Methods and apparatus for multi-agent path finding within diagnostic laboratory systems
EP4758482A1Pending Publication Date: 2026-06-17SIEMENS HEALTHCARE DIAGNOSTICS INC
Patent Information
- Authority / Receiving Office
- EP · EP
- Patent Type
- Applications
- Current Assignee / Owner
- SIEMENS HEALTHCARE DIAGNOSTICS INC
- Filing Date
- 2024-08-07
- Publication Date
- 2026-06-17
AI Technical Summary
Technical Problem
Determining the optimal paths and timing for transporting and processing multiple sample containers in diagnostic laboratory systems while avoiding collisions and unnecessary delays is challenging.
Method used
A method and apparatus that employ multi-agent path finding (MAPF) techniques using a trained neural network to determine actions for sample carriers, considering arrival, deadline, and precedence constraints, as well as non-instantaneous goal processing times.
Benefits of technology
The solution effectively optimizes the routing and processing of sample containers, reducing congestion and delays, and ensuring that samples are processed within their scheduled time windows.
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Smart Images
Figure US2024041204_13022025_PF_FP_ABST
Abstract
In some embodiments, a method of path finding for sample containers in diagnostic laboratory systems includes receiving a batch of sample containers in a diagnostic laboratory system having diagnostic laboratory equipment; obtaining a grid for the diagnostic laboratory system, the grid having cells that include the diagnostic laboratory equipment and one or more tracks connecting the diagnostic laboratory equipment; assigning an agent to each of the sample carriers; determining, for each agent assigned to a sample carrier holding a sample container, a goal including an earliest arrival time constraint, a deadline constraint, and a goal processing time constraint; and employing a multi-agent path finding (MAPF) trained neural network to determine an action for each agent, the neural network trained with arrival, deadline, and precedence constraints and with non-instantaneous goal processing times. Numerous other aspects are provided.
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