Robot Programming via Natural Language and Multimodal Teaching
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Solution Overview
Problem
Conventional robot programming requires specialized knowledge and expertise, making it difficult and costly for non-experts to reconfigure robots frequently needed in applications like collaborative robots in small workshops, medical labs, and restaurants, where intuitive and accessible programming is necessary to reduce costs and simplify reconfiguration.
Innovation Solution
A system that enables intuitive robot programming using multiple communication channels such as speech, vision, touch, and augmented reality, translating generic operator inputs into software commands, allowing non-experts to teach robots tasks through natural interaction and providing immediate feedback, thereby simplifying the programming process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional robot programming languages and methods are used, then the robot can be programmed with precise control over its movements and operations, but the programming becomes complex and requires specialized expert knowledge
Solution Approach 1:
The patent introduces an intermediary system consisting of sensors, processors, and communication modules that translate natural language instructions into robot-executable commands. This intermediary layer shields the user from complex programming syntax while maintaining precise robot control, resolving the contradiction between programming precision and ease of operation
Solution Approach 2:
The patent replaces traditional mechanical programming interfaces (buttons, switches, manual teaching pendants) with voice-based and gesture-based control systems. This substitution allows users to program robots using natural human communication methods rather than specialized mechanical interfaces, significantly improving ease of operation while maintaining control precision
2Reliability
If expert robot engineers are employed to program robots, then the robot programming can be done accurately and reliably, but the cost increases significantly
Solution Approach 1:
The patent enables robots to be programmed by non-expert users through intuitive natural language interfaces and automated sensor-based system configuration. The system automatically translates user instructions into reliable robot commands, eliminating the need for expensive expert engineers while maintaining programming reliability through automated validation and error checking
Solution Approach 2:
The patent creates a universal programming interface that works across different robot types and applications through standardized natural language processing. This multi-functional system can handle various programming tasks without requiring specialized training for each application, reducing costs while maintaining reliability through consistent processing
3Adaptability or versatility
If robots are frequently reconfigured for different tasks, then the system becomes adaptable to various applications, but the time and cost for reprogramming increases
Solution Approach 1:
The patent implements preliminary action by pre-configuring the robot system with sensors, communication modules, and translation algorithms that are ready to rapidly process new instructions. The system maintains pre-compiled libraries of common tasks and movements that can be quickly adapted through natural language modification, enabling fast reconfiguration without time-consuming reprogramming
Solution Approach 2:
The patent creates a dynamic programming system where the robot can continuously receive and process new natural language instructions in real-time. The system dynamically adapts to new tasks through ongoing natural language processing and automated command generation, allowing frequent reconfiguration without fixed reprogramming cycles
Data Source
AI summary
A method and system are provided for programming robots by operators without expertise in specialized robot programming languages. In the method, inputs are received from the operator generically describing a desired robot movement. The system then uses the operator inputs to translate the desired robot movement into software commands that direct the robot to perform the desired robot movement. The robot may then be programmed with the software commands and operated to perform the desired robot movement.