Robotic Workflow Scheduling for Multi-Device Laboratory Automation
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Solution Overview
Problem
Existing approaches to automating laboratory tasks and experiments with robotic equipment are limited in scalability, throughput, and flexibility, particularly in handling multiple robotic devices and dynamic workflows, and struggle with complex liquid handling and sensitive material management in life sciences applications.
Innovation Solution
A system and method for integrating and scheduling multiple robotic devices to perform complex workflows, allowing users to define and configure equipment and operations, with an interface for easy setup and monitoring, enabling dynamic path resolution and prioritization, and supporting diverse applications including life sciences and industrial processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If existing approaches are used to automate laboratory tasks with robotic equipment, then automation of single workcell or single robot is achieved, but scalability is limited and setup process becomes difficult when integrating multiple robotic devices
Solution Approach 1:
The system segments the complex workflow into discrete tasks that can be independently scheduled and executed by different robotic devices. Each task is defined with specific parameters including required equipment, duration, and dependencies, allowing the system to manage multiple robotic devices through modular task decomposition rather than treating the entire workflow as a monolithic complex process
Solution Approach 2:
The scheduling system implements a universal task management framework that can handle diverse robotic devices and workflow types through a common interface. The system uses standardized task definitions and equipment abstraction layers that allow different robotic devices to be integrated and managed uniformly, eliminating the need for device-specific integration approaches
2Productivity
If existing approaches are used for robotic workflow automation, then single path execution is implemented, but throughput is limited and dynamic reprioritization is not supported
Solution Approach 1:
The system implements dynamic scheduling that continuously monitors task progress, equipment availability, and workflow dependencies to automatically reprioritize and reassign tasks in real-time. The scheduler can dynamically adjust execution paths based on changing conditions such as equipment failures, task completion rates, and new incoming tasks, enabling adaptive throughput optimization without fixed predetermined paths
Solution Approach 2:
The system maintains continuous workflow execution by implementing intelligent task buffering and parallel processing capabilities. When bottlenecks are detected in the workflow, the scheduler automatically redistributes tasks to available equipment and maintains continuous operation of all robotic devices, ensuring that useful action continues uninterrupted across the entire system rather than halting for synchronization
3Reliability
If existing approaches are used for robotic equipment automation, then basic task execution is achieved, but monitoring and oversight require extensive human involvement increasing walk-away times
Solution Approach 1:
The system implements comprehensive automated monitoring with real-time feedback loops that track task progress, equipment status, and workflow compliance. The monitoring system continuously compares actual execution against planned parameters and automatically triggers corrective actions or alerts when deviations are detected, providing reliable oversight without requiring continuous human presence or manual intervention
4Adaptability or versatility
If existing approaches are used for workflow automation, then simple tasks can be automated, but complex liquid handling and sensitive material management in life sciences applications remain difficult
Solution Approach 1:
The system introduces a sophisticated task management intermediary layer that handles the complexity of liquid handling protocols and sensitive material management. This intermediary software layer translates high-level workflow definitions into device-specific commands, manages liquid handling parameters such as volumes and speeds, tracks sensitive materials through the workflow, and ensures compliance with protocol requirements, shielding users from the underlying device complexity while enabling complex operations
Data Source
AI summary
An approach for fully automating the use of robotic devices in a laboratory workflow includes defining sequences for automating tasks and equipment involved in such a workflow, and calculating a path for each sequence that resolves get, handoff, and placement procedures. The approach develops a schedule that executes resolved pathways in and between each device. The approach is provided with an easy-to-use interface, in which a user drags and drops devices to automatically configure them, defines operations to be performed by these devices, and then runs the laboratory workflow. The interface also provides the ability to monitor progress of the workflow, and make modifications and adjustments as needed.