Control system and control method for shuttle vehicle in logistics unmanned vehicle

Abstract

The invention relates to the field of logistics transportation control, in particular to a control system and a control method for a shuttle vehicle in a logistics unmanned vehicle, the control system is provided with the logistics unmanned vehicle and a cage box, the vehicle is provided with a vehicle inner guide rail and a vehicle outer guide rail, the vehicle-mounted shuttle vehicle can slide between the guide rails, and the control system is further provided with a main control system, an environment sensing system, a positioning system, a lifting system, a servo driving system and the like; the control method comprises the steps of unloading and loading, unloading comprises the processes of unlocking, recognition, environment perception and the like, and the control method further comprises the obstacle removing step and related algorithms, efficient loading, unloading and transferring of the cages in the logistics unmanned vehicle are achieved, obstacles can be accurately recognized and avoided, and safety and stability of the transportation process are guaranteed.

Description

Technical Field

[0001] This invention relates to the field of logistics transportation control, and in particular to a control system and control method for a shuttle vehicle inside an unmanned logistics vehicle. Background Technology

[0002] Currently, unmanned last-mile delivery has become a hot topic in the field of logistics automation. Unmanned delivery vehicles, with their advantages of high efficiency, convenience, and low cost, are widely used for goods delivery in communities, industrial parks, office buildings, and other scenarios. Cages, as the main cargo containers in unmanned delivery vehicles, are crucial to the efficiency of the entire unmanned delivery process through loading, unloading, and transfer between the inside and outside of the vehicle. With the continuous development of the logistics industry, the demand for improving cage loading and unloading efficiency and achieving automation is increasing. This not only relates to the speed and cost of logistics delivery but also affects the smooth operation of the entire logistics supply chain. At the same time, the large-scale development of the logistics industry also places higher demands on the versatility and adaptability of cage loading and unloading equipment.

[0003] In existing technologies, there are two main methods for loading and unloading cages on unmanned delivery vehicles. One is manual operation, where delivery personnel manually operate the system to move the cages from inside the vehicle to the outside, or from the outside to the onboard lifting mechanism, and then manually move the cages back inside. This method is common in small logistics stations or scenarios with low automation requirements. It relies on human experience and skills, but its inefficiency becomes apparent when handling large volumes of goods. The other method is semi-automated loading and unloading, which uses simple guide rails or pushing mechanisms on the unmanned delivery vehicle to assist manual loading and unloading. This method reduces the intensity of manual labor to some extent and is used in some medium-sized logistics deliveries. However, its automation level is limited because it still requires human intervention in positioning and pushing operations.

[0004] However, these existing technologies have significant drawbacks. Manual loading and unloading methods are not only labor-intensive and inefficient, but also fail to achieve full automation of the unmanned delivery process, making them unsuitable for large-scale delivery needs. While semi-automated loading and unloading methods can reduce manual labor intensity to some extent, they still require manual intervention in positioning and assisting with pushing, resulting in low automation levels and problems such as insufficient cage positioning accuracy, susceptibility to jamming, and poor loading and unloading stability, making fully automated cage transfer impossible. Furthermore, existing automated loading and unloading equipment is mostly designed for large logistics vehicles, with complex structures, large sizes, and heavy weights, making it unsuitable for the installation space requirements of small unmanned delivery vehicles. Simultaneously, the control logic of such equipment is complex, difficult to debug, and costly, and it cannot be flexibly adapted to different cages, resulting in poor versatility. Summary of the Invention

[0005] This invention solves the problem that the existing cage loading and unloading positioning accuracy is insufficient and cannot achieve fully automatic cage transfer. It proposes a control system and control method for a shuttle car in unmanned logistics vehicles. The main control scheme of automatic loading and unloading of cages in unmanned logistics vehicles is adopted, which realizes the full-process automated loading and unloading of cages in unmanned delivery vehicles, thereby improving efficiency and reducing costs.

[0006] To achieve the above objectives, the following technical solution is proposed: A control system for a shuttle vehicle inside a logistics unmanned vehicle includes the logistics unmanned vehicle and a cage. The logistics unmanned vehicle has separate internal and external guide rails. A vehicle-mounted shuttle is slidably mounted within the internal guide rail. When the external guide rail is aligned with the internal guide rail, the vehicle-mounted shuttle slides within the external guide rail. The vehicle-mounted shuttle has a main control system that is communicatively connected to the logistics unmanned vehicle and electrically connected to an environmental perception system. The vehicle-mounted shuttle has a positioning module, a lifting mechanism, and a servo drive system that are electrically connected to the main control system. The environmental perception system detects whether there are interfering objects in the vehicle-mounted shuttle's travel path. The positioning module locates the position of the vehicle-mounted shuttle on the internal guide rail. The servo drive system drives the operation of the vehicle-mounted shuttle. The lifting mechanism is used to raise and lower the cage placed on the internal or external guide rail.

[0007] By adopting the above technical solutions, the logistics unmanned vehicle is equipped with separate internal and external guide rails, which facilitate the transfer of cages between the vehicle and the external guide rails. The main control system of the vehicle-mounted shuttle is connected to the logistics unmanned vehicle and can receive loading and unloading instructions. The environmental perception system detects objects interfering with the driving path, which can avoid collisions and ensure safe operation. The positioning module positions the vehicle-mounted shuttle on the internal guide rails, enabling the shuttle to move accurately to the target position. The servo drive system drives the vehicle-mounted shuttle to provide power for the transfer. The lifting mechanism raises and lowers the cages, realizing the transfer of cages between the internal and external guide rails. This achieves fully unmanned autonomous loading and unloading of cages in the logistics unmanned vehicle, improving logistics and distribution efficiency, reducing operating costs, and the system has a compact structure that is compatible with small unmanned delivery vehicles.

