is driven to the material loading port at the actual speed to obtain the expected time, and the logistics robot is driven to the material loading port at the preset rated speed to obtain standard time data, and the congestion coefficient and the time required for the elevator to arrive at the material loading port are analyzed and calculated; S32, calculate the speed adjustment coefficient of the logistics robot according to the following formula : ； wherein, is a congestion coefficient of the material transport route, is a time required for the elevator to reach the material loading port, is a standard time required for the logistics robot to travel to the material loading port at a preset rated speed in a case where the congestion coefficient of the material transport route is zero, is a predicted time required for the logistics robot to travel to the material loading port at an actual speed, is a preset congestion weight coefficient, is a preset time weight coefficient; S33, adjusting the running speed of the logistics robot by the logistics control unit, and the running speed of the logistics robot after adjustment is wherein, is a speed adjustment coefficient of the logistics robot, is a safe maximum speed allowed for the robot under the current path, is a preset speed adjustment parameter.

7. The intelligent, coordinated building logistics robot and construction elevator system of claim 1, wherein, The sensor array includes a camera sensor and a laser radar sensor, obstacles, pedestrians and potholes are identified through image recognition technology, and the laser radar sensor is used to analyze and obtain the occupied area of obstacles and potholes, and the Internet of Things sensor includes a speed sensor, a time sensor and a displacement sensor.

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