Autonomous Body Task Order Pre-calculation for Warehouse Path Planning
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Solution Overview
Problem
Current techniques for optimizing operations in warehouses with autonomous bodies lead to inefficient path planning and increased calculation time due to dynamic task additions, as they do not pre-calculate optimal paths for multiple via-points, resulting in suboptimal operation orders and prolonged calculation times.
Innovation Solution
A design execution apparatus that includes an input unit for task group and environmental information, a determining unit to calculate and store the optimal order for task execution, and a memory unit to store this order information, allowing for efficient task assignment and path planning by reusing past calculations to speed up path searching.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If path optimization is performed every time a task is added, then the operation order can be optimized, but the calculation time increases significantly
Solution Approach 1:
The system pre-calculates and stores optimal paths for multiple via-points (task locations) in advance before tasks are added. When a task is added, the system retrieves previously calculated path information and combines it with new task requirements, rather than recalculating all paths from scratch. This preliminary action significantly reduces the calculation time for dynamic task additions while maintaining optimization quality.
2Productivity
If the autonomous body is assigned tasks immediately upon addition, then task execution can begin quickly, but the operation order may not be optimal
Solution Approach 1:
The system pre-calculates optimal execution orders for groups of tasks (task groups) in advance and stores them. When tasks are added dynamically, the system determines whether the new tasks form a complete task group that matches pre-calculated configurations. If so, the pre-determined optimal execution order is applied immediately, achieving both fast task assignment and optimal operation sequencing.
3Measurement precision
If all paths are recalculated for every new task, then the most optimal path can be found, but the searching time becomes unacceptably long
Solution Approach 1:
The system performs preliminary path calculations for all possible via-points (task locations) in advance and stores these optimal path segments. When a new task is added, the system combines pre-calculated path segments rather than recalculating entire paths. This approach maintains high path optimization accuracy while dramatically reducing the searching time for dynamic task additions.
Solution Approach 2:
The system divides the overall path planning problem into smaller segments corresponding to individual task locations (via-points). Each via-point's optimal path is calculated and stored independently in advance. When multiple tasks are executed, the system segments the total path into individual via-point paths and combines them, reducing the computational complexity from calculating one large optimal path to combining multiple pre-calculated smaller paths.
Data Source
AI summary
A design execution apparatus includes: an input unit that inputs task group information indicating a task group including one or more tasks to be executed by an autonomous body and environmental information indicating an environment in which the task is executed; a determining unit that determines an order in which the autonomous body executes tasks included in a task group indicated by the task group information, based on the task group information and the environmental information that are input by the input unit; and a memory unit that stores order information indicating the order determined by the determining unit.