Communication system for realizing physical sorting

Abstract

The invention discloses a communication system for realizing physical sorting, which relates to the technical field of communication systems, and comprises a central task management module for processing data and issuing advanced task instructions, a distributed sensing module for acquiring real-time data, and an autonomous control module for controlling equipment to execute specific operation instructions. And the communication network module is used for transmitting communication data. Computing tasks are sunk to sensor terminals through a distributed sensing architecture, the network bandwidth and the load of a central server are greatly reduced, the real-time performance and the expandability of the system are improved, the dynamic response and the flexibility of the system are enhanced, and the innovative data upgrading processing module is used for realizing multi-sensor redundancy backup and mode switching through a multi-sensor redundancy backup and mode switching mechanism. Seamless transition from a fusion mode to a degradation mode during failure is achieved, the problem of systematic paralysis caused by single-point failure is thoroughly solved, and unplanned shutdown is converted into planned maintenance.

Description

Technical Field

[0001] This invention relates to the field of communication system technology, specifically to a communication system that implements physical sequencing. Background Technology

[0002] In automated logistics and sorting systems, traditional technical architectures typically suffer from the following inherent drawbacks, which limit their efficiency, reliability, and scalability: Centralized processing bottleneck: Traditional systems typically employ a centralized processing architecture, where all raw sensing data (such as high-definition video streams and 3D point clouds) must be uploaded to a central server for processing. This places enormous pressure on network bandwidth, easily becoming a bottleneck for system performance and limiting the expansion of system scale and the improvement of response speed.

[0003] High latency and low real-time performance: Because all computations rely on a central server, the chain from data acquisition, transmission to processing, and then issuing control commands is too long, introducing significant latency. This makes the system difficult to handle dynamic environments that require rapid responses, such as avoiding suddenly appearing obstacles or grabbing items on a high-speed conveyor belt.

[0004] Single point of failure and vulnerability: The entire system's sensing capabilities are highly dependent on a central server and a few key sensors. Once the central server crashes or a key sensor fails, the entire system often faces the risk of a complete shutdown, lacking fault tolerance, leading to production interruptions and economic losses.

[0005] High maintenance costs: Failures in traditional systems are often sudden and require immediate emergency repairs. Such unplanned downtime disrupts normal production rhythms, requires maintenance personnel to respond reactively, and results in high repair costs and low efficiency.

[0006] Poor flexibility: Robot controllers typically lack intelligence, merely executing precise trajectory point instructions from a central server. This makes the entire system rigid and difficult to adapt to complex and changing environments. Any minor environmental change requires the central server to recalculate and intervene, preventing truly autonomous and flexible production. Summary of the Invention

[0007] The purpose of this invention is to provide a communication system that realizes physical ordering, thereby solving the problems in the background art.

[0008] To achieve the above objectives, the present invention provides the following technical solution: a communication system for realizing physical ordering, comprising: The central task management module includes a system status monitor, a data enhancement and processing module, a data fusion module, and a task scheduler. The distributed sensing module includes multiple visual acquisition modules and a weighing module; The autonomous control module includes a task parsing module, a local path planning module, a real-time obstacle avoidance module, and a motion actuator; Multiple vision acquisition modules are signal-connected to the communication network module; multiple weighing modules are signal-connected to the communication network module; the communication network module is signal-connected to the system status monitor; the communication network module is signal-connected to the data fusion module; the communication network module is signal-connected to the local path planning module; the system status monitor is signal-connected to the data enhancement processing module; the data enhancement processing module is signal-connected to the data fusion module; the data enhancement processing module is signal-connected to the task scheduler; the data enhancement processing module is signal-connected to the task parsing module; the task parsing module is signal-connected to the local path planning module; the local path planning module is signal-connected to the real-time obstacle avoidance module; and the real-time obstacle avoidance module is signal-connected to the motion actuator.

[0009] Furthermore, the visual acquisition module and the weighing module have built-in processing units for running recognition, localization, and parsing algorithms locally, outputting information including object ID and location. Weight, confidence level One or more types of structured data.

[0010] Furthermore, the local route planning module is based on a local map. and real-time sensor information The collision-free path is dynamically calculated by solving the following optimization problem. The formula is as follows: .

[0011] Furthermore, the data fusion module is used to receive and fuse structured sensing results from N intelligent sensing nodes, and the fused position estimation... Calculated using the following formula: ; in, Let be the position of the object measured at the i-th node. Coordinate transformation matrix Based on confidence level The assigned weights.