[0008] The positioning module includes a first infrared photoelectric sensor located on one side of the vehicle-mounted shuttle, and a second and a third infrared photoelectric sensor located on the other side of the vehicle-mounted shuttle. The inner wall of the guide rail on the same side as the first infrared photoelectric sensor is provided with several first reflective stickers, the inner wall of the guide rail on the same side as the second infrared photoelectric sensor is provided with several second reflective stickers, and the inner wall of the guide rail on the same side as the third infrared photoelectric sensor is provided with several third reflective stickers. The first, second, and third infrared photoelectric sensors are electrically connected to the main control system. The unmanned logistics vehicle is equipped with several foot tags for securing cages, and a fourth infrared photoelectric sensor is mounted on each foot tag.

[0009] By adopting the above technical solution, this invention uses cages arranged sequentially from inside to outside the unmanned logistics vehicle, numbered 1, 2, ..., n. Each cage has four corner supports at its bottom, which are secured to foot brackets. A fourth infrared photoelectric sensor is installed on any foot bracket closest to the inside of the unmanned logistics vehicle to identify the cage's position. A first reflective sticker is attached to the cages numbered odd-numbered. Its position is such that when the vehicle-mounted shuttle moves directly beneath the cage numbered odd-numbered, the first infrared photoelectric sensor is aligned with the first reflective sticker. The first reflective sticker and the first infrared photoelectric sensor position the vehicle-mounted shuttle so that it can stop directly beneath the cage numbered odd-numbered. The second reflective sticker is attached to the even-numbered cage. Its position is such that when the vehicle-mounted shuttle moves directly beneath the even-numbered cage, the second infrared photoelectric sensor is aligned with the second reflective sticker. The second reflective sticker and the second infrared photoelectric sensor position the vehicle-mounted shuttle so that it stops directly beneath the even-numbered cage. The third reflective sticker is positioned so that when the vehicle-mounted shuttle moves to the external guide rail and the cage is completely away from the automated logistics vehicle (fixed-point loading / unloading position), the third infrared photoelectric sensor is aligned with the third reflective sticker. The third reflective sticker and the third infrared photoelectric sensor position the vehicle-mounted shuttle so that it stops directly beneath the cage being loaded / unloaded on the external guide rail.

[0010] The environmental perception system includes two IR-CUT sensing cameras and a main control unit. The IR-CUT sensing cameras are electrically connected to the main control unit, and the main control unit is communicatively connected to the main control system.

[0011] By adopting the above technical solution, the two IR-CUT sensing cameras of the environmental perception system work together with the main control unit to identify obstacles on the vehicle-mounted shuttle's travel path. The main control unit communicates with the main control system and can feed back the obstacle situation to the main control system, enabling the system to make a decision on clearing obstacles or continuing operation based on the feedback. This achieves fully unmanned autonomous operation, enhances the system's environmental adaptability and versatility, ensures the safe operation of the shuttle during the transfer of cages, and avoids collisions and interference.

[0012] The servo drive system includes several wheels that are mounted and slidable within the vehicle's guide rails, servo motors, and motor drive modules. The wheels are connected to the output ends of the servo motors, the servo motors are controlled by the motor drive modules, and the motor drive modules are electrically connected to the main control system.

[0013] By adopting the above technical solution, the servo drive system can control the servo motor through the motor drive module under the control of the main control system, thereby driving the wheels to slide and lock in the guide rail inside the vehicle, realizing the operation of the vehicle-mounted shuttle, providing power drive for the vehicle-mounted shuttle, ensuring its smooth movement on the guide rail, and thus realizing the transfer of cages.

[0014] The lifting mechanism uses a scissor lift structure, and the power drive of the scissor lift structure is an electric cylinder.

[0015] By adopting the above technical solutions, the lifting mechanism using a scissor lift structure and an electric cylinder as the power drive can realize the lifting and lowering of cages and boxes, which can be adapted to cages and boxes of different sizes and weights. This helps to realize the automated and precise transfer of cages and boxes, meet the loading and unloading needs of unmanned logistics vehicles, improve logistics and distribution efficiency, and reduce operating costs.

[0016] A control method for a shuttle vehicle inside a logistics unmanned vehicle, employing the aforementioned control system for a shuttle vehicle inside a logistics unmanned vehicle, includes an unloading step and a loading step, wherein the unloading step specifically includes: S1, when the main control system receives the unloading instruction from the unmanned logistics vehicle, the vehicle-mounted shuttle control locking module is released to release the unmanned logistics vehicle from fixing the cage and the unmanned logistics vehicle from fixing the vehicle-mounted shuttle. S2, the main control system identifies the number of cages inside the unmanned logistics vehicle; S3, the main control system notifies the environmental perception system to perform environmental perception and sends the current status to the environmental perception system; S4, the environmental perception system identifies obstacles on the cage transfer path and determines whether there are obstacles that interfere with the movement of the shuttle. If so, it performs the obstacle clearing step; otherwise, it proceeds to S5. S5, the main control system controls the vehicle-mounted shuttle to move directly under the cage, lifts the cage, and transfers it to the external guide rail; S6, determine whether there is a cage inside the unmanned logistics vehicle. If yes, the main control system controls the vehicle shuttle to return to the unmanned logistics vehicle and executes S3; otherwise, after unloading is completed, the vehicle shuttle returns to the origin and is locked by the locking module. The loading step is performed in reverse order of the unloading step.

