261 results about "Logistics automation" patented technology

The invention relates to the technical field of intelligent warehousing and logistics automation, in particular to a forklift dynamic path planning method based on deep reinforcement learning, and the method comprises the steps: deploying multi-view vision, geomagnetism and other multi-source sensors, achieving data calibration and fusion through employing an insect compound eye-imitating vision model, and constructing a high-dimensional state space vector; heuristic models such as migrant bird navigation and biological stress response are adopted, deep reinforcement learning is combined, decision instructions are generated from the three aspects of path planning, dynamic obstacle avoidance and energy efficiency management, actions are executed through a control system, and deviation is fed back; a reward function is used for evaluating the decision effect, rewards are formed by weighting path efficiency, obstacle avoidance success and energy consumption penalty, the weight can be updated in a self-adaptive mode, and therefore the deep reinforcement learning model is optimized. According to the method, the accuracy, safety and efficiency of forklift path planning are effectively improved, the method can adapt to complex dynamic environments, and the requirements of intelligent logistics and industrial automation for forklift intelligent operation are met.

The invention discloses an automatic loading method for a truck based on deep learning and stereoscopic vision. The automatic loading method comprises the following steps that S1, goods location pixel coordinates are obtained and converted into an AGV forklift coordinate system; s2, a driving track is calculated, a front station is generated, and the AGV forklift is guided to move; s3, collecting point cloud data, denoising, extracting features by adopting an improved Transform point cloud registration network, calculating three-dimensional feature points of goods locations and trays, and converting coordinates; s4, calculating a rotation adjustment amount and a displacement compensation parameter, optimizing a driving track and correcting a butt joint deviation; s5, adopting a self-adaptive local attention weighting strategy to match the target goods allocation with the tray slot, and correcting the pose; s6, the cargo stacking posture is adjusted, gravity center distribution is optimized, and the AGV forklift is controlled to complete cargo loading; and S7, exiting the loading area along the optimized track, recording data and optimizing a loading strategy. The goods allocation identification precision is improved, the loading path is optimized, manual intervention is reduced, the loading efficiency, stability and adaptability are improved, and the logistics automation level is enhanced.

The invention relates to the technical field of logistics automation, in particular to a full-automatic stacking method and system based on machine vision and path planning, and the method comprises the following steps: based on three-dimensional point cloud data of goods, extracting point cloud coordinates, normal vectors and curvature values of the surface of the goods, calculating the geometric segmentation range of point cloud edge features, and calculating the geometric segmentation range of the point cloud edge features; and calculating a fitting relationship between the boundary size and curvature distribution. According to the method, the surface point cloud coordinates, the normal vector and the curvature value are extracted based on the three-dimensional point cloud data, the accuracy of geometric feature description of the complex cargo surface is enhanced, the geometric center and the variance range are reasonably determined through spatial distribution analysis and feature set classification, the accuracy and stability of shape classification are improved, and the accuracy and stability of shape classification are improved through gravity center and size deviation calculation. The position and pressure distribution of the contact point are optimized, the space priority analysis of the grabbing point and the obstacle point is combined, the path planning and obstacle point elimination strategy is optimized, the path conflict is reduced, and the flexibility and efficiency of logistics operation are improved.

The invention relates to the technical field of transfer robots, in particular to an intelligent warehouse logistics automatic transfer robot. The robot comprises a scraper and a suction cup which are arranged on a robot body, the scraper is provided with specially-designed groove pressing teeth, an arc-shaped groove with a guiding function can be formed in the surface of a box body, and it is ensured that a frost layer effectively falls off along a preset path through the design. The system collects temperature gradient, surface appearance and contact stress data in real time through the integrated multi-mode environment sensing unit, the intelligent decision-making unit establishes a dynamic control model based on the data, and accurate evaluation and self-adaptive processing of the frost layer state are achieved. The whole system constructs a complete closed-loop control chain, the limitation of a traditional defrosting method is overcome, the adsorption stability is kept, meanwhile, the operation efficiency is improved, the system is particularly suitable for the low-temperature storage environment of-25 DEG C and below, and a reliable solution is provided for cold-chain logistics automatic operation.

