Intelligent transportation robot capable of transferring materials

Abstract

The invention relates to the technical field of building construction mechanical automation, and discloses a turnover material intelligent transportation robot which comprises a walking chassis module, a vertical lifting module is installed at the top of the walking chassis module, and a material recognition module is installed at the front end of the top of the walking chassis module. A mechanical arm loading module is installed in the middle of the top of the walking chassis module. According to the intelligent transportation robot for the turnover materials, the input cost of special lifting equipment can be saved by reusing a construction elevator transmission system, the 3D visual recognition system can adapt to the material positioning requirement under the complex construction site environment, and the dependence of turnover material transportation on manpower in super high-rise construction is reduced; automatic identification and accurate classification and stacking of scaffold tubes and other materials are achieved, rapid and accurate identification of the materials is achieved through the RFID identification system, the construction efficiency is further improved, and the functions of omnidirectional obstacle avoidance, emergency braking and self-adaptive adjustment of the track support are achieved through the safety protection module.

Description

Technical Field

[0001] This invention relates to the field of automation technology in construction machinery, specifically to an intelligent transport robot for reusable materials. Background Technology

[0002] In the construction of super high-rise buildings, the transportation efficiency of reusable materials directly affects the project progress and cost. Currently, the industry generally relies on manual handling combined with traditional equipment such as tower cranes and winches for material transfer. This method has problems such as high manpower consumption, high operational risks, and intermittent waiting. As the building height increases, the frequency of material transfer increases exponentially. Traditional methods can no longer meet the construction efficiency requirements of modern super high-rise buildings. In recent years, the field of construction robots has made breakthroughs in processes such as masonry and spraying, but intelligent transportation equipment for rod-type materials is still lacking.

[0003] Among existing technological solutions, manual handling + hopper transfer: workers collect materials into hoppers and then use tower cranes to lift them to the target floor. The advantage is that it can adapt to irregular material shapes, but the disadvantage is that it relies on manpower and there is a risk of falling from heights. Unloading platform + winch system: materials are piled up on the unloading platform and then lifted by a winch. The advantage is that it has a strong continuous transportation capacity, but the disadvantage is that it requires a fixed installation platform and cannot achieve precise classification and stacking. Tower crane direct lifting: materials are tied with slings and transported vertically. The advantage is that it has high flexibility, but the disadvantage is that it requires frequent use of tower crane resources and has low loading and unloading efficiency.

[0004] Existing technologies still have the following problems: high reliance on human labor leads to rising costs and safety hazards; traditional equipment cannot achieve automatic identification and classification of materials; and there are resource conflicts with other construction equipment during vertical transportation. Therefore, there is an urgent need for a reusable intelligent material transportation robot. Summary of the Invention

[0005] The purpose of this invention is to provide a reusable intelligent material transport robot to solve the problems mentioned in the background art.

[0006] To solve the above-mentioned technical problems, the present invention provides the following technical solution: a reusable material intelligent transportation robot, including a walking chassis module, a vertical lifting module installed on the top of the walking chassis module, a material identification module installed at the front end of the top of the walking chassis module, and a robotic arm loading module installed in the middle of the top of the walking chassis module. The walking chassis module includes tracked drive wheels and a steering mechanism. The track width is 200mm, the track pitch is 100mm, and the rated load is ≥500kg. The vertical lifting module includes guide rails and a gear transmission box that match the standard section of the construction elevator. The output shaft tooth profile of the gear transmission box meshes with the gears of the construction elevator. The gear transmission box uses 20CrMnTi alloy steel quenched gears with a module of 4.5 and 28 teeth.

[0007] Preferably, the material identification module uses a 3D vision sensor with a scanning radius covering a range of 5 meters. The 3D vision sensor is Azure Kinect DK based on the ToF principle, with a resolution of 1280×1024, a frame rate of 30fps, and a depth accuracy of ±2mm.

[0008] Preferably, the robotic arm loading module consists of a six-degree-of-freedom articulated arm, an electromagnetic gripper, and a rotating chassis. The electromagnetic gripper has a rated suction force of ≥200kg and is compatible with scaffold tubes with a diameter of 48-60mm. The six-degree-of-freedom articulated arm has a load capacity of ≥100kg and a repeatability of ±0.05mm.