[0017] By adopting the above technical solutions, fully automated loading and unloading operations of the shuttle car in the unmanned logistics vehicle have been realized. It can automatically complete the unloading and loading process according to instructions, identify obstacles through the environmental perception system and clear them, ensuring the safe operation of the shuttle car. It can also accurately locate the position of the shuttle car and the cage, and transfer the cage to the designated location, realizing fully unmanned autonomous operation, improving logistics and distribution efficiency, reducing labor costs, and adapting to the installation and use needs of cages of different sizes and weights as well as various small unmanned delivery vehicles.

[0018] The obstacle removal process includes the following steps: S41, the environmental perception system notifies the main control system that there is interference; S42, the vehicle-mounted shuttle stops operating; S43, the main control system notifies that there is an obstacle on the track of the unmanned logistics vehicle; S44, the logistics unmanned vehicle calls for obstacle removal service, waits for the obstacle to be removed, and returns to S4.

[0019] By adopting the above technical solution, when the environmental perception system detects an obstacle in the cage-carrying transfer path, it can promptly notify the main control system to stop the onboard shuttle and avoid collision. The main control system notifies the unmanned logistics vehicle of an obstacle on its track, allowing the unmanned logistics vehicle to call for obstacle removal service, ensuring the smooth progress of subsequent transfer processes, ensuring the safety and efficiency of the entire cage-carrying loading and unloading process, and improving the reliability and stability of the unmanned logistics vehicle shuttle control system.

[0020] The steps by which the S5 main control system controls the vehicle-mounted shuttle to move directly under the cage are as follows: S51, the main control system controls the vehicle-mounted shuttle to move to the outermost cage of the logistics unmanned vehicle until the first infrared photoelectric sensor or the first reflective sticker or the second reflective sticker of the first infrared photoelectric sensor moves to the outermost cage and obtains a positioning signal, then the main control system controls the vehicle-mounted shuttle to stop moving. S52, the main control system controls the lifting mechanism to lift the cage until it is lifted to the designated working height, at which point the cage separates from the guide rail inside the vehicle; The steps of S5 in transferring the cage to the external guide rail are as follows: S53, obtain the distance s from the cargo cage to the fixed loading / unloading position on the guide rail inside the vehicle and obtain the real-time speed v of the onboard shuttle via the servo motor. k ; S54, set the maximum acceleration 'a' and the maximum speed of the onboard shuttle, and calculate the time 't' of uniform motion under ideal conditions. 匀 ; S55, the vehicle-mounted shuttle first moves to its maximum actual speed based on the maximum acceleration 'a', and then moves at a constant speed at the maximum actual speed for a duration of 't'. 匀 Finally, it decelerates with maximum acceleration a until it reaches the set speed v. 低 ; S56, the vehicle-mounted shuttle travels at a speed of v 低 The motion continues at a constant speed until the third infrared photoelectric sensor detects the third reflective sticker, at which point the motion stops.

[0021] The environmental perception system identifies obstacles along the cage transport path as follows: Sa: Turn on the camera and correct camera distortion; Sb maps pixels to real-world 3D dimensions; Sc, the main control unit analyzes the objects on the travel path of the vehicle-mounted shuttle 3; Sd determines whether there are obstacles. If so, it sends the object's 3D dimensions to the main control system; otherwise, it outputs "no obstacles" to the main control system.

[0022] By adopting the above technical solutions, obstacles on the cage-box transfer path can be accurately identified, providing a basis for subsequent obstacle removal or transfer operations, ensuring that the vehicle-mounted shuttle is not interfered with during operation, guaranteeing the smooth transfer of cage-boxes, and further improving the safety and reliability of the shuttle control system in the unmanned logistics vehicle.

[0023] The beneficial effects of this invention are: 1. Achieve fully unmanned autonomous operation: Through the collaborative work of the environmental perception system and the main control system, the system can autonomously identify and model the cages inside the unmanned vehicle, guiding the shuttle to move precisely under the cages without human intervention, thus solving the problem of automated loading and unloading in the "last mile" of logistics and distribution. 2. Highly integrated and lightweight structure: The main control, drive, lifting and sensing units are highly integrated into the compact shuttle body, reducing the space occupied and system weight, and improving the internal space utilization and range of the small unmanned delivery vehicle. 3. The architecture is clear, and the response is precise and efficient. The control system adopts a modular design, decoupling environmental perception from motion control, ensuring that the system has extremely high response speed and control accuracy when handling complex transfer tasks. 4. It has strong environmental adaptability and versatility. Relying on the flexible recognition capability of the environmental perception system, it can adapt to standard specification cages and can also automatically be compatible with vehicles of different sizes or with slight displacement. The standardized interface design of the communication module can be integrated into various models of unmanned delivery vehicle platforms. Attached Figure Description

[0024] Figure 1 This is a diagram showing the hardware configuration of the system before unloading according to the present invention.

[0025] Figure 2 This is a diagram showing the configuration of the system hardware after unloading.

[0026] Figure 3 The structural layout of the vehicle-mounted shuttle of the present invention is shown.

[0027] Figure 4 This is a schematic diagram showing the relative positions of the vehicle-mounted shuttle and the in-vehicle guide rails of the present invention.

[0028] Figure 5 This is a flowchart of the unloading steps of the present invention.

[0029] Figure 6 This is a flowchart of the loading steps of the present invention.

[0030] Figure 7 This is a schematic diagram of the velocity change curve of the present invention.

[0031] Figure 8 This is a flowchart of the obstacle recognition steps of the present invention.