The invention provides a multi-AGV bidirectional channel dynamic avoidance method and system based on conflict prediction, and relates to the field of industrial logistics automation control, when a vehicle-mounted laser radar of a first AGV detects an opposite second AGV in a preset fan-shaped early warning interval, double-AGV priority quantification is carried out, avoidance role distribution is carried out according to a quantification priority comparison result, and an avoidance AGV is positioned; and the way-giving AGV receives the standard driving track of the non-way-giving AGV, calculates a smooth way-giving track, and carries out two-way traffic conflict dynamic resolution. The technical problem that the logistics efficiency of a high-beat precise assembly production line is seriously restricted due to the fact that the accuracy of collision conflict prediction and avoidance processing and the response timeliness are insufficient due to the fact that the autonomous collaboration of multi-AGV passing control is weak in a narrow industrial channel in the prior art is solved. Full-autonomous cooperative passage control of multiple AGV clusters in a narrow industrial channel is realized, and zero-interruption execution of high-value logistics tasks is ensured.

The invention discloses an e-commerce storage order real-time picking path planning method and system, and relates to the technical field of intelligent storage and logistics automation, and the method comprises the following steps: training a behavior prediction model based on historical picking behavior data, and outputting a path candidate region of a picker; constructing a path game model according to the path candidate area in combination with the current order task; based on a Stackelberg mechanism, solving a game equilibrium path distribution result; according to a solving result, evaluating the candidate path scheme through a multi-objective optimization algorithm, and outputting an optimal path scheduling strategy; according to the method, by introducing path candidate region extraction based on behavior prediction, fusion graph construction, a Stackelberg hierarchical game solving mechanism and multi-target optimization strategy output, real-time performance and global collaborative optimization of order picking path selection are realized.

The invention relates to the technical field of conveying line control systems, and provides a simple sorting station control method based on roller conveying line construction, and efficient and flexible operation of a sorting station is achieved by dynamically distributing a conveying path and independently triggering an outbound instruction. The method solves the problems that an existing sorting station lacks deep cooperation with a conveying line, cannot dynamically adjust operation logic and excessively depends on hardware equipment. The sorting station is emptied through initialization operation, a conveying path is dynamically distributed, and an independent outbound instruction is generated after sorting is completed. The method has the beneficial effects that the utilization rate of the sorting station is increased, invalid overstock is reduced, the equipment cost and maintenance complexity are reduced, meanwhile, the cooperative capacity of the sorting station and a conveying line is enhanced, and the overall logistics automation efficiency is improved.

The invention provides an intelligent warehousing robot operation method and system based on path planning, and relates to the technical field of warehousing logistics automation, and the method comprises the steps: receiving an order task through a warehousing management system, and obtaining the goods information and a target sorting position in the order task; based on a path planning algorithm, obtaining an initial path of the order task according to the cargo information and the target sorting position in the order task; based on the collected real-time environment data, utilizing a reinforcement learning model to dynamically optimize and adjust the initial path, and generating a target path of the order task; and the robot is controlled to execute sorting and carrying operation along the target path. According to the method, the initial path of the order task is obtained by optimizing the path planning algorithm, then the initial path is optimized and adjusted in combination with the real-time environment data, the target path is obtained, the robot is controlled to work through the target path, the dynamic environment adaptability of the storage robot is improved, and finally the working efficiency of the robot is improved.

The invention discloses a control method and device for a loading and unloading clamp based on pneumatic and electromagnetic composite self-locking, and relates to the technical field of logistics automation equipment. The method comprises the steps that size information and material information of goods to be loaded and unloaded are acquired; acquiring initial position information and target position information of goods to be loaded and unloaded; based on the size information, the material information, the initial position information and the target position information, clamping parameters of the loading and unloading clamp are determined, and the clamping parameters are clamping jaw control parameters of the loading and unloading clamp; and controlling the loading and unloading clamp to clamp the to-be-loaded and unloaded goods based on the clamping parameters of the loading and unloading clamp. The technical problem that in the prior art, automatic loading and unloading equipment is poor in adaptability is solved.