[0009] Preferably, it also includes a control system module, which is electrically connected to the walking chassis module, vertical lifting module, material identification module and robotic arm loading module via a wireless port. The control system module includes a microprocessor and a display panel, integrates a PLC controller, sensor interface and human-machine interface, and uses a Siemens S7-1200 series PLC with an EtherCAT bus interface and supports Modbus TCP / IP communication protocol.

[0010] Preferably, the walking chassis module further includes a track support, which is a self-lifting track support, and the track support is electrically connected to the control system module.

[0011] Preferably, the material identification module also includes multispectral imaging capabilities, adding infrared and ultraviolet imaging technologies in addition to 3D vision.

[0012] Preferably, the robotic arm loading module further includes a torque sensor to monitor the grasping force in real time and to monitor whether an object is grasped each time the gripping is performed.

[0013] Preferably, the material identification module further includes an RFID identification system, with an electronic tag pre-embedded at the end of the material. The RFID identification system is compatible with the electronic tag, and the RFID identification system is electrically connected to the control system module. The RFID system includes an RFID reader / writer, which uses high-frequency reading and writing, operates at a frequency of 915MHz, and has a reading distance of ≥3 meters.

[0014] Preferably, it also includes a safety protection module, which includes a laser obstacle avoidance sensor and an emergency braking system. The laser obstacle avoidance sensor is installed around the steering mechanism, the emergency braking system is integrated into the chassis module, the emergency braking system is electrically connected to the control system module, the laser obstacle avoidance sensor is signal connected to the control system module, and the laser obstacle avoidance sensor is electrically connected to the track support.

[0015] Compared with the prior art, the beneficial effects achieved by the present invention are: Firstly, in this invention, the material identification module generates three-dimensional coordinates after identifying scattered materials through a vision system. Then, the control system plans the movement trajectory of the robotic arm. After the electromagnetic gripper adsorbs the materials, the device moves to the construction elevator shaft via the walking chassis module. The vertical lifting module's gears mesh with the elevator's standard section, achieving vertical movement via a motor drive. Upon reaching the target floor, the direction is adjusted by rotating the chassis, and the height is adjusted by a six-degree-of-freedom articulated arm, allowing the robotic arm to classify and stack the materials in a designated area according to a preset program. The steering mechanism uses a hydraulic steering system with a steering angle of ±45° and a steering radius ≤1.5m. The walking chassis module has obstacle-crossing capabilities and can move freely on complex ground surfaces via tracked supports. Multispectral imaging is also included. Functions: The system incorporates infrared and ultraviolet imaging technology, with an infrared wavelength range of 8-14μm and an ultraviolet wavelength range of 200-400nm, to identify surface defects and material properties. This information is then uploaded to the control panel. A torque sensor monitors the grasping force in real time with an accuracy of ±1N·m. The sensor detects whether an object is grasped during each gripping attempt. If a gripping attempt fails more than five times, an alarm is sent to the display panel via the control system. This solution saves on the cost of dedicated lifting equipment by reusing the construction elevator drive system. The 3D vision recognition system adapts to the material positioning needs of complex construction sites, reducing reliance on manual labor for transporting reusable materials in high-rise construction and enabling automatic identification and precise classification and stacking of materials such as scaffolding pipes.

[0016] Secondly, this invention utilizes an RFID identification system to enhance the material identification module. Building upon existing 3D vision sensor scanning as base data and multispectral imaging as an auxiliary function, the RFID identification system is the primary tool for classifying and processing each material. Electronic tags are pre-embedded at the ends of the materials, storing material type, specifications, and production date information. The RFID reader employs high-frequency reading and writing at 915MHz, with a reading distance ≥3 meters, and supports the ISO18000-6C protocol. Data transmission: The RFID identification system is electrically connected to the control system module, transmitting material information to the control system module in real time. The location of the scaffolding pipe is determined by a wide-range scan using the 3D vision sensor, and then precisely confirmed by the RFID identification system, further ensuring accurate material classification. The control system module integrates the 3D vision scan data with the RFID tag information to generate a complete material identification report, achieving rapid and accurate material identification, further improving construction efficiency, reducing labor costs, and enhancing the transparency and security of material management.

