AR Robot Programming via Speech and Motion Code Generation
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Solution Overview
Problem
Programming a robot to perform tasks is a resource-intensive process requiring specialized skills and time, as users must write and test code, which can be tedious and consume significant resources.
Innovation Solution
A code generation system using augmented reality (AR) and artificial intelligence (AI) that processes speech and video data to generate executable code for robots, allowing users to manipulate virtual robots and generate code for real robots to perform actions through natural language processing and pseudocode transformation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If traditional robot programming methods are used, then robots can perform tasks, but the process requires specialized skills and consumes significant time and resources
Solution Approach 1:
The system creates a virtual robot that copies the physical robot's appearance and behaviors. Users program the virtual robot through natural language interactions, and the code generated from the virtual robot automatically programs the physical robot, eliminating the need for specialized programming skills and reducing programming time significantly
Solution Approach 2:
The virtual robot serves as an intermediary between the user and the physical robot. Instead of users directly programming the physical robot, they interact with the virtual robot using natural language, which then translates into executable code for the physical robot, simplifying the programming process
2Productivity
If traditional robot programming methods are used, then robots can perform tasks, but the process is tedious and resource-intensive
Solution Approach 1:
The system performs preliminary actions by capturing video data of the physical robot and generating a virtual robot model in advance. Natural language processing models and pseudocode generation models are pre-trained and ready, enabling rapid code generation when users need to program tasks, thus improving productivity while managing computational resources efficiently
Solution Approach 2:
The system replaces traditional manual coding mechanics with automated natural language processing and pseudocode generation. Instead of users manually writing and debugging code, the system automatically generates executable code from natural language descriptions, dramatically increasing code generation speed and reducing resource consumption
Data Source
AI summary
A device may receive, from an augmented reality device, speech data identifying augmented reality interactions with an augmented reality robot. The device may receive, from a camera, video data identifying movements of a real robot based on the augmented reality interactions with the augmented reality robot. The device may process the speech data to obtain first action data identifying first actions that the real robot is to perform. The device may process the video data to obtain second action data identifying second actions that the real robot is to perform. The device may process the first action data and the second action data to generate pseudocode. The device may transform the pseudocode into code. The device may cause the real robot to execute the code, wherein executing the code causes the real robot to perform the first actions and the second actions.