The invention discloses an automatic transfer robot for warehouse logistics. The automatic transfer robot comprises a lift truck, a fixing mechanism and an extension mechanism, a carrying table is arranged at the upper end of a lifting platform of the lifting truck; the fixing mechanism comprises L-shaped vertical plates, sliding tables, overturning assemblies and rotating shafts, the sliding tables capable of moving in a front-back symmetry mode are arranged in the carrying table, the rotating shafts are rotationally connected to the upper ends of the sliding tables through rotating bases, the rotating shafts are fixedly sleeved with the evenly-distributed L-shaped vertical plates, and the overturning assemblies are arranged at the right ends of the sliding tables; the overturning assembly drives the rotating shaft to rotate; the extension mechanism comprises U-shaped plates and sliding rails, the sliding rails which are evenly distributed are fixedly connected to the top wall of the carrying table, and the U-shaped plates are slidably connected between the sliding rails on the left side and the right side. And goods can be transferred conveniently.

The invention discloses an e-commerce logistics automatic stereoscopic warehouse, and relates to the field of warehousing, the e-commerce logistics automatic stereoscopic warehouse comprises a plurality of groups of goods shelves arranged at intervals and conveying units matched with the goods shelves, one side of each goods shelf is provided with a pick-and-place unit matched with the goods shelves and the conveying units, and the pick-and-place units are used for placing goods on the conveying units on the goods shelves; the goods shelf comprises four support rods and a plurality of supporting plates arranged among the four support rods. A supporting plate is installed between the two support rods on the same side, a lifting air cylinder is installed at the top of the supporting plate, and the top of the telescopic end of the lifting air cylinder is fixedly connected with a supporting plate. According to the automatic stereoscopic warehouse for e-commerce logistics, through mutual cooperation of the lifting air cylinders, the supporting plates and the bearing units, the position height of the supporting plates can be adjusted according to the size height of actual goods in the logistics goods storage process, so that the actual use flexibility of the goods shelf can be better; and meanwhile, the space utilization rate of the stereoscopic warehouse is higher.

The logistics automatic carrying device comprises a moving rod and a base, a strip-shaped groove is formed in one side of the moving rod, a two-way threaded rod is rotationally installed in the strip-shaped groove, sliding sleeves are connected to the two ends of the surface of the two-way threaded rod in a threaded and sleeved mode, and a clamping motor is fixedly installed at one end of the moving rod; and the output end of the clamping motor penetrates through the moving rod and is fixedly connected with one end of a bidirectional threaded rod, and a fixing plate is fixedly mounted on one side of each sliding sleeve. According to the logistics automatic carrying device, an operator places logistics between clamping plates, then a clamping motor is started, the clamping motor operates to enable a bidirectional threaded rod to rotate, then two sliding sleeves are driven to move in opposite directions in a strip-shaped groove, at the moment, the sliding sleeves can drive a fixing plate to slide, and then the logistics is carried out. And when the surfaces of the clamping plates are arranged on the outer surface of the logistics, the clamping plates can drive the round rods to slide in the fixing plates, and then the springs are extruded.

The invention relates to a two-dimensional image and geometric constraint-based cargo stack three-dimensional pose detection method and device, which are applied to the technical field of computer vision and logistics automation, and comprises the following steps of: through an edge straight line screening strategy, combining robust fitting of a random sampling consistency algorithm, calculating a three-dimensional pose of a cargo stack; a real physical boundary can be effectively and accurately recognized from complex visual interference such as adhesive tape, labels and printed patterns on the surface of a container, the accuracy and robustness of edge detection are remarkably improved, and therefore the high precision of final three-dimensional pose calculation is guaranteed; and secondly, only a common industrial camera is needed, and an expensive three-dimensional sensor such as a laser radar or a depth camera is not needed, so that the hardware cost and the maintenance complexity of the system are greatly reduced, and the cost benefit is extremely high. And thirdly, an efficient image processing and geometric calculation algorithm is mainly adopted, the calculation complexity is low, and the requirement for real-time detection of the goods stack on an industrial automatic assembly line can be met.