[0017] Thirdly, in this invention, the safety protection module is installed on the chassis module as a further safety guarantee for equipment movement. Four sets of laser obstacle avoidance sensors are distributed around the steering mechanism, covering 360° omnidirectional obstacle avoidance. The installation height is ≥0.5 meters above the ground to avoid interference from ground obstacles. It uses a SICKLMS511 laser radar with a scanning frequency of 75Hz, an angular resolution of 0.33°, a maximum measurement distance of 80 meters, and a laser wavelength of 905nm, conforming to Class 1 laser safety standards. It communicates with the control system module via a wireless port, transmitting obstacle distance, angle, and speed information in real time. This allows operators to remotely adjust the equipment position manually or automatically based on the obstacle locations provided by the safety protection module, avoiding collisions. The laser obstacle avoidance sensors detect the height of obstacles. When an obstacle is abnormally shaped, the control system module automatically adjusts the height of the track support to avoid collisions. For obstacles that are too high, it directly avoids them. The control system module receives point cloud data and uses the SLAM algorithm to synchronously locate and build a map, updating the environmental map in real time, identifying obstacle types and movement states. When the distance to an obstacle is ≤2 meters, the control system module issues an audible and visual warning through the display panel to remind the operator. When the distance to an obstacle is ≤1 meter, the control system module immediately triggers the emergency braking system, applying maximum braking force to the hydraulic brake. At the same time, the control system module sends a stop command to the robotic arm loading module to prevent the robotic arm from misoperating. This achieves omnidirectional obstacle avoidance, emergency braking, and adaptive adjustment of the track support, enhancing the equipment's adaptability to complex environments and further solving the problem of high reliance on human labor. Attached Figure Description

[0018] Figure 1 This is a three-dimensional schematic diagram of the overall structure of the present invention; Figure 2 This is a three-dimensional schematic diagram of the walking chassis module of the present invention; Figure 3 This is a three-dimensional schematic diagram of the vertical lifting module of the present invention; Figure 4 This is a three-dimensional schematic diagram of the robotic arm loading module of the present invention.

[0019] Legend: 1. Walking chassis module; 101. Steering mechanism; 102. Tracked drive wheel; 2. Vertical lifting module; 201. Guide rail; 202. Gear transmission box; 3. Material identification module; 4. Robotic arm loading module; 401. Six-degree-of-freedom articulated arm; 402. Electromagnetic gripper; 403. Rotating chassis; 5. Safety protection module; 501. Laser obstacle avoidance sensor. Detailed Implementation

[0020] 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

[0021] like Figure 1 , Figure 2 , Figure 3 , Figure 4 As shown, the present invention provides a technical solution: a reusable intelligent material transport robot, including a walking chassis module 1, a vertical lifting module 2 installed on the top of the walking chassis module 1, a material identification module 3 installed at the front end of the top of the walking chassis module 1, and a robotic arm loading module 4 installed in the middle of the top of the walking chassis module 1. The walking chassis module 1 includes tracked drive wheels 102 and a steering mechanism 101. The track width is 200mm, the track pitch is 100mm, and the rated load is ≥500kg. The vertical lifting module 2 includes a guide rail 201 that matches the standard section of the construction elevator and a gear transmission box 202. The output shaft tooth profile of the gear transmission box 202 meshes with the gear of the construction elevator. The gear transmission box 202 uses 20CrMnTi alloy steel quenched gears with a module of 4.5 and 28 teeth.

[0022] The material identification module 3 uses a 3D vision sensor with a scanning radius covering a range of 5 meters. The 3D vision sensor is Azure Kinect DK based on the ToF principle, with a resolution of 1280×1024, a frame rate of 30fps, and a depth accuracy of ±2mm.

[0023] The robotic arm loading module 4 consists of a six-degree-of-freedom articulated arm 401, an electromagnetic gripper 402, and a rotating chassis 403. The electromagnetic gripper 402 has a rated suction force of ≥200kg and is compatible with scaffold tubes with a diameter of 48-60mm. The six-degree-of-freedom articulated arm 401 has a load capacity of ≥100kg and a repeatability of ±0.05mm.

[0024] It also includes a control system module, which is electrically connected to the walking chassis module 1, the vertical lifting module 2, the material identification module 3 and the robotic arm loading module 4 via a wireless port. The control system module includes a microprocessor and a display panel, and integrates a PLC controller, sensor interface and human-machine interface. It uses a Siemens S7-1200 series PLC, which has an EtherCAT bus interface and supports Modbus TCP / IP communication protocol.

[0025] The walking chassis module 1 also includes a track support, which is a self-lifting track support and is electrically connected to the control system module.

[0026] The material identification module 3 also includes multispectral imaging capabilities, adding infrared and ultraviolet imaging technologies in addition to 3D vision.

