Robot Motion Guidance for Ambiguous Natural Language Tasks
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Solution Overview
Problem
Conventional robots struggle with accurately performing complex tasks due to ambiguity in verbal instructions and require additional task-specific guidance.
Innovation Solution
A robotic system that analyzes natural language commands, categorizes actions as requiring guidance, receives motion guidance from users, and stores these motions in correlation with the commands, enabling it to perform tasks efficiently and accurately.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional robots perform tasks based on verbal instructions, then they can execute simple commands, but they fail to accurately perform complex tasks due to ambiguity in verbal instructions
Solution Approach 1:
The patent introduces an intermediary guidance system between the robot and complex tasks. When a natural language command is categorized as requiring guidance, the system solicits and stores detailed motion guidance from operators. This intermediary layer resolves the contradiction by providing the robot with specific, unambiguous motion instructions for complex tasks while maintaining natural language interface for simple commands.
Solution Approach 2:
The system performs preliminary action by storing motion guidance in advance for future task execution. During the training phase, the robot receives and stores detailed motion guidance associated with natural language commands. This preliminary storage of guidance information enables the robot to accurately execute complex tasks without requiring real-time interpretation of ambiguous verbal instructions.
2Reliability
If robots require task-specific guidance for complex tasks, then they can perform those tasks accurately, but the system complexity increases due to additional guidance requirements
Solution Approach 1:
The patent implements a universal guidance system that handles both simple and complex tasks through a single integrated framework. The controller categorizes natural language commands and automatically determines whether guidance is needed, making the guidance system multi-functional. This resolves the contradiction by providing a unified interface that adapts to different task complexities without requiring separate systems.
Solution Approach 2:
The system performs self-service by automatically categorizing commands and determining when guidance is required. The controller autonomously identifies which natural language commands need additional motion guidance and manages the guidance collection and storage process without external intervention, reducing the perceived complexity for users.
3Ease of operation
If robots use natural language commands for task specification, then ease of operation improves, but measurement precision deteriorates due to ambiguity in verbal instructions
Solution Approach 1:
The patent segments the command interpretation process into two distinct phases: natural language processing for intent recognition, and motion guidance specification for precise execution. This segmentation allows users to provide simple natural language commands while the system separately collects detailed motion guidance, thereby maintaining both ease of operation and measurement precision.
Solution Approach 2:
The system introduces motion guidance as an intermediary between the natural language command and the robot's execution. This intermediary layer captures the precision needed for accurate task performance while allowing the user to interact through simple natural language, resolving the contradiction between ease of operation and instruction precision.
Data Source
AI summary
A robotic system is contemplated. The robotic system comprises a robot comprising a camera, a microphone, memory, and a controller that is configured to receive a natural language command for performing an action within a real world environment, parse the natural language command, categorize the action as being associated with guidance for performing the action, receive the guidance for performing the action, the guidance including a motion applied to at least one portion of the robot within the real world environment for performing the action, and store, in the memory, the natural language command in correlation with the motion that is applied to the at least one portion of the robot.