The invention discloses a new energy automobile logistics transfer robot based on visual navigation and an implementation method, relates to the field of logistics automation and intelligent equipment, and solves the problems that traditional equipment is low in navigation precision, difficult in data fusion and weak in obstacle avoidance capability. The transferring robot body comprises Mecanum wheels, supporting legs, an intelligent temperature control battery bin, a visual navigation system, a core control center, an interactive touch screen and a mechanical arm. The core control center comprises an image acquisition module, a data processing module, a path planning module and a transfer control module; all the modules work cooperatively, the automation and intelligence level of logistics transfer is remarkably improved, and powerful support is provided for the new energy automobile logistics industry.

The invention relates to the technical field of logistics automation and information processing, and discloses a sorting center intelligent management method and system based on a cloud platform. The method comprises the following steps: acquiring an image and input information of an abnormal package, and extracting a preliminary attribute; if the preliminary attribute is incomplete, analyzing the high-definition image, calculating a damage index and generating a repair queue; according to the repair queue, matching from a historical feature library to obtain inferred physical attributes; the input information is analyzed, all known attributes are synthesized, and a final destination is determined; generating an initial path according to the final destination and the real-time working condition; the preliminary path is optimized by fusing historical congestion records; and carrying out load balancing based on the optimized path, generating a final allocation scheme, and issuing and executing. According to the method, a complete process from multi-dimensional information intelligent completion to dynamic closed-loop scheduling is constructed, so that the technical problem of low abnormal package processing efficiency in the prior art is solved.

The invention relates to the technical field of logistics automation and intelligent scheduling, and discloses a multi-objective optimization logistics distribution path dynamic planning method, which comprises the following steps: S1, mapping a logistics distribution area and vehicles, clients and constraint entities in the area to a continuous coordinate space; s2, in the continuous coordinate space, optimizing cost, time, priority and constraints based on the mapped clients and constraint entities, and respectively constructing corresponding decision force fields; s3, based on a preset strategy adjustment matrix, carrying out linear transformation and combination on the plurality of constructed decision force fields so as to synthesize total decision force acting on the space; and S4, taking the synthesized total decision-making force as an external driving force. According to the method, through the strategy adjustment matrix and the path dynamic evolution equation, the high-level strategy and the path physical characteristics are deeply coupled, and refined, smooth and efficient regulation and control of multi-target dynamic path planning are realized.

The invention discloses an intelligent express sorting machine system based on'end-edge-cloud 'cooperation and a sorting method, and relates to the technical field of logistics automation. According to the system, the multi-mode recognition device, the intelligent self-adaptive regulation and control device, the equipment connection and management module, the self-adaptive sorting execution mechanism and the logistics data intelligent analysis system work cooperatively. The multi-modal identification device integrates image identification and radio frequency identification technologies, so that the parcel identification accuracy is improved; the intelligent self-adaptive regulation and control device monitors and adjusts the working states of the conveyor belt and the sorting port in real time; the equipment connection and management module realizes deep connection between the equipment and the cloud, thereby facilitating remote monitoring and management; the self-adaptive sorting execution mechanism flexibly processes different types of packages; and the logistics data intelligent analysis system mines data value to optimize operation. The problems that an existing express sorting technology is low in efficiency, poor in accuracy, weak in adaptability and the like are solved, efficient, accurate and intelligent express sorting is achieved, and the requirements of the modern logistics industry are met.

