Natural Language Robot Control via LLM Command Translation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing devices require manual creation of interfaces and controls for remotely controlled devices, which is time-consuming and limits user interaction, especially for complex devices that need training to understand device capabilities.
Innovation Solution
A system that uses natural language commands to control robotic devices through a large language model (LLM) that translates user requests into actionable commands and logic, converting them into low-level machine controls for execution by the robotic device, with an API module maintaining mappings between high-level and low-level commands.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If manual creation of interfaces and controls is used for remotely controlled devices, then device control functionality is achieved, but deployment time increases and user interaction flexibility is limited
Solution Approach 1:
The system enables self-service by allowing the robotic device to automatically generate its own control interface. The device publishes its capabilities and state through an API that the language model directly accesses, eliminating the need for manual interface creation. The device essentially creates and maintains its own control interface through automated capability publication and state reporting mechanisms.
Solution Approach 2:
The language model acts as an intermediary between the user and the robotic device. It receives natural language commands, translates them into appropriate API calls based on the device's published capabilities, and executes the desired actions. This intermediary layer abstracts the complexity of low-level device controls while maintaining full functionality.
2Ease of operation
If predefined controls are used for complex robotic devices, then device operation is controllable, but user training is required and ease of operation decreases
Solution Approach 1:
The patent replaces the traditional mechanical control interface (physical buttons, switches, and predefined controls) with a linguistic interface. Instead of requiring users to interact with complex mechanical control systems, the system accepts natural language commands that are processed by the language model and translated into appropriate device operations. This substitution dramatically simplifies the user interaction while maintaining full device functionality.
Solution Approach 2:
The language model provides a universal control interface that can handle multiple types of commands and device operations through a single natural language interface. Rather than requiring separate controls for different device functions, the system uses a multi-functional language-based interface that adapts to various operational needs based on the user's natural language input and the device's current state.
3Adaptability or versatility
If traditional remote control interfaces are used, then device control is achieved, but adaptability to different user preferences and scenarios is limited
Solution Approach 1:
The control interface is made dynamic by allowing it to adapt its behavior based on the device's current state and the user's needs. The language model dynamically determines the appropriate interpretation and execution of commands based on real-time context, including the device's published capabilities, current operational state, and the semantic meaning of the user's natural language input. This dynamic adaptation enables the interface to flexibly respond to different user preferences and scenarios.
Data Source
AI summary
Disclosed are systems and methods to control a robotic device using natural language commands. A natural language command may be received by a system. The system may convert the command into low-level machine controls and logic for implementation by a robotic device to achieve a desired action. In some instances, an API module may include mapping data to associate high-level commands with low-level machine controls. A language model may process the natural language command (input), high-level commands, and/or other information, such as system state, sensor observation data, parameters, etc., to determine one or more commands to execute by a robotic device and possibly logic for execution by the robotic device. The robotic device may receive the low-level machine controls and logic to cause the robotic device to perform the requested actions.