[0032] Among them: 1. Logistics unmanned vehicle; 2. In-vehicle guide rail; 3. Vehicle-mounted shuttle; 4. Cage; 5. Out-of-vehicle guide rail; 31. First infrared photoelectric sensor; 32. Wheel; 33. Second infrared photoelectric sensor; 34. Lifting mechanism; 35. Second reflective sticker; 36. First reflective sticker; 37. Third infrared photoelectric sensor; 38. Third reflective sticker. Detailed Implementation

[0033] The technical solutions in the embodiments of the present invention will be further described in detail below with reference to the accompanying drawings. The described embodiments are only possible technical implementations of the present invention, but are not limited thereto. Other embodiments obtained by those skilled in the art in conjunction with the embodiments of the present invention without creative effort are also within the protection scope of the present invention. Example

[0034] This embodiment proposes a control system for a shuttle vehicle inside an unmanned logistics vehicle, referring to... Figure 1 The system includes a logistics unmanned vehicle 1 and a cage 4. The logistics unmanned vehicle 1 is equipped with a separate internal guide rail 2 and an external guide rail 5. A vehicle-mounted shuttle 3 is slidably mounted inside the internal guide rail 2. When the external guide rail 5 is aligned with the internal guide rail 2, the vehicle-mounted shuttle 3 is locked and slidably mounted inside the external guide rail 5. The vehicle-mounted shuttle 3 is equipped with a main control system, which is communicatively connected to the logistics unmanned vehicle 1. The main control system is electrically connected to an environmental perception system. (Reference) Figure 4The vehicle-mounted shuttle 3 is equipped with a positioning module, a lifting mechanism 34, and a servo drive system that are electrically connected to the main control system. The environmental perception system detects whether there are interfering objects in the driving path of the vehicle-mounted shuttle 3. The positioning module positions the vehicle-mounted shuttle 3 on the inner guide rail 2. The servo drive system drives the operation of the vehicle-mounted shuttle 3. The lifting mechanism 34 is used to raise and lower the cage 4 placed on the inner guide rail 2 or the outer guide rail 5.

[0035] The unmanned logistics vehicle features separate internal and external guide rails, facilitating the transfer of cages between the vehicle and the external rails. The main control system on the vehicle-mounted shuttle communicates with the unmanned logistics vehicle and receives loading and unloading commands. An environmental perception system detects interfering objects along the travel path, preventing collisions and ensuring safe operation. A positioning module locates the vehicle-mounted shuttle on the internal guide rails, enabling precise movement to the target location. A servo drive system powers the vehicle-mounted shuttle, providing power for the transfer. A lifting mechanism raises and lowers the cages, transferring them between the internal and external guide rails. This achieves fully automated, unmanned loading and unloading of cages, improving logistics efficiency, reducing operating costs, and the system's compact structure makes it compatible with small unmanned delivery vehicles.

[0036] refer to Figure 3 The positioning module includes a first infrared photoelectric sensor 31 disposed on one side of the vehicle-mounted shuttle 3, and a second infrared photoelectric sensor 33 and a third infrared photoelectric sensor 37 disposed on the other side of the vehicle-mounted shuttle 3. The inner wall of the guide rail 2 on the same side as the first infrared photoelectric sensor 31 is provided with a plurality of first reflective stickers 36, and the inner wall of the guide rail 2 on the same side as the second infrared photoelectric sensor 33 is provided with a plurality of second reflective stickers 35. (Reference) Figure 2 The inner wall of the external guide rail 5 on the same side as the third infrared photoelectric sensor 37 is provided with several third reflective stickers 38. The first infrared photoelectric sensor 31, the second infrared photoelectric sensor 33 and the third infrared photoelectric sensor 37 are electrically connected to the main control system. The logistics unmanned vehicle 1 is provided with several foot codes for locking the cage box 4. The foot codes are provided with a fourth infrared photoelectric sensor 11.

[0037] The cages 4 set up inside and outside the unmanned logistics vehicle 1 are numbered sequentially as 1, 2, ..., n. Each cage 4 has four ankles at its bottom corners, which are secured to foot brackets. A fourth infrared photoelectric sensor 11 is installed on any foot bracket closest to the inside of the unmanned logistics vehicle 1 to identify the position of the cage 4. A first reflective sticker 36 is attached to the cages 4 numbered odd. Its position is set so that when the vehicle-mounted shuttle 3 moves directly under the cage 4 numbered odd, the first infrared photoelectric sensor 31 is facing the first reflective sticker 36. The vehicle-mounted shuttle 3 is positioned by the first reflective sticker 36 and the first infrared photoelectric sensor 31 so that it can stop directly under the cage 4 numbered odd. The second reflective sticker 35 is attached to the even-numbered cage 4. Its position is such that when the vehicle-mounted shuttle 3 moves directly beneath the even-numbered cage 4, the second infrared photoelectric sensor 33 is directly opposite the second reflective sticker 35. The second reflective sticker 35 and the second infrared photoelectric sensor 33 position the vehicle-mounted shuttle 3 so that it stops directly beneath the even-numbered cage 4. The third reflective sticker 38 is positioned so that when the vehicle-mounted shuttle 3 moves to the external guide rail 5 and the cage 4 is completely away from the unmanned logistics vehicle 1 (fixed-point loading / unloading position), the third infrared photoelectric sensor 37 is directly opposite the third reflective sticker 38. The third reflective sticker 38 and the third infrared photoelectric sensor 37 position the vehicle-mounted shuttle 3 so that it stops directly beneath the cage 4 being loaded / unloaded on the external guide rail 5.

[0038] The environmental perception system includes two IR-CUT sensing cameras and a main control unit. The IR-CUT sensing cameras are electrically connected to the main control unit, and the main control unit is communicatively connected to the main control system.