The invention relates to the technical field of logistics automation, in particular to an industrial air track shuttle vehicle which comprises a loop line type track, a shuttle vehicle body is arranged on the loop line type track, a frame body is connected to the shuttle vehicle body through a traction rope, and an electric wire spool used for winding and unwinding the traction rope is installed in the shuttle vehicle body. The frame body comprises a lifting plate connected to the traction rope, U-shaped rods are arranged on the lifting plate in a sliding mode at intervals, round blocks are connected to the top ends of the two sides of each U-shaped rod, and a feeding and discharging mechanism is arranged at the bottom of the lifting plate. The linear motor can drive the mounting plate to drive the first push plate and the second push plate to horizontally reciprocate, cargoes can be pushed into the frame through movement of the first push plate, the cargoes can be pushed out of the frame through movement of the second push plate, automatic feeding and discharging of the cargoes are achieved, and therefore automatic feeding and discharging are achieved; the feeding and discharging operation of goods can be completed without a roller conveyor, so that manual operation can be reduced, the labor intensity can be reduced, the efficiency can be improved, and the cost can be reduced.

The invention discloses a multi-robot intelligent collaborative simulation training system based on an augmented reality technology, and relates to the technical field of intelligent warehousing and logistics automation. An AR dynamic obstacle generation technology breaks through static limitation of a traditional simulation scene, sudden interference such as container collapse, temporary forbidding and the like is simulated through a physical engine, and real-time simulation is achieved. A training strategy is directly exposed to a high-simulation risk environment; a topology potential field decision-making mechanism is introduced to quantify course conflicts and distance threats into a repulsive force field in a unified mode, a course Gaussian modulation item accurately filters non-direct collision targets, and the oscillation defect of a traditional potential field method is avoided. According to the path entropy calculation, the conflict probability is analyzed through direction density distribution, gradient adjustment is forcibly activated when the entropy of a narrow channel exceeds a threshold value, the chain reaction of high-density deadlock is restrained from the source, and the group path fluency is guaranteed.

Proposed are a logistics automation system and an operating method thereof. The logistics automation system includes a processor, a memory configured to load a computer program executed by the processor, and a storage configured to store the computer program, wherein the computer program comprises instructions for performing an operation for receiving at least one order, an operation for allocating product picking tasks for the at least one order, an operation for setting a picking route according to a predefined criterion for the allocated product picking tasks, and an operation for transmitting guide information about the allocated product picking tasks to a worker terminal, wherein the guide information includes information about product picking location of a product loading area.

The invention relates to an express balance wheel sorting machine control method and device and a sorting machine, and aims to improve the cargo posture stability and transmission efficiency in the logistics sorting process. The method comprises the following steps: receiving goods sorting path information, and generating a synchronous control instruction including swing wheel disc angle deflection, goods linear speed and a four-wheel belt transmission mechanism; the deflection angle of each swing wheel disc is calculated in real time, and on the premise of ensuring stable conveying of goods and balanced stress of each roller, the optimal rotating speed of a driving wheel is dynamically solved by adopting a multi-target dynamic optimization model on the basis of transmission balance among the driving wheel, a tensioning wheel and a driven wheel, so that the vibration torque of each belt is minimum, and the transmission efficiency is maximized. The control device is composed of a path information receiving module, a control instruction generating module, a swing wheel disc angle control module, a linear speed control module and a shearing vibration control module, efficient, low-energy-consumption, cooperative and intelligent control and stable transmission of the multi-swing-wheel disc sorting mechanism in the sorting process are achieved, and the multi-swing-wheel disc sorting mechanism is suitable for a logistics automatic sorting system.

The invention discloses an intelligent boxing method and system based on space optimization in an automatic loading and unloading scene, and relates to the technical field of logistics automation, and the method comprises the steps: obtaining the basic information of a to-be-loaded box body, measuring the space size of a loading container, and initializing the constraint condition of boxing; calculating an initial boxing plan based on a three-dimensional space optimization algorithm, and establishing a spatial index mechanism; and guiding the loading equipment to place the current box body, detecting the actual placement position of the box body, updating the position information of the loaded box body, recalculating the boxing plan of the remaining box bodies, and repeating the steps until the loading of all the box bodies is completed. The method is specially designed for an automatic loading and unloading scene, can be seamlessly integrated into intelligent equipment such as a loading and unloading robot, and provides key algorithm support for logistics automation; the logistics transportation cost is effectively reduced by improving the loading efficiency and the space utilization rate; through a real-time detection and dynamic adjustment mechanism, the system can automatically deal with abnormal conditions in the loading process.

