Warehouse Robot Scheduling for Idle Zone Path Control
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current robot scheduling methods in warehouses require manual intervention to turn robots on and off, leading to increased operational and maintenance costs and reduced efficiency, as they need to be manually scheduled for maintenance and to prevent interference with warehouse infrastructure.
Innovation Solution
A robot scheduling method that determines the working state and current position of robots, scheduling them into a preset target range when idle and outside that range, using a server to automatically direct them to idle areas closer to workstations, ensuring minimal disruption to other robots.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual scheduling method is used to turn robots on and off and schedule them to designated positions, then robots can be controlled to be in specific positions, but the usage cost increases and work efficiency of staff decreases
Solution Approach 1:
The robot scheduling system performs self-service by automatically collecting information about idle robots, determining their positions, and scheduling them to target ranges without human intervention. The server autonomously manages the entire scheduling process, including identifying robots that need to be turned off, calculating optimal paths, and directing them to maintenance areas, thereby eliminating manual scheduling operations and improving staff efficiency.
Solution Approach 2:
The patent replaces the mechanical manual scheduling system with an automated information processing system. Instead of staff manually selecting and scheduling robots through control terminals, the system uses automated information collection, analysis, and decision-making processes to schedule robots, substituting human operations with automated computational methods.
2Reliability
If manual scheduling is performed before maintenance to prevent robot interference with maintenance activities, then maintenance can be conducted smoothly, but operation and maintenance cost increases
Solution Approach 1:
The system performs preliminary actions by proactively scheduling robots to target ranges before maintenance activities begin. The server continuously monitors robot positions and proactively directs idle robots away from areas that will undergo maintenance, preventing potential interference before it occurs and ensuring smooth maintenance operations without requiring reactive manual intervention.
Solution Approach 2:
The scheduling system uses feedback mechanisms by continuously collecting information about robot positions, maintenance schedules, and warehouse operations. This feedback loop enables the server to dynamically adjust robot scheduling decisions, ensuring robots are directed away from maintenance areas while optimizing overall system efficiency and reducing operational costs.
3Adaptability or versatility
If robots are randomly distributed in the warehouse, then they can operate freely, but scheduling them for maintenance and shutdown becomes complex and costly
Solution Approach 1:
The server implements a universal scheduling mechanism that handles multiple robot types and operations through a single automated system. The system universally collects information from all robots, determines their states, and applies consistent scheduling rules regardless of robot type or current task, simplifying the management of randomly distributed robots while maintaining their operational freedom.
Data Source
Figure 1~2
Figure 3
Figure 4~5
AI summary
The present application discloses robot scheduling, robot path control and robot fire control methods and devices, a server and a storage medium. The robot scheduling method includes: receiving a scheduling instruction; determining a working state and a current position of a robot in a working area in response to the scheduling instruction; wherein the working state comprises an idle state and a non-idle state; and when the working state of the robot is idle and the current position is outside a preset target range, scheduling the robot from the current position into the target range.