Cargo Sorting Robots With Threshold-Based Container Transfer
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Solution Overview
Problem
Existing goods sorting systems, such as cross-belt and robot steel platform systems, face inefficiencies in sorting accuracy and efficiency due to inflexible design, high labor costs, and manual handling, which leads to increased labor demands and reduced productivity.
Innovation Solution
A goods sorting system comprising a control server, multiple delivery robots, and carrying robots that communicate to determine delivery routes and manage goods distribution, automatically allocating resources based on container thresholds to optimize sorting efficiency and flexibility.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Stability of the object's composition
If cross-belt sorting system is used with fixed delivery ports, then sorting structure is stable, but system flexibility and extendability deteriorate
Solution Approach 1:
The sorting system is divided into multiple independent sorting units, each with its own delivery robot and control module. This segmentation allows individual units to be added, removed, or modified without affecting the entire system, thereby improving flexibility and extendability while maintaining overall structural stability through modular design.
Solution Approach 2:
The system transitions from fixed mechanical delivery ports to dynamic robot-based delivery points. Delivery robots can move freely along the conveyor belt and adapt their positions based on real-time sorting requirements, enabling the system to dynamically adjust to changing sorting demands while maintaining operational stability through centralized control.
2Device complexity
If manual collection and buffering of goods is implemented, then system complexity is reduced, but sorting efficiency and accuracy deteriorate
Solution Approach 1:
Delivery robots are equipped with automated goods collection and buffering capabilities, allowing them to autonomously collect sorted goods from delivery ports and buffer them in designated containers. This self-service mechanism eliminates the need for manual intervention, thereby improving sorting efficiency and accuracy while the standardized collection process keeps system complexity manageable.
Solution Approach 2:
Manual mechanical operations of collecting and buffering goods are replaced with automated robot operations. The delivery robots use sensors, grippers, and navigation systems to automatically collect goods and buffer them in containers, replacing human labor with intelligent mechanical systems that improve efficiency and accuracy without significantly increasing overall system complexity.
3Productivity
If robot steel platform sorting system is used with high construction, then delivery capability is improved, but construction cost and flexibility deteriorate
Solution Approach 1:
Delivery robots are designed as multi-functional units that can perform multiple tasks: transporting goods along the conveyor, delivering to various ports, collecting sorted goods, and buffering in containers. This universality allows the system to achieve high delivery capability with standardized robot units rather than expensive custom-built steel platforms, reducing construction costs and improving flexibility.
Solution Approach 2:
The system uses a centralized control server as an intermediary that coordinates multiple delivery robots and manages the sorting process. This control intermediary enables the system to achieve complex delivery capabilities through software coordination rather than expensive physical infrastructure, reducing construction costs while maintaining high delivery capability and flexibility.
4Measurement precision
If high robot density is implemented in steel platform, then delivery precision is improved, but waiting time and stopping increase
Solution Approach 1:
The control server pre-plans delivery routes and coordinates robot movements before actual delivery operations begin. By anticipating sorting requirements and preparing robot paths in advance, the system maintains high delivery precision while minimizing waiting time and stopping, as robots are already positioned and ready when goods need to be delivered.
Solution Approach 2:
Multiple delivery robots operate simultaneously and continuously along the conveyor belt, maintaining constant motion and delivery operations. This continuous operation eliminates idle waiting time between deliveries, as robots can continuously service different ports without stopping, while the control server ensures precise coordination to maintain delivery accuracy.
Data Source
AI summary
Disclosed are a goods sorting system and method. The system includes a control server, a delivery robot, and a first carrying robot. The control server is configured to determine a delivery port according to a road direction of goods to be delivered, allocate the delivery robot, plan a traveling route for the delivery robot, generate a delivery instruction and send the delivery instruction to the delivery robot. The delivery robot is configured to travel to the delivery port, deliver the goods to be delivered to the delivery port. The control server is further configured to: when the number of goods collected in a target goods collection container below the delivery port is greater than or equal to a preset threshold, allocated the first carrying robot, plan a traveling route for the first carrying robot, generate a carrying instruction and send the carrying instruction to the first carrying robot. The first carrying robot is configured to travel to the target goods collection container according to the traveling route, carry the target goods collection container to a goods collection station. Further disclosed is a server and a storage medium.