[0039] Two IR-CUT sensing cameras are installed in the opposite top corner of the cargo compartment of the unmanned logistics vehicle 1. The two IR-CUT sensing cameras of the environmental perception system work together with the main control unit to identify obstacles in the driving path of the onboard shuttle. The main control unit communicates with the main control system and can feed back the obstacle situation to the main control system, so that the system can make a decision on clearing obstacles or continuing to operate based on the feedback, realizing fully unmanned autonomous operation, enhancing the system's environmental adaptability and versatility, ensuring the safe operation of the shuttle during the transfer of cages and avoiding collisions and interference.

[0040] When there are only two cages per vehicle, the environmental perception system is designed as follows: Empty wagons transferring full-load cages inward: 00 (empty wagon) → 10 (single cage) → 11 (double cage) (two full cages are transferred into the wagon). Full wagons transferring full-load cages outward: 11 (double cage) → 10 (single cage) → 00 (empty wagon) (two full cages are transferred out of the wagon). Complete status flow: 00 (empty wagon) → 10 (single cage) → 11 (full wagon) → 10 (single cage) → 00 (empty wagon). Environmental perception system recognition area: It can recognize the areas on both sides and in the middle of the shuttle rail inside the unmanned vehicle, detect obstacles, and send signals to the shuttle.

[0041] The servo drive system includes several wheels 32 that are mounted and slidable within the vehicle guide rail 2, a servo motor, and a motor drive module. The wheels 32 are connected to the output end of the servo motor, the servo motor is controlled by the motor drive module, and the motor drive module is electrically connected to the main control system.

[0042] This application enables the servo drive system to control the servo motor using the motor drive module under the control of the main control system, thereby driving the wheels to slide and lock within the guide rail inside the vehicle, realizing the operation of the vehicle-mounted shuttle, providing power drive for the vehicle-mounted shuttle, ensuring its smooth movement on the guide rail, and thus realizing the transfer of cages.

[0043] The lifting mechanism 34 uses a scissor lift structure, and the power drive of the scissor lift structure is an electric cylinder.

[0044] This application uses a scissor lift structure and an electric cylinder as the power-driven lifting mechanism to achieve the lifting and lowering of cages. It can adapt to cages of different sizes and weights, which helps to realize the automated and precise transfer of cages, meet the loading and unloading needs of unmanned logistics vehicles, improve logistics and distribution efficiency and reduce operating costs.

[0045] Example 2: This embodiment proposes a control method for a shuttle vehicle inside an unmanned logistics vehicle. It employs the control system for a shuttle vehicle inside an unmanned logistics vehicle described in Embodiment 1, including unloading and loading steps. (Refer to...) Figure 5 The unloading steps specifically include: S1, when the main control system receives the unloading instruction from the logistics unmanned vehicle 1, the vehicle-mounted shuttle 4 controls the locking module to release, so as to release the logistics unmanned vehicle 1 from fixing the cage 4 and the logistics unmanned vehicle 1 from fixing the vehicle-mounted shuttle 3. S2, the main control system identifies the number of cages inside the unmanned logistics vehicle 1; S3, the main control system notifies the environmental perception system to perform environmental perception and sends the current status to the environmental perception system; S4, the environmental perception system identifies obstacles on the transfer path of cage 4 and determines whether there are obstacles that interfere with the movement of the shuttle. If so, it performs the obstacle clearing step; otherwise, it proceeds to S5. S5, the main control system controls the vehicle-mounted shuttle 3 to move directly under the cage 4, lifts the cage 4, and transfers it to the external guide rail 5; S6, determine whether there is a cage 4 inside the unmanned logistics vehicle 1. If yes, the main control system controls the vehicle shuttle 3 to return to the unmanned logistics vehicle 1 and executes S3. If no, after unloading is completed, the vehicle shuttle 3 returns to the origin and is locked by the locking module. refer to Figure 6 The loading step is performed in reverse order of the unloading step.

[0046] This application realizes fully automated loading and unloading operations of shuttle vehicles in unmanned logistics vehicles. It can automatically complete the unloading and loading process according to instructions, identify obstacles through an environmental perception system and clear them, ensuring the safe operation of the shuttle vehicle. It can also accurately locate the shuttle vehicle and the cage, and transfer the cage to the designated location, realizing fully unmanned autonomous operation, improving logistics and distribution efficiency, reducing labor costs, and adapting to the installation and use needs of cages of different sizes and weights as well as various small unmanned delivery vehicles.

[0047] The obstacle removal process includes the following steps: S41, the environmental perception system notifies the main control system that there is interference; S42, the vehicle-mounted shuttle 3 stops operating; S43, the main control system notifies that there is an obstacle on the track of logistics unmanned vehicle 1; S44, the logistics unmanned vehicle 1 calls the obstacle clearing service, waits for the obstacle to be cleared, and returns to S4.

[0048] When the environmental perception system detects an obstacle in the cage-carrying transport path, it can promptly notify the main control system to stop the onboard shuttle and avoid a collision. The main control system then notifies the unmanned logistics vehicle of an obstacle on its track, prompting the unmanned vehicle to call for obstacle removal services. This ensures the smooth progress of subsequent transport processes, guarantees the safety and efficiency of the entire cage-carrying loading and unloading process, and improves the reliability and stability of the unmanned logistics vehicle shuttle control system.

