3D Object Selection Workflow for Repeated Task Initiation
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Solution Overview
Problem
Existing systems struggle to efficiently and accurately initiate tasks based on user-selected objects in three-dimensional scenes without requiring redundant user inputs or natural language commands.
Innovation Solution
A computer system that concurrently detects natural language input and object selection, allowing it to initiate tasks based on the first object, and subsequently, upon meeting certain criteria, continues the task on a second object without additional natural language input.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the system requires natural language input for each task initiation, then task initiation accuracy is improved, but user interaction efficiency deteriorates due to redundant inputs
Solution Approach 1:
The system performs preliminary action by detecting and storing the user's initial natural language task request, then maintains a state where subsequent object selections can automatically trigger the task without requiring repeated natural language commands. This allows the system to prepare for task execution in advance and respond efficiently to object selections.
Solution Approach 2:
The system implements continuity of useful action by maintaining an active state after the initial natural language input, where the system continuously monitors for object selections and can immediately execute the requested task when an object is selected. This eliminates the need to repeatedly require natural language commands for each object interaction.
2Adaptability or versatility
If the system monitors multiple input types concurrently, then user interaction versatility is improved, but system complexity increases
Solution Approach 1:
The system applies universality by designing a unified input processing architecture that can handle multiple input types (natural language, object selections, gestures) through a common framework. The same system components process different input modalities, reducing the need for separate specialized processing paths for each input type.
Solution Approach 2:
The system implements self-service through automatic input type detection and routing, where the system autonomously determines which input modality the user is employing and processes it appropriately without requiring additional configuration or complex decision logic from the user.
3Measurement precision
If the system requires additional natural language input for each object change, then task specificity is improved, but power consumption increases
Solution Approach 1:
The system performs preliminary action by capturing the complete task specification in the initial natural language input, including the action to be performed. Subsequent object selections then simply parameterize this pre-defined task rather than requiring re-specification, reducing the computational energy needed for repeated natural language processing.
Solution Approach 2:
The system maintains continuous task context after the initial natural language input, keeping the task specification in an active state that can be applied to multiple objects. This continuity eliminates the need for repeated natural language processing cycles, which are energy-intensive, while maintaining task specificity through the preserved context.
Data Source
AI summary
An example process includes: concurrently detecting: a first natural language input that requests to perform a first task and a first input that corresponds to a selection of a first object; in response to concurrently detecting the first natural language input and the first input, initiating the first task based on the first object; and after initiating the first task based on the first object: detecting a second input corresponding to a selection of a second object different from the first object; and in response to detecting the second input corresponding to the selection of the second object: in accordance with a determination that the second input satisfies a set of input criteria, initiating, without receiving a natural language input after detecting the first natural language input, the first task based on the second object.