Autonomous Mobile Picking With Stationary Robot Fulfillment
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Solution Overview
Problem
Picking items in warehouses is labor-intensive, and existing methods lack efficient automation to reduce labor costs and scale with order volume effectively.
Innovation Solution
The implementation of autonomous mobile robotic units capable of autonomous operation and augmentation by humans, which can alter their path to work alongside personnel, equipped with receptacle supports, robotic arms, and indicator systems for efficient picking and putting of articles, and integrated with stationary automated systems for order fulfillment and inventory replenishment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual picking is used, then labor flexibility is maintained, but labor costs are high and efficiency is low
Solution Approach 1:
The robotic units autonomously navigate the facility, locate items, and transport them to picking stations without human intervention. The system self-manages path planning, obstacle detection, and coordination with workers, eliminating the need for manual material handling and significantly improving picking efficiency while maintaining operational flexibility.
Solution Approach 2:
The system dynamically adapts its operation mode based on real-time conditions. Robotic units can operate independently for routine tasks and seamlessly coordinate with human workers when complex picking is required. The path planning and task allocation are dynamically adjusted to optimize productivity while maintaining flexibility in automation level.
2Productivity
If more robotic units are added to increase capacity, then automation level improves, but facility complexity and coordination difficulty increase
Solution Approach 1:
Each robotic unit is designed as a universal platform capable of performing multiple functions: autonomous navigation, item transport, station docking, and coordination with both automated and manual picking processes. This multi-functionality allows the system to scale capacity by adding identical units rather than designing specialized equipment, thereby managing complexity while increasing productivity.
Solution Approach 2:
The system implements continuous feedback loops where robotic units report their status, location, and task completion to a central coordination system. This feedback mechanism enables real-time optimization of task allocation and path planning, allowing the system to manage increased numbers of units without proportionally increasing coordination complexity. The feedback-driven dynamic adjustment resolves the contradiction between capacity and complexity.
Data Source
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AI summary
An order-picking method (210), comprising: autonomously routing at least one mobile robotic unit (214) in a facility having a stationary robotic system (240); and conducting at least one chosen from order fulfilment and inventory replenishment operations with stationary robotic system (240), said stationary robotic system (240) including a stationary robot (242) and vision equipment (244) to (i) store product with the stationary robot (242) to a receptacle (218), the product being retrieved from an assignment location (246) or (ii) retrieve product from a receptacle (218) with the stationary robot (242), the product being stored to an assignment location (246).