Autonomous Vehicle Routing for Warehouse Closed-Area Picking
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Solution Overview
Problem
Current autonomous vehicle routing systems face challenges in navigating through areas closed to travel, such as loft areas, narrow aisles, and crowded spaces, leading to inefficient pick routes and increased picker walking time.
Innovation Solution
The system dynamically revises and reconfigures autonomous vehicle routes to guide pickers through closed areas, allowing the vehicle to meet the picker at an optimized rendezvous location, minimizing walking time and optimizing pick routes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the autonomous vehicle follows a fixed pick route, then the routing system is simple and reliable, but the picker walking time increases and pick rate decreases when areas are closed to travel
Solution Approach 1:
The routing system transitions from static fixed routes to dynamic adaptive routing. The system continuously monitors area accessibility and automatically recalculates pick routes in real-time, allowing the autonomous vehicle to adapt its path based on current warehouse conditions such as closed areas, thereby maintaining high pick rates without requiring complex manual intervention
Solution Approach 2:
The system implements continuous feedback loops where the routing algorithm receives real-time information about area accessibility, picker location, and product locations. This feedback enables the system to dynamically adjust routes, optimizing picker walking time and maintaining productivity even when parts of the warehouse are inaccessible to autonomous vehicles
2Productivity
If the autonomous vehicle navigates through closed areas, then the pick route efficiency improves, but the vehicle cannot access loft areas, narrow aisles, and crowded spaces
Solution Approach 1:
The system introduces a hybrid operation mode where the autonomous vehicle serves as an intermediary for areas it can access, while human pickers serve as intermediaries for closed areas. The routing system coordinates between autonomous vehicle capabilities and human picker capabilities, dynamically assigning tasks based on area accessibility, thus achieving comprehensive coverage without requiring the autonomous vehicle to physically navigate restricted spaces
Solution Approach 2:
The warehouse space is segmented into autonomous-accessible areas and human-accessible closed areas. The routing system divides pick tasks accordingly, assigning products in open areas to the autonomous vehicle and products in closed areas to human pickers. This segmentation allows the system to optimize for both automation efficiency and human flexibility, maintaining high overall productivity
3Ease of operation
If the picker collects products while the autonomous vehicle is stationary, then the vehicle can wait for the picker, but the overall pick time increases
Solution Approach 1:
The routing system performs preliminary calculations to predict picker completion times and proactively plans the autonomous vehicle's next actions. Instead of waiting stationarily, the system pre-calculates optimal rendezvous locations and prepares the next pick route segment, enabling the vehicle to remain productive during picker operations and significantly reducing overall pick time
Solution Approach 2:
The system ensures continuous useful action by keeping the autonomous vehicle in motion or in productive standby modes. Rather than stationary waiting, the vehicle continuously navigates to predetermined rendezvous locations, transfers products, and prepares for the next task segment, eliminating idle time and maintaining continuous productivity throughout the pick process
Data Source
AI summary
Disclosed are systems and methods for dynamically routing pickers and autonomous vehicles to avoid areas closed to travel by the autonomous vehicles within a warehouse. A processor in communication with an autonomous vehicle and an electronic device operated by a user (e.g., handheld device) may, in response to detecting that the electronic device diverges from a path of the autonomous vehicle, provide, for display on the electronic device, information about the product. The processor may then determine a rendezvous location for the autonomous vehicle based on a location of the product. The processor may then instruct the autonomous vehicle to navigate to the rendezvous location and transmit the rendezvous location to the electronic device.