[0012] Furthermore, the weights The calculation satisfies = 2 .

[0013] Furthermore, the data enhancement processing module is used for: Monitor the health status and data confidence level of all intelligent sensing nodes. ; The confidence level With preset threshold Comparisons are used to diagnose faults; Depending on the number of faulty nodes, the system operates in normal mode ( ), downgrade mode ( ) or safe pause mode ( Run under )

[0014] Furthermore, the normal mode of the data enhancement processing module ( ), downgrade mode ( ) or safe pause mode ( The switching logic is defined by the following function: .

[0015] Furthermore, in degraded mode, the system stops data fusion and directly uses the data from any healthy node J, through the formula... Calculate the position in the world coordinate system.

[0016] Furthermore, the data upgrade processing module is also used to record fault events, the duration of the downgrade mode, and generate maintenance reports.

[0017] Furthermore, the data upgrade processing module is configured to generate a detailed maintenance request report after the system enters the downgrade mode or safe pause mode. The report includes at least the fault node identifier, the fault occurrence timestamp, the system downgrade duration, and recommended maintenance measures. The system will undergo maintenance and debugging within the predetermined maintenance time window, rather than immediately interrupting the production process.

[0018] This invention provides a communication system for implementing physical ordering. It has the following advantages: (1) In this invention, the real-time performance and efficiency of the system are significantly improved: through the distributed perception architecture, the computing tasks are pushed down to the edge nodes, and only lightweight result data is uploaded, which greatly reduces the network bandwidth pressure and the computing load of the central server, reduces communication latency, and makes the system response faster.

[0019] (1) In this invention, the robustness and availability of the system are greatly enhanced: the core innovation is the introduction of a data upgrade processing mechanism. When some sensors fail, the system can automatically degrade and continue to work using the remaining healthy nodes instead of shutting down completely. This minimizes unplanned downtime and realizes the transformation from "single point failure causing system paralysis" to "single point failure only causing graceful performance degradation", which significantly improves the availability and reliability of the system.

[0020] (1) In this invention, a high degree of autonomy and flexibility is achieved: by giving the autonomous control module local path planning and real-time obstacle avoidance capabilities, the central server only needs to issue high-level goals, without micromanagement of specific motion trajectories. This enables individual robots to respond quickly to dynamic environmental changes, making the system more flexible, intelligent, and suitable for complex scenarios.

[0021] (1) In this invention, the perception accuracy and reliability are improved: In normal mode, the information of redundant sensors is effectively utilized through the multi-sensor data fusion algorithm, the noise and error of a single sensor are suppressed, and a more accurate and reliable perception result is obtained than that of any single sensor.

[0022] (1) In this invention, the maintenance process is optimized and the operating cost is reduced: the system can automatically diagnose faults and generate detailed maintenance reports, making maintenance work predictable and plannable, and can be carried out in a concentrated manner during production breaks, reducing the high costs and production losses caused by emergency repairs, and optimizing the overall operating cost. Attached Figure Description

[0023] Figure 1 This is a general system diagram of a communication system for implementing physical ordering according to the present invention; Figure 2 This is a schematic diagram of a central task management module for a communication system that implements physical sorting according to the present invention; Figure 3 This is a schematic diagram of a distributed sensing module for a communication system that implements physical sorting according to the present invention; Figure 4 This is a schematic diagram of an autonomous control module for a communication system that implements physical sorting according to the present invention.

[0024] In the diagram: 1. Central task management module; 2. Distributed sensing module; 3. Autonomous control module; 4. Communication network module. Detailed Implementation

[0025] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments.

[0026] Examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain the invention, and should not be construed as limiting the invention.

[0027] The present invention will be further described below with reference to the accompanying drawings and embodiments: Example 1, please refer to Figure 1-4 This invention provides a technical solution: a communication system for realizing physical sorting, comprising: a central task management module 1 for data processing and issuing high-level task commands; a distributed sensing module 2 for acquiring real-time data; an autonomous control module 3 for controlling devices to execute specific operation commands; and a communication network module 4 for transmitting communication data. The central task management module 1 includes a system status monitor, a data enhancement processing module, a data fusion module, and a task scheduler. The distributed sensing module 2 includes multiple visual acquisition modules and a weighing module. The autonomous control module 3 includes a task parsing module, a local path planning module, a real-time obstacle avoidance module, and a motion actuator. Signal connections are established between the multiple visual acquisition modules and the communication network module 4, and between the multiple weighing modules and the communication network module 4. The communication network module 4 is connected to the system status monitor, the data fusion module, and the local path planning module. The system status monitor, data enhancement processing module, data fusion module, task scheduler, task parsing module, local path planning module, real-time obstacle avoidance module, and motion actuator are all connected via signal connections. This architecture avoids transmitting massive amounts of raw image data, greatly reducing network bandwidth pressure, lowering communication latency, and making the system response more real-time. Simultaneously, distributed processing avoids the accumulation of computing tasks on a central server, improving the overall system processing capacity.

