Virtual Lab Highlighting for Ambiguous Equipment Selection
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Solution Overview
Problem
Automation in lab environments faces challenges due to non-standardized communication languages between operators and robots, lack of operator expertise, and varying interfaces among equipment and robots, leading to difficulties in parsing protocols and increased latency.
Innovation Solution
A lab automation system that uses a graphic user interface to receive instructions, identifies ambiguous terms, and modifies the interface to include predictive text elements for equipment selection, allowing users to interactively select equipment and update instructions, thereby standardizing communication and reducing latency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automation is implemented in lab environments, then productivity is improved, but device complexity increases due to multiple interfaces and communication protocols
Solution Approach 1:
The patent implements a universal natural language interface that can communicate with multiple different equipment types and robots through a single standardized protocol. The system translates user-friendly natural language commands into equipment-specific instructions, eliminating the need for operators to learn multiple specialized interfaces while maintaining compatibility with diverse lab equipment.
Solution Approach 2:
The patent introduces a natural language processing layer as an intermediary between the user and the automated equipment. This mediator translates ambiguous natural language instructions into precise machine-executable commands, resolving the complexity of direct interface communication while preserving productivity gains from automation.
2Ease of operation
If standardized communication is implemented, then ease of operation is improved, but adaptability decreases due to rigid protocol requirements
Solution Approach 1:
The patent employs dynamic protocol adaptation where the communication interface automatically adjusts its behavior based on the target equipment type. The system maintains a standardized natural language input interface for ease of use while dynamically generating equipment-specific command protocols, thus achieving both user-friendliness and adaptability to diverse equipment.
Solution Approach 2:
The system changes communication parameters dynamically based on the equipment being controlled. The natural language interface maintains consistent syntax and semantics for users, while the underlying translation layer adjusts protocol parameters to match the specific requirements of different robots and equipment, preserving both ease of operation and adaptability.
3Ease of operation
If predictive text interface elements are added, then ease of operation is improved, but device complexity increases
Solution Approach 1:
The patent implements predictive text functionality that proactively suggests relevant equipment and parameters based on the context of the natural language instruction. By performing preliminary analysis of the user's intent and providing anticipatory suggestions, the system reduces the cognitive load on operators and simplifies equipment selection without requiring a fundamentally more complex interface architecture.
Solution Approach 2:
The predictive text interface incorporates feedback mechanisms where the system analyzes user input in real-time and provides contextual suggestions based on previously selected equipment and protocol parameters. This feedback loop refines the interface interaction by learning from user choices, improving ease of operation while managing complexity through intelligent rather than structural enhancements.
Data Source
AI summary
A lab automation system receives an instruction from a user to perform a protocol within a lab via an interface including a graphical representation of the lab. The lab includes a robot and set of equipment rendered within the graphical representation of the lab. The lab automation system identifies an ambiguous term of the instruction and pieces of equipment corresponding to the ambiguous term and modifies the interface to include a predictive text interface element listing the pieces of equipment. Upon a mouseover of a listed piece of equipment within the predictive text interface element, the lab automation system modifies the graphical representation of the lab to highlight the listed piece of equipment corresponding to the mouseover. Upon a selection of the listed piece of equipment within the predictive text interface element, the lab automation system modifies the instruction to include the listed piece of equipment.