[0049] The steps by which the S5 main control system controls the vehicle-mounted shuttle 3 to move directly below the cage 4 are as follows: S51, the main control system controls the vehicle-mounted shuttle 3 to move to the outermost cage 4 of the logistics unmanned vehicle 1 until the first infrared photoelectric sensor 31 or the first reflective sticker 36 or the second reflective sticker 35 of the first infrared photoelectric sensor 31 moves to the outermost cage 4 and obtains a positioning signal, then the main control system controls the vehicle-mounted shuttle 3 to stop moving. S52, the main control system controls the lifting mechanism 34 to lift the cage 4 until it is lifted to the specified working height, at which point the cage 4 is separated from the guide rail 2 inside the vehicle. The steps of S5 in transferring the cage 4 to the external guide rail 5 are as follows: S53, obtain the distance s from the unloading cage 4 to the fixed loading / unloading position of the guide rail 2 inside the vehicle, and obtain the real-time speed v of the on-board shuttle 3 through the servo motor. k ; S54, set the maximum acceleration 'a' and the maximum speed of the onboard shuttle, and calculate the time 't' of uniform motion under ideal conditions. 匀 ; Ideally, the acceleration phase displacement is the displacement of the vehicle-mounted shuttle as it accelerates uniformly from 0 to its maximum speed with maximum acceleration *a*, and the deceleration phase displacement is the displacement of the vehicle-mounted shuttle as it decelerates uniformly from its maximum speed with maximum acceleration *a* to 0. The distance *s* minus the acceleration and deceleration phase displacements, divided by the maximum speed, yields the ideal uniform motion time *t*. 匀 .

[0050] S55, the vehicle-mounted shuttle first moves to its maximum actual speed based on the maximum acceleration 'a', and then moves at a constant speed at the maximum actual speed for a duration of 't'. 匀 Finally, it decelerates with maximum acceleration a until it reaches the set speed v. 低 ; S56, the vehicle-mounted shuttle travels at a speed of v 低 The motion continues at a constant speed until the third infrared photoelectric sensor detects the third reflective sticker, at which point the motion stops.

[0051] refer to Figure 7 Where: at time t0, the onboard shuttle starts; at time t1, the onboard shuttle reaches its maximum speed and moves at a constant speed; at time t2, the onboard shuttle begins to decelerate after displacement calculation; t 匀 =t2-t1; t3 is the low-speed operation before approaching the target point, with a speed of v. 低 At time t4, the third infrared photoelectric sensor detects the third reflector, triggering a stop signal and initiating braking; at time t5, the motion stops. This application integrates the speed based on real-time feedback, with an integration time of Δt, to prepare acceleration and deceleration strategies in advance. Based on actual conditions, the maximum allowable acceleration of the shuttle can be calculated as a. Here, we divide the entire movement distance into three displacement segments.

[0052] s1: Displacement used for shuttle acceleration; s2: Displacement of the shuttle at a constant speed; s3: Displacement used for shuttle deceleration; s4: Used for the residual displacement caused by actual error; The total distance s = s1 + s2 + s3 + s4; Displacement s1 during acceleration phase: dynamically determined based on the total actual displacement length during acceleration phase; Displacement s2 during the uniform velocity phase: Excluding additions and subtractions, the remaining displacements are considered as uniform motion. Let s4 = 0, s 2= s-s1-s3; Displacement s3 during deceleration phase: dynamically determined based on the total actual displacement length during deceleration phase; Error elimination displacement s4: Due to the error caused by the motion, the vehicle shuttle needs to run slowly during the remaining s4 to ensure that it can stop immediately when the vehicle shuttle triggers the fourth infrared photoelectric sensor.

[0053] The formula for calculating displacement is: s k =s k−1 + v k ∙∆t, where k represents the current time, k-1 represents the previous time with a time interval of ∆t, and s k s represents the total displacement at the current moment. k−1 This represents the total displacement at the previous moment.

[0054] The software in this application will control the shuttle car according to the strategy of slow acceleration-constant speed-slow deceleration-stop. It can calibrate the error caused by speed integration during the operation of the shuttle car, so that the shuttle car can make acceleration and deceleration strategies in advance according to its own position, ensuring that the speed meets the set requirements when it reaches the designated position, thereby ensuring the accurate positioning of the shuttle car and improving the accuracy and stability of cage transfer.

[0055] refer to Figure 8 The process by which the environmental perception system identifies obstacles along the transfer path of cage 4 is as follows: Sa: Turn on the camera and correct camera distortion; Sb maps pixels to real-world 3D dimensions; Sc, the main control unit analyzes the objects on the travel path of the vehicle-mounted shuttle 3; Sd determines whether there are obstacles. If so, it sends the object's 3D dimensions to the main control system; otherwise, it outputs "no obstacles" to the main control system.

[0056] This application can accurately identify obstacles on the cage-and-box transfer path, providing a basis for subsequent obstacle removal or transfer operations, ensuring uninterrupted operation of the vehicle-mounted shuttle, guaranteeing the smooth transfer of cages and boxes, and further improving the safety and reliability of the shuttle control system within the unmanned logistics vehicle. The specific implementation of this step includes pre-processing and perception / detection procedures.

[0057] Preprocessing: Read resource directory and camera selection (camera A, camera B): Read JSON configuration file, select camera-profile (A / B), parse: device, resource_root, calibration parameters (chessboard size / grid length), and form the dedicated resource directory for this camera: cameras / A|B.

[0058] Distortion calibration: Automatically acquire chessboard frames (corner detection + subpixel optimization), calculate intrinsic and extrinsic parameters after the number of effective images reaches the standard, calculate and print reprojection error (for quality inspection), and save distortion parameters.

[0059] Plane mapping calibration: Load the latest distortion calibration file, detect corner points after distortion removal of the checkerboard image, use findHomography to calculate the homography matrix H, perform mapping error verification (mean / max mm), and save plane_mapping.npz.

[0060] A linear compensation technique is employed to compensate for the limitation of planar calibration in terms of accuracy, achieved only in planar measurements, by calibrating at different depth locations. In the absence of depth information, the mapping link logic at different depths is calculated.

[0061] Collect and detect the ROI: four mouse points form a quadrilateral (multiple regions are possible), and save the files as detection_roi.json, detection_roi_points.jpg, and detection_roi_mask.png.

