Natural Interface Robot Control via Speech and Gesture Recognition
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Solution Overview
Problem
Conventional methods for controlling unmanned robots in inspection tasks require extensive training for human operators due to the use of traditional screen-based menus and buttons, which is time-consuming and inefficient.
Innovation Solution
A system that integrates natural interfaces such as speech and gesture recognition, allowing human operators to guide robots using probabilistic decision-making to switch between tasks, reducing the need for extensive training and improving user experience and system extensibility.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional screen-based menus and buttons are used to control the robot, then the control system is reliable and structured, but the training time for operators increases significantly
Solution Approach 1:
The patent replaces traditional mechanical screen-based menu navigation with a voice-based control system. Operators speak natural language commands which are processed by speech recognition algorithms, eliminating the need for manual menu navigation and significantly reducing training requirements while maintaining control reliability through structured command parsing
Solution Approach 2:
The patent introduces a natural language processing intermediary layer between the operator and the robot control system. This intermediary translates spoken commands into structured control signals, bridging the gap between human natural communication and machine execution while reducing the cognitive load and training time for operators
2Ease of operation
If natural interfaces like speech and gesture recognition are integrated, then the ease of operation improves significantly, but the device complexity increases
Solution Approach 1:
The patent implements a unified natural interface system that handles multiple input modalities (speech recognition, gesture recognition) through a single integrated architecture. This multi-functional approach allows the system to process different types of natural inputs using common processing pipelines, reducing the effective complexity compared to implementing separate systems for each input type
Solution Approach 2:
The patent divides the natural interface processing into distinct modular components: speech recognition module, gesture recognition module, and command interpretation module. Each module handles specific tasks independently, making the overall complex system more manageable through functional segmentation while maintaining ease of operation
3Productivity
If multiple channels of information are combined into one decision-making channel, then the productivity of task execution improves, but the difficulty of detecting and measuring increases
Solution Approach 1:
The patent implements feedback mechanisms where the system confirms recognized commands to operators and provides status updates on robot execution. This feedback loop allows operators to verify that their natural language inputs were correctly interpreted, reducing the perceived complexity while maintaining high productivity through efficient multi-channel processing
Data Source
AI summary
The example embodiments are directed to a system and method for controlling and commanding an unmanned robot using natural interfaces. In one example, the method includes receiving a plurality of sensory inputs from a user via one or more natural interfaces, wherein each sensory input is associated with an intention of the user for an unmanned robot to perform a task, processing each of the plurality of sensory inputs using a plurality of channels of processing to produce a first recognition result and a second recognition result, combining the first recognition result and the second recognition result to determine a recognized command, and generating a task plan assignable to the unmanned robot based on the recognized command and predefined control primitives.