[0028] Please see Figure 1-4 The visual acquisition module and weighing module have built-in processing units that run recognition, localization, and analysis algorithms locally, outputting information including object ID and location. Weight, confidence level One or more structured data types, local route planning module, which is based on local maps and real-time sensor information The collision-free path is dynamically calculated by solving the following optimization problem. : The data fusion module is used to receive and fuse structured sensing results from N intelligent sensing nodes, and the fused location estimation... Calculated using the following formula: ,in, Let be the position of the object measured at the i-th node. Coordinate transformation matrix Based on confidence level Assigned weights, weights The calculation satisfies = 2 The task scheduler of the central task management module 1 only issues high-level instructions, such as "move the box at point A to point B". After receiving the instructions, the task parsing module of the autonomous control module 3 uses the local path planning module based on the local map. and real-time sensor information Autonomously solve optimization problems The path planning module dynamically adjusts the path according to environmental changes, and the motion actuator ultimately completes the action. By delegating path planning and real-time obstacle avoidance to the autonomous control module 3, the individual robot has a high degree of autonomy and agility, and can quickly respond to environmental changes, such as avoiding suddenly appearing obstacles, without waiting for calculations and instructions from the central server, which greatly improves the operational reliability of the individual robot.

[0029] Please see Figure 1-4 The data enhancement processing module is used to monitor the health status and data confidence level of all intelligent sensing nodes. Confidence level With preset threshold Comparisons are made to diagnose faults, and the system in normal mode is evaluated based on the number of faulty nodes. ), downgrade mode ( ) or safe pause mode ( Running under ) in the normal mode of the data enhancement processing module ( ), downgrade mode ( ) or safe pause mode ( The switching logic for system mode is defined by the following function: In degraded mode, the system stops data fusion and directly uses data from any healthy node J, through the formula... The system calculates the world coordinate system position. The data enhancement processing module also records fault events, the duration of degradation mode, and generates maintenance reports. Configured to generate a detailed maintenance request report after the system enters degradation mode or safe pause mode, this report includes at least the fault node identifier, fault occurrence timestamp, system degradation duration, and recommended maintenance measures. The system will undergo maintenance and debugging within a predetermined maintenance time window, rather than immediately interrupting production. In normal mode, the data fusion module receives data from multiple sensing nodes and uses a weighted fusion algorithm to calculate high-precision positions, effectively suppressing noise from individual sensors and improving sensing accuracy. This mechanism is the core innovation of the system, preventing a complete system crash when some sensors fail. It allows the system to maintain basic operation at the cost of partial performance degradation, significantly improving system robustness and availability. The generated maintenance report guides personnel to perform precise repairs within the maintenance window, minimizing unplanned downtime and ensuring production continuity.

[0030] Working principle: Normal execution process: Task Issuance: The task scheduler of the central task management module 1 receives advanced instructions, such as "move the box at point A to point B", and issues them to the task parsing module of the designated autonomous control module 3 through the communication network module 4. Distributed sensing: Multiple vision acquisition modules and weighing modules deployed in the work area work in parallel, processing the raw data locally (identification, localization, and parsing) to generate data including object ID and location. Weight, confidence level Structured data packets, Data Upload and Fusion: Each sensing module uploads only lightweight structured data to the data fusion module of the central task management module 1 via the communication network module 4. The data fusion module uses a weighted fusion algorithm. (in = 2 This allows for the calculation of more accurate and reliable target object position coordinates. Autonomous Planning and Execution: The task parsing module of the autonomous control module 3 receives high-level instructions, while its local path planning module subscribes to target location and real-time environmental information from the data fusion module. The path planning module solves... The system generates an optimal collision-free path locally, and the real-time obstacle avoidance module monitors the environment and dynamically adjusts the path during movement. Finally, the motion actuator completes physical operations such as grasping, transporting, and placing. System monitoring: Throughout the process, the system status monitor tracks the health status of all modules in real time, ensuring normal operation. Fault degradation process: Fault diagnosis: The system status monitor continuously monitors the confidence level of each sensing module. And heartbeat signals, when a certain module is detected Continuously below the threshold If a signal is lost, the system will determine the fault and immediately send an alarm to the data escalation processing module. Pattern Decision: The data enhancement processing module makes decisions based on preset mathematical logic. .