[0027] The robotic arm loading module 4 also includes a torque sensor to monitor the grasping force in real time and to monitor whether an object is grasped each time.

[0028] Through the above technical solution, the material identification module 3 generates three-dimensional coordinates after identifying scattered materials through the vision system, and then plans the movement trajectory of the robotic arm through the control system. After the electromagnetic gripper 402 adsorbs the materials, the equipment moves to the construction elevator shaft position through the walking chassis module 1. The gear of the vertical lifting module 2 meshes with the standard section of the elevator, and the vertical movement is achieved by the motor drive. After reaching the target floor, the direction is adjusted by rotating the chassis 403, and the height is adjusted by the six-degree-of-freedom articulated arm 401, so that the robotic arm can classify and stack the materials in the designated area according to the preset program. Among them, the steering mechanism 101 adopts a hydraulic steering system with a steering angle of ±45° and a steering radius of ≤1.5m. The walking chassis module 1 has obstacle crossing ability and can move freely on the ground with complex working environment through the track support. The system features multispectral imaging capabilities, including infrared and ultraviolet imaging (8-14μm infrared wavelength range, 200-400nm ultraviolet wavelength range) to identify surface defects and material properties. This information is then uploaded to the control panel. A torque sensor monitors the gripping force in real-time with an accuracy of ±1N·m. The sensor detects whether an object is grasped during each gripping attempt; if the grasping attempt fails more than five times, an alarm is sent to the display panel via the control system. This solution saves on the cost of dedicated lifting equipment by reusing the construction elevator drive system. The 3D vision recognition system adapts to the material positioning needs of complex construction sites, reducing reliance on manual labor for transporting reusable materials in high-rise construction and enabling automatic identification and precise classification and stacking of materials such as scaffolding pipes. Example

[0029] like Figure 1 , Figure 2 , Figure 3 , Figure 4 As shown, the present invention provides a technical solution: a reusable intelligent material transport robot, the material identification module 3 also includes an RFID identification system, an electronic tag is pre-embedded at the end of the material, the RFID identification system is adapted to the electronic tag, the RFID identification system is electrically connected to the control system module, the RFID system includes an RFID reader, adopts high-frequency reading and writing, the working frequency is 915MHz, and the reading distance is ≥3 meters.

[0030] Through the above technical solution, the RFID identification system is used to improve the material identification module 3. It uses the existing 3D vision sensor scanning as the base data and multispectral imaging as an auxiliary function. The RFID identification system is the main body for classifying and processing each material. Electronic tags are pre-embedded at the ends of the materials, storing material type, specifications, and production date information. The RFID reader uses high-frequency reading and writing, with a working frequency of 915MHz and a reading distance of ≥3 meters, supporting the ISO18000-6C protocol. Data transmission: The RFID identification system is electrically connected to the control system module, transmitting material information to the control system module in real time. The large-scale scanning of the 3D vision sensor determines the location of the scaffolding pipes, and the RFID identification system performs precise confirmation, further ensuring accurate material classification. The control system module integrates the 3D vision scanning data with the RFID tag information to generate a complete material identification report, achieving rapid and accurate material identification, further improving construction efficiency, reducing labor costs, and enhancing the transparency and security of material management. Example

[0031] like Figure 1 , Figure 2 , Figure 3 , Figure 4 As shown, the present invention provides a technical solution: a reusable material intelligent transport robot, which also includes a safety protection module 5. The safety protection module 5 includes a laser obstacle avoidance sensor 501 and an emergency braking system. The laser obstacle avoidance sensor 501 is installed around the steering mechanism 101. The emergency braking system is integrated into the walking chassis module 1. The emergency braking system is electrically connected to the control system module. The laser obstacle avoidance sensor 501 is signal connected to the control system module. The laser obstacle avoidance sensor is electrically connected to the track support.