The invention discloses an operation control method and system for three-dimensional warehouse scheduling, and relates to the technical field of warehousing and logistics automation, and the method comprises the steps: receiving a warehouse-in or warehouse-out task instruction of a measurement production scheduling platform, and carrying out the analysis to generate an operation instruction set; collecting equipment identification information and comparing the equipment identification information with the task instruction; generating a goods allocation allocation or path optimization scheme according to the task type; and according to the optimization scheme, the conveying equipment is controlled to complete warehousing or ex-warehouse operation of the equipment. Through the dynamic goods allocation and path optimization method, the optimal storage position and the logistics path of the equipment are calculated in real time, the problems of storage space waste and unreasonable path planning caused by fixed rules are solved, and the logistics operation efficiency and the equipment scheduling accuracy are improved. Through path node and equipment state monitoring, task allocation is dynamically adjusted, and continuity and efficient completion of logistics operation are guaranteed. And aiming at abnormal conditions, goods allocation or path planning is rapidly corrected, equipment redistribution and path adjustment are realized, and manual intervention is reduced.

The invention discloses an intelligent warehouse task allocation method and system for multiple types of AGVs, and particularly relates to the technical field of intelligent warehouse logistics automation, and the method comprises the steps: obtaining a to-be-allocated task through a docking warehouse management system WMS, carrying out the structural normalization processing, mapping the to-be-allocated task to a warehouse topological map, and generating a task execution element set; and meanwhile, the running state and event log records of each AGV are collected. Calling a task consumption model based on the environment feature vector to obtain a power consumption predicted value and a time consumption predicted value; constructing a health risk score based on the monitoring window and mapping the health risk score into a risk level; and generating an electric quantity safety margin by combining the residual electric quantity with the necessary return stroke or the nearby complementary energy cost, and forming a dynamic capability portrait. In the candidate set generation stage, sustainability constraint verification is carried out according to the health risk score, the risk level, the electric quantity safety margin and the maintenance window constraint, a rolling scheduling mechanism is adopted to generate a task allocation result, and a task instruction is issued to the corresponding AGV to be executed.

The invention discloses a multi-layer three-dimensional cross belt sorting control method and system, and relates to the technical field of logistics automation, and the method comprises the following steps: scanning and identifying an identification code of a target material, extracting the priority of the identification code, and marking a priority label; and the system monitors the materials in real time based on the priority labels to obtain the latest information. And performing hierarchical path planning according to the material information, and monitoring a fault in the path through a set fault threshold. Once a fault is detected, the system is automatically switched to a standby path, it is ensured that sorting control of the materials is continuously carried out, and the stability and high efficiency of the sorting process are kept. The technical problem that an existing multi-layer three-dimensional cross-belt sorting system is insufficient in material sorting efficiency and fault handling capacity is solved, and load balance of a sorting path is further achieved by integrating a hierarchical conflict adjusting strategy of an automatic three-dimensional warehouse and a redundancy switching mechanism of an intelligent suspension conveying system; and the technical effect of ensuring the stability and high efficiency in the sorting process is achieved.

The invention discloses a parcel specification detection method based on shape fitting, and relates to the technical field of logistics, and the method comprises the steps: carrying out the target detection of an RGB image of a parcel detection region through employing a target detection model, determining a parcel region where a to-be-detected parcel is located, extracting the depth data of the parcel region, and converting the depth data into parcel point cloud data, then randomly selecting a plurality of point clouds from the parcel point cloud data to respectively fit a plurality of reference geometric shapes, and evaluating the matching degree between other parcel point cloud data and each fitted reference geometric shape to obtain the confidence coefficient of each fitted reference geometric shape; and finally, calculating according to the reference geometrical shape with the maximum confidence coefficient to obtain specification parameters of the parcel to be detected. According to the method, through combination of an image algorithm and a point cloud processing technology, robust processing can be carried out on point cloud data with different qualities, so that various standard and special-shaped parcel specifications can be quickly and accurately identified, and the sorting efficiency and the application range of a logistics automation system can be remarkably improved.

