Robot Task Teaching via Voice and Gesture Inquiry Control
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Solution Overview
Problem
Current robot teaching systems require users to operate complex interfaces and spend significant time becoming proficient, leading to increased user operation burden and costs due to the need for specialized user interfaces and machine-centric teaching methods.
Innovation Solution
A robot control system that generates inquiries to users while executing tasks, identifies user actions using sensors like cameras and microphones, and complements task execution based on these actions, allowing for intuitive and abstract human-centric teaching without the need for specialized input devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If traditional robot teaching systems use complex user interfaces and machine-centric teaching methods, then the robot can execute tasks with precision, but the user operation burden increases and users need significant time to become proficient
Solution Approach 1:
The patent replaces traditional mechanical input devices (buttons, switches, joysticks) with voice recognition and gesture recognition systems. The voice recognition unit captures and processes spoken commands, while the gesture recognition unit detects hand movements via camera, substituting physical interface interactions with natural human communication methods.
Solution Approach 2:
The patent introduces an image processing unit and voice recognition unit as intermediary components between the user and the robot controller. These intermediaries translate natural human inputs (gestures, speech) into robot control commands, bridging the gap between human-centric expression and machine execution without requiring users to learn complex interface operations.
2Manufacturing precision
If traditional robot teaching systems require specialized user interfaces, then the robot can be controlled accurately, but the system structure becomes complex and development costs increase
Solution Approach 1:
The patent makes the robot controller multi-functional by integrating voice recognition, gesture recognition, and document image processing capabilities into a single device. The robot controller serves both as the traditional control unit and as an interface for natural human interaction, eliminating the need for separate specialized input devices and reducing overall system complexity.
Solution Approach 2:
The patent merges the functions of the voice recognition unit, gesture recognition unit, and document image processing unit with the robot controller into an integrated system. This consolidation combines multiple interface functions into a single control device, simplifying the system structure while maintaining accurate control capabilities.
3Productivity
If traditional robot teaching methods use specialized input devices, then the robot can be taught tasks effectively, but the development costs increase
Solution Approach 1:
The patent enables the robot teaching system to use readily available consumer technology (smartphones, cameras, microphones) for input functions. The document image processing uses the robot's or user's existing camera, and voice recognition uses built-in microphones, allowing the system to leverage existing hardware resources rather than requiring specialized expensive input devices.
Data Source
AI summary
A robot control system includes processing circuitry that generates an inquiry for a user while a robot is executing a task, identifies an action of the user in response to the inquiry using a sensor, complements at least part of the task based on the identified action, and controls the robot such that the robot executes the complemented at least part of the task.