[0032] Through the above technical solution, the safety protection module 5 is installed on the walking chassis module 1 as a further safety guarantee for the movement of the equipment. Four sets of laser obstacle avoidance sensors 501 are distributed around the steering mechanism 101, covering 360° omnidirectional obstacle avoidance. The installation height is ≥0.5 meters above the ground to avoid interference from ground obstacles. It uses a SICKLMS511 laser radar with a scanning frequency of 75Hz, an angular resolution of 0.33°, a maximum measurement distance of 80 meters, and a laser wavelength of 905nm, conforming to Class 1 laser safety standards. It communicates with the control system module via a wireless port, transmitting obstacle distance, angle, and speed information in real time. This allows operators to remotely adjust the equipment position manually or automatically based on the obstacle locations provided by the safety protection module 5, avoiding collisions. The laser obstacle avoidance sensors 501 detect... When encountering obstacles of abnormal height or shape, the control system module automatically adjusts the height of the track support to avoid collisions. For obstacles that are too high, it directly chooses to avoid them. The control system module receives point cloud data and uses the SLAM algorithm to synchronously locate and build a map, updating the environmental map in real time, identifying obstacle types and movement states. When the distance to an obstacle is ≤2 meters, the control system module issues an audible and visual warning through the display panel to remind the operator. When the distance to an obstacle is ≤1 meter, the control system module immediately triggers the emergency braking system, applying maximum braking force to the hydraulic brake. At the same time, the control system module sends a stop command to the robotic arm loading module 4 to prevent the robotic arm from misoperating. This realizes omnidirectional obstacle avoidance, emergency braking, and adaptive adjustment of the track support, enhancing the equipment's adaptability to complex environments and further solving the problem of high reliance on human labor.

[0033] In operation, the material identification module 3 uses a vision system to identify scattered materials and generate three-dimensional coordinates. The control system then plans the robotic arm's trajectory. After the electromagnetic gripper 402 adsorbs the materials, the device moves to the construction elevator shaft via the walking chassis module 1. The vertical lifting module 2's gears mesh with the elevator's standard section, achieving vertical movement via a motor. Upon reaching the target floor, the direction is adjusted by rotating the chassis 403, and the height is adjusted by the six-degree-of-freedom articulated arm 401. The robotic arm then sorts and stacks the materials in designated areas according to a preset program. The steering mechanism 101 uses a hydraulic steering system with a steering angle of ±45° and a steering radius ≤1.5m. The walking chassis module 1 has obstacle-crossing capabilities and can move freely on complex ground surfaces via its tracked supports. The multispectral imaging function adds infrared and ultraviolet imaging technology, with an infrared wavelength range of 8-14μm and an ultraviolet wavelength range of 200-400nm, used to identify material surface defects and material properties, and uploads the data to the panel through the control system. The torque sensor monitors the grasping force in real time with an accuracy of ±1N·m. The torque sensor monitors whether an object is grasped each time. If the grasping fails more than five times, the control system sends an alarm message to the display panel. This solution can save the investment cost of dedicated lifting equipment by reusing the construction elevator transmission system. The 3D vision recognition system can adapt to the material positioning needs in complex construction site environments, reduce the dependence on manpower for transporting reusable materials in super high-rise construction, and realize the automatic identification and accurate classification and stacking of materials such as scaffolding pipes. The RFID identification system enhances the material identification module 3. Building upon the existing 3D vision sensor scanning as base data and multispectral imaging as an auxiliary function, the RFID system is the primary tool for classifying and processing each material. Electronic tags are pre-embedded at the ends of the materials, storing material type, specifications, and production date information. The RFID reader uses high-frequency reading and writing at 915MHz, with a reading distance of ≥3 meters, and supports the ISO18000-6C protocol. Data transmission: The RFID identification system is electrically connected to the control system module, transmitting material information to the control system module in real time. The 3D vision sensor's wide-range scanning determines the location of the scaffolding pipes, which is then precisely confirmed by the RFID identification system, further ensuring accurate material classification. The control system module integrates the 3D vision scan data with the RFID tag information to generate a complete material identification report, achieving rapid and accurate material identification, further improving construction efficiency, reducing labor costs, and enhancing the transparency and security of material management.Safety protection module 5 is installed on the walking chassis module 1 to provide further safety assurance for equipment movement. Laser obstacle avoidance sensors 501 are distributed around the steering mechanism 101, in four groups, covering 360° omnidirectional obstacle avoidance. The installation height is ≥0.5 meters above the ground to avoid interference from ground obstacles. It uses a SICKLMS511 laser radar with a scanning frequency of 75Hz, angular resolution of 0.33°, a maximum measurement distance of 80 meters, and a laser wavelength of 905nm, conforming to Class 1 laser safety standards. It communicates with the control system module via a wireless port, transmitting obstacle distance, angle, and speed information in real time. This allows operators to remotely adjust the equipment position manually or automatically based on the obstacle locations provided by safety protection module 5, avoiding collisions. The laser obstacle avoidance sensors 501 detect obstacles. When the height or shape is abnormal, the control system module automatically adjusts the height of the track support to avoid collisions. For obstacles that are too high, it directly chooses to avoid them. The control system module receives point cloud data and uses the SLAM algorithm to synchronously locate and build a map to update the environmental map in real time, identify obstacle types and movement status. When the distance to an obstacle is ≤2 meters, the control system module issues an audible and visual warning through the display panel to remind the operator. When the distance to an obstacle is ≤1 meter, the control system module immediately triggers the emergency braking system, and the hydraulic brake applies maximum braking force. At the same time, the control system module sends a stop command to the robotic arm loading module 4 to prevent the robotic arm from operating incorrectly. It realizes omnidirectional obstacle avoidance, emergency braking and adaptive adjustment of the track support, enhances the adaptability of the equipment to complex environments, and further solves the problem of high dependence on human labor.