[0062] Collect background region ROI: four mouse points form a quadrilateral (multiple regions are possible), and save background_roi.json, background_roi_points.jpg, and background_roi_mask.png.

[0063] Create a background template for the background ROI area: continuously sample multiple frames (median fusion) in the background ROI area to generate a stable background grayscale template (it will automatically resample if the background ROI changes), and save bbackground_template.npz and background_template_preview.jpg.

[0064] Asset integrity verification: Ensure that plane_mapping, detection_roi, background_roi, and background_template are complete.

[0065] Sensing and detection process: Initialization: Load the camera profile assets (calibration, mapping, ROI, background template), initialize the camera (distortion removal can be enabled), and enter the main loop after passing asset integrity verification.

[0066] Get the current frame: OpenCV pulls a single frame image, continuously acquires it in a loop to form a video stream, and if frame acquisition fails, the frame is treated as unsafe.

[0067] Preprocessing: grayscale conversion, illumination normalization using double Gaussian difference, Otsu binarization, AND operation with "background-foreground mask" (only retaining relative background changes), morphological close / open + bridge (connectivity breakage, noise reduction).

[0068] Background and foreground masking: Alignment of current grayscale with background template using brightness delta compensation, enhancement of dark / bright areas + background difference fusion, adaptive thresholding, dark target compensation + gradient residual branching, shadow suppression, temporal mask voting (historical frame hits), and IR-CUT switching protection (cooling during switching and temporary suppression of false detections).

[0069] Candidate contour extraction and geometric filtering: Extract outer contour, filter conditions: ROI overlap area / ratio, area upper and lower limits, boundary edge filtering, minimum short side, aspect ratio, extent / solidity, and merging of neighboring contours.

[0070] Secondary discrimination + physical size measurement: Secondary confidence filtering (brightness contrast + gradient + foreground coverage weighting), projecting contour pixels onto plane coordinates (mm), calculating the physical length and width of obstacles (mm), and classifying them into levels (small / medium / large) according to size thresholds.

[0071] Temporal stability maintenance: cross-frame target matching (nearest neighbor), size / location EMA smoothing, median smoothing window, and hierarchical hysteresis (to prevent back-and-forth jumps around the threshold).

[0072] Safety voting confirmation: When the original result is unsafe, the streak is accumulated; two consecutive unsafe frames are required to confirm that the output is unsafe; if any safe frame appears, the streak is immediately cleared to restore safety.

[0073] Output decision and feedback: The output results include whether it is safe, obstacle level, obstacle size (mm), obstacle list, generated summary (usually the highest risk target), local visualization overlay of ROI / status, and encoding and sending CAN feedback after receiving a valid control command.

[0074] Example 3: This embodiment, based on embodiment 1, integrates an environmental perception system and a camera into the vehicle-mounted shuttle 3. Algorithms are used to perceive and locate the surrounding environment, making the system more integrated. In this embodiment, the vehicle-mounted shuttle 3 interacts with the unmanned logistics vehicle via wireless communication and can also serve as a method for the vehicle-mounted shuttle 3 to land and locate the cage 4. After the vehicle-mounted shuttle 3 leaves the unmanned logistics vehicle 1, it can connect to the unmanned logistics vehicle 1 via Bluetooth and perform path planning and recognition through visual algorithms.

[0075] In this embodiment, the lidar can also be integrated into the vehicle-mounted shuttle 3, and the surrounding environment can be perceived and located through algorithms, making the system more integrated.

[0076] Example 4: This embodiment is based on Embodiment 1, with only a modification to the in-vehicle track positioning method. A slot is cut into the guide rail, and a reflective sticker for an infrared laser photoelectric switch sensor with mirror reflection is attached. The reflective sticker is placed at the cage placement position, and the infrared photoelectric sensor is placed on both sides of the shuttle car, facing the track. When the shuttle car moves to the reflective sticker and triggers the infrared laser photoelectric switch sensor, the shuttle car stops moving, and the cage car descends. The remaining loading and unloading steps are the same as in Embodiment 1.

Claims

1. A control system for a shuttle vehicle inside a logistics unmanned vehicle, comprising a logistics unmanned vehicle (1) and several cages (4), characterized in that, The unmanned logistics vehicle (1) is equipped with a pair of separate internal guide rails (2) and a pair of external guide rails (5). A vehicle-mounted shuttle (3) is slidably mounted within the internal guide rails (2). When the external guide rails (5) are aligned with the internal guide rails (2), the vehicle-mounted shuttle (3) slides within the external guide rails (5). The vehicle-mounted shuttle (3) is equipped with a main control system, which is communicatively connected to the unmanned logistics vehicle (1). The main control system is electrically connected to an environmental perception system. The vehicle-mounted shuttle (3) is equipped with a positioning module, a lifting mechanism (34) and a servo drive system that are electrically connected to the main control system. The environmental perception system detects whether there are interfering objects in the driving path of the vehicle-mounted shuttle (3). The positioning module positions the vehicle-mounted shuttle (3) on the in-vehicle guide rail (2). The servo drive system drives the vehicle-mounted shuttle (3) to run. The lifting mechanism (34) is used to lift and lower the cage (4) placed on the in-vehicle guide rail (2) or the out-of-vehicle guide rail (5).