The invention relates to the technical field of intelligent warehouse logistics automation, and particularly discloses a stereoscopic warehouse AGV and elevator intelligent regulation and control system based on the Internet of Things, and the system comprises an Internet of Things sensing module, an edge calculation module, a cloud decision module and a control execution module, and is specifically characterized in that a real-time digital twinborn model is constructed through the edge calculation module; a collaborative optimization scheduling algorithm with task execution time window coupling of the AGV and the elevator at the connection port as a core constraint condition is adopted in the cloud decision module, and a scheduling instruction containing a path and a precise time window is generated; the edge calculation module further performs real-time local obstacle avoidance path planning for the AGV by using a dynamic window method based on the instruction, and implements priority-based traffic management to ensure that the AGV passes preferentially in work; according to the method, accurate matching of the AGV and the elevator operation plan in time and space is realized, waiting time between equipment is reduced, the equipment utilization rate and the system throughput are improved, and the overall efficiency of a warehousing system is further improved.

The invention discloses an automatic guided vehicle intelligent scheduling and path optimization system based on image recognition, and relates to the technical field of intelligent warehousing and logistics automation, and the system comprises an information collection module which is used for collecting a goods taking task signal, goods receiving point image information and AGV operation state data; the intelligent dispatching center is used for performing task distribution, global path planning and dynamic conflict resolution based on the goods taking task signal, the goods receiving point image information and the AGV operation state data and issuing a dispatching instruction; and the task execution and monitoring module is used for issuing a driving instruction to each target AGV according to the scheduling instruction and monitoring the task execution process of the AGV. According to the method, image recognition, statistical modeling and rolling optimization are taken as the core, the improved path optimization and the obstacle avoidance algorithm are combined, a multi-AGV high-concurrency-response, scientific-scheduling, collision-free, optimal-path and high-robustness transportation system is constructed, the transportation efficiency, safety and flexibility are remarkably improved, the intelligent degree is high, and the expandability is high.

The invention relates to the technical field of logistics automation and intelligent detection, and discloses a sorting automatic identification and early warning system based on computer vision, and the system comprises a visual perception module which is used for collecting multi-dimensional information of parcels and carrying out physical pre-classification; the strategy generation module dynamically generates a detection parameter set according to the pre-classification result; the physical detection module is used for applying active physical excitation to the parcel according to the parameter set and synchronously acquiring multi-modal response data such as acoustics, thermotics and surface deformation; and the fusion decision module is used for processing the multi-modal response data to extract physical feature vectors so as to determine the health state of the parcel and generate a sorting early warning instruction. The invention further provides a corresponding method. Through the above scheme, preposed identification of potential risks such as internal damage and structural fatigue of the parcel is realized, the detection scheme has adaptivity, and the accuracy and robustness of identification are improved through the multi-modal fusion decision.

The invention discloses a delivery point calculation method based on three-segment-code area refinement and application thereof, and relates to the technical field of logistics automatic sorting, and the method comprises the steps: collecting three-segment-code area data of each salesman, and determining a preliminary delivery point division standard of an area in charge of the salesman based on the three-segment-code area data; calculating delivery point identification information corresponding to each delivery address by using an address model algorithm through matching of the delivery address provided by a client and a delivery point geographic fence; when the electronic waybill is generated, the identification information of the delivery points is printed on the electronic waybill according to a calculation result, and a sorter sorts and aggregates parcels according to the identification information of the delivery points on the electronic waybill; according to the method, through an intelligent address analysis model, in combination with historical delivery data and address keyword matching, the matching precision of complex addresses is further improved, and automatic calculation of delivery points is realized.