[0034] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A recyclable material intelligent transportation robot comprising a walking chassis module (1), characterized in that: A vertical lifting module (2) is installed on the top of the walking chassis module (1), a material identification module (3) is installed at the front end of the top of the walking chassis module (1), and a robotic arm loading module (4) is installed in the middle of the top of the walking chassis module (1). The walking chassis module (1) includes a tracked drive wheel (102) and a steering mechanism (101). The track width is 200mm, the track pitch is 100mm, and the rated load is ≥500kg. The vertical lifting module (2) includes a guide rail (201) that matches the standard section of the construction elevator and a gear transmission box (202). The output shaft tooth profile of the gear transmission box (202) meshes with the gear of the construction elevator. The gear transmission box (202) uses 20CrMnTi alloy steel quenched gears with a module of 4.5 and 28 teeth.

2. The smart transport robot of claim 1, wherein: The material identification module (3) uses a 3D vision sensor with a scanning radius covering a range of 5 meters. The 3D vision sensor is Azure Kinect DK based on the ToF principle, with a resolution of 1280×1024, a frame rate of 30fps, and a depth accuracy of ±2mm.

3. The smart transport robot of claim 1, wherein: The robotic arm loading module (4) consists of a six-degree-of-freedom articulated arm (401), an electromagnetic gripper (402), and a rotating chassis (403). The electromagnetic gripper (402) has a rated adsorption force of ≥200kg and is compatible with scaffold tubes with a diameter of 48-60mm. The six-degree-of-freedom articulated arm (401) has a load capacity of ≥100kg and a repeatability of ±0.05mm.

4. The smart transport robot of claim 1, wherein: It also includes a control system module, which is electrically connected to the walking chassis module (1), the vertical lifting module (2), the material identification module (3) and the robotic arm loading module (4) via a wireless port. The control system module includes a microprocessor and a display panel, integrates a PLC controller, sensor interface and human-machine interface, selects Siemens S7-1200 series PLC, has EtherCAT bus interface, and supports Modbus TCP / IP communication protocol.

5. The intelligent transport robot for reusable materials according to claim 1, characterized in that: The walking chassis module (1) also includes a track support, which is a self-lifting track support and is electrically connected to the control system module.

6. The intelligent transport robot for reusable materials according to claim 1, characterized in that: The material identification module (3) also includes multispectral imaging function, adding infrared and ultraviolet imaging technology in addition to 3D vision.

7. The intelligent transport robot for reusable materials according to claim 1, characterized in that: The robotic arm loading module (4) also includes a torque sensor to monitor the grasping force in real time and to monitor whether an object is grasped each time it grasps.

8. The intelligent transport robot for reusable materials according to claim 2, characterized in that: The material identification module (3) also includes an RFID identification system, with an electronic tag pre-embedded at the end of the material. The RFID identification system is compatible with the electronic tag. The RFID identification system is electrically connected to the control system module. The RFID system includes an RFID reader / writer, which uses high-frequency reading and writing, with a working frequency of 915MHz and a reading distance of ≥3 meters.

9. The intelligent transport robot for reusable materials according to claim 1, characterized in that: It also includes a safety protection module (5), which includes a laser obstacle avoidance sensor (501) and an emergency braking system. The laser obstacle avoidance sensor (501) is installed around the steering mechanism (101), and the emergency braking system is integrated into the chassis module (1). The emergency braking system is electrically connected to the control system module, the laser obstacle avoidance sensor (501) is signal connected to the control system module, and the laser obstacle avoidance sensor is electrically connected to the track support.

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