2. The control system for a shuttle vehicle inside a logistics unmanned vehicle according to claim 1, characterized in that, The positioning module includes a first infrared photoelectric sensor (31) set on one side of the vehicle-mounted shuttle (3) and a second infrared photoelectric sensor (33) and a third infrared photoelectric sensor (37) set on the other side of the vehicle-mounted shuttle (3). The inner wall of the guide rail (2) on the same side as the first infrared photoelectric sensor (31) is provided with a number of first reflective stickers (36). The inner wall of the guide rail (2) on the same side as the second infrared photoelectric sensor (33) is provided with a number of second reflective stickers (35). The inner wall of the guide rail (5) on the same side as the third infrared photoelectric sensor (37) is provided with a number of third reflective stickers (38). The first infrared photoelectric sensor (31), the second infrared photoelectric sensor (33) and the third infrared photoelectric sensor (37) are electrically connected to the main control system. The logistics unmanned vehicle (1) is provided with a number of foot codes for locking the cage (4). The foot codes are provided with a fourth infrared photoelectric sensor (11).

3. A control system for a shuttle vehicle inside a logistics unmanned vehicle according to claim 2, characterized in that, The environmental perception system includes two IR-CUT sensing cameras and a main control unit. The IR-CUT sensing cameras are electrically connected to the main control unit, and the main control unit is communicatively connected to the main control system.

4. A control system for a shuttle vehicle inside a logistics unmanned vehicle according to claim 2, characterized in that, The servo drive system includes several wheels (32) that are mounted and slidable in the vehicle guide rail (2), a servo motor and a motor drive module. The wheels (32) are connected to the output end of the servo motor. The servo motor is controlled by the motor drive module and the motor drive module is electrically connected to the main control system.

5. A control system for a shuttle vehicle inside an unmanned logistics vehicle according to any one of claims 1-4, characterized in that, The lifting mechanism (34) uses a scissor lift structure, and the power drive of the scissor lift structure is an electric cylinder.

6. A control method for a shuttle vehicle inside an unmanned logistics vehicle, employing the control system for a shuttle vehicle inside an unmanned logistics vehicle as described in any one of claims 2-4, characterized in that, It includes unloading and loading steps, and the unloading step specifically includes: S1, when the main control system receives the unloading instruction issued by the logistics unmanned vehicle (1), the vehicle-mounted shuttle (4) controls the locking module to release, so as to release the logistics unmanned vehicle (1) from the cage (4) and the logistics unmanned vehicle (1) from the vehicle-mounted shuttle (3). S2, the main control system identifies the number of cages inside the unmanned logistics vehicle (1); S3, the main control system notifies the environmental perception system to perform environmental perception and sends the current status to the environmental perception system; S4, the environmental perception system identifies obstacles on the transfer path of the cage (4) and determines whether there are obstacles that interfere with the movement of the shuttle. If yes, it performs the obstacle clearing step; otherwise, it performs S5. S5, the main control system controls the vehicle-mounted shuttle (3) to move directly under the cage (4), lifts the cage (4), and transfers it to the external guide rail (5). S6, determine whether there is a cage (4) inside the logistics unmanned vehicle (1). If yes, the main control system controls the vehicle shuttle (3) to return to the logistics unmanned vehicle (1) and executes S3; if no, after unloading is completed, the vehicle shuttle (3) returns to the origin and locks the vehicle shuttle (3) through the locking module. The loading step is performed in reverse order of the unloading step.

7. The control method for a shuttle vehicle inside a logistics unmanned vehicle according to claim 6, characterized in that, The obstacle removal process includes the following steps: S41, the environmental perception system notifies the main control system that there is interference; S42, the vehicle-mounted shuttle (3) stops operating; S43, the main control system notifies the logistics unmanned vehicle (1) that there is an obstacle on the track; S44, the logistics unmanned vehicle (1) calls the obstacle clearing service, waits for the obstacle to be cleared, and returns to S4.

8. The control method for a shuttle vehicle inside a logistics unmanned vehicle according to claim 6, characterized in that, The steps by which the S5 main control system controls the vehicle-mounted shuttle (3) to move directly below the cage (4) are as follows: S51, the main control system controls the vehicle-mounted shuttle (3) to move to the outermost cage (4) of the logistics unmanned vehicle (1) until the first infrared photoelectric sensor (31) or the first reflective sticker (36) or the second reflective sticker (35) of the outermost cage (4) obtains a positioning signal, and the main control system controls the vehicle-mounted shuttle (3) to stop moving. S52, the main control system controls the lifting mechanism (34) to lift the cage (4) until it is lifted to the specified working height. At this time, the cage (4) is separated from the guide rail (2) inside the vehicle. The steps of S5 in transferring the cage (4) to the external guide rail (5) are as follows: S53, obtain the distance s from the unloading cage (4) to the fixed loading / unloading position of the guide rail (2) inside the vehicle and obtain the real-time speed v of the on-board shuttle (3) through the servo motor. k ; S54, set the maximum acceleration 'a' and the maximum speed of the onboard shuttle, and calculate the time 't' of uniform motion under ideal conditions. 匀 ; S55, the vehicle-mounted shuttle first moves to its maximum actual speed based on the maximum acceleration 'a', and then moves at a constant speed at the maximum actual speed for a duration of 't'. 匀 Finally, it decelerates with maximum acceleration a until it reaches the set speed v. 低 ; S56, the vehicle-mounted shuttle travels at a speed of v 低 The motion continues at a constant speed until the third infrared photoelectric sensor detects the third reflective sticker, at which point the motion stops.

9. A control method for a shuttle vehicle inside a logistics unmanned vehicle according to claim 6, characterized in that, The process by which the environmental perception system identifies obstacles along the transfer path of the cage (4) is as follows: Sa: Turn on the camera and correct camera distortion; Sb maps pixels to real-world 3D dimensions; Sc, the main control unit analyzes the objects on the travel path of the vehicle-mounted shuttle 3; Sd determines whether there are obstacles. If so, it sends the object's 3D dimensions to the main control system; otherwise, it outputs "no obstacles" to the main control system.

Images