[0031] Downgraded operation: If you enter downgrade mode ( The data enhancement processing module will instruct the data fusion module to stop working and select data from any currently healthy sensing node J for direct use. The system performs calculations and sends out the results. In this mode, the accuracy and robustness of the system decrease, but the core functions are maintained and the task continues to be executed.

[0032] If you enter safe pause mode ( The data enhancement processing module sends a signal to the task scheduler, ordering all execution units to suspend operations and await manual intervention to ensure system security.

[0033] Maintenance preparation: During downgrade or pause, this module records fault details and duration, and generates a maintenance report to guide technicians to perform efficient and accurate repairs within the scheduled maintenance window, avoiding production interruptions.

[0034] The above are merely preferred embodiments of the present invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the inventive concept of the present invention, and these all fall within the protection scope of the present invention.

Claims

1. A communication system for implementing physical ordering, characterized in that, include: The central task management module (1) includes a system status monitor, a data enhancement processing module, a data fusion module, and a task scheduler; The distributed sensing module (2) includes multiple visual acquisition modules and a weighing module; The autonomous control module (3) includes a task parsing module, a local path planning module, a real-time obstacle avoidance module, and a motion actuator; Multiple vision acquisition modules are signal-connected to the communication network module (4), multiple weighing modules are signal-connected to the communication network module (4), the communication network module (4) is signal-connected to the system status monitor, the communication network module (4) is signal-connected to the data fusion module, the communication network module (4) is signal-connected to the local path planning module, the system status monitor is signal-connected to the data enhancement processing module, the data enhancement processing module is signal-connected to the data fusion module, the data enhancement processing module is signal-connected to the task scheduler, the data enhancement processing module is signal-connected to the task parsing module, the task parsing module is signal-connected to the local path planning module, the local path planning module is signal-connected to the real-time obstacle avoidance module, and the real-time obstacle avoidance module is signal-connected to the motion actuator.

2. The communication system for implementing physical ordering according to claim 1, characterized in that, The visual acquisition module and weighing module have built-in processing units for running recognition, localization, and analysis algorithms locally, outputting information including object ID and location. Weight, confidence level One or more types of structured data.

3. A communication system for implementing physical ordering according to claim 2, characterized in that, The local route planning module is based on a local map. and real-time sensor information The collision-free path is dynamically calculated by solving the following optimization problem. The formula is as follows: 。 4. A communication system for implementing physical ordering according to claim 3, characterized in that, The data fusion module is used to receive and fuse structured sensing results from N intelligent sensing nodes, and the fused position estimation... Calculated using the following formula: ； in, Let be the position of the object measured at the i-th node. Coordinate transformation matrix Based on confidence level The assigned weights.

5. A communication system for implementing physical ordering according to claim 4, characterized in that, The weight The calculation satisfies = 2 .

6. A communication system for implementing physical ordering according to claim 5, characterized in that, The data enhancement processing module is used for: Monitor the health status and data confidence level of all intelligent sensing nodes. ; The confidence level With preset threshold Comparisons are used to diagnose faults; Depending on the number of faulty nodes, the system operates in normal mode ( ), downgrade mode ( ) or safe pause mode ( Run under ) 7. A communication system for implementing physical ordering according to claim 6, characterized in that, The normal mode of the data enhancement processing module ( ), downgrade mode ( ) or safe pause mode ( The switching logic is defined by the following function: 。 8. A communication system for implementing physical ordering according to claim 7, characterized in that, In degraded mode, the system stops data fusion and directly uses data from any healthy node J, through the formula... Calculate the position in the world coordinate system.

9. A communication system for implementing physical ordering according to claim 8, characterized in that, The data upgrade processing module is also used to record fault events, the duration of the downgrade mode, and generate maintenance reports.

10. A communication system for implementing physical ordering according to claim 9, characterized in that, The data upgrade processing module is configured to generate a detailed maintenance request report after the system enters a downgrade mode or a safe pause mode. The report includes at least the fault node identifier, the fault occurrence timestamp, the system downgrade duration, and recommended maintenance measures. The system will undergo maintenance and debugging within a predetermined maintenance time window, rather than immediately interrupting the production process.

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