Mobile Robot User Interface for Task Selection
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Solution Overview
Problem
It is challenging for individuals without specialized robotics training to write or compile command data for robotic devices, as this requires complex vectors and matrices, which can be time-consuming and expensive to learn.
Innovation Solution
A mobile robot equipped with a user interface that presents task information visually, audibly, and tactiley, allowing users to select tasks without needing extensive training, and autonomously performs these tasks using a combination of sensors, manipulator systems, and a controller that processes user inputs to execute commands.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If command data is provided using complex vectors and matrices, then the robotic device can perform tasks with high precision and control capability, but it becomes difficult for individuals without specialized training to write or compile the command data
Solution Approach 1:
The patent introduces a natural language processing intermediary that translates between simple human language commands and the complex vector/matrix representations required by the robotic system. This mediator layer allows users to interact using everyday language while the system internally processes the sophisticated mathematical structures needed for precise control.
Solution Approach 2:
The system creates simplified copies or abstractions of the complex command data structures that are presentable to users. Instead of showing users raw vectors and matrices, the system generates user-friendly representations such as natural language descriptions or simplified parameters that map to the underlying complex structures.
2Reliability
If specialized robotics training is required to operate the robotic device, then the device can be controlled with high precision, but the training process becomes time-consuming and expensive
Solution Approach 1:
The robotic system provides self-service through automated natural language processing that eliminates the need for specialized training. The system automatically interprets user commands, translates them into appropriate control signals, and executes tasks without requiring users to learn complex robotics concepts or programming.
Solution Approach 2:
The patent replaces the mechanical training system (formal education, practice, and skill development) with an information processing system based on natural language understanding. Instead of requiring users to mechanically learn control protocols and system operations, the system uses AI-driven language processing to automatically interpret and execute user intent.
3Manufacturing precision
If specialized robotics training is required, then proper command compilation is achieved, but the training cost becomes expensive
Solution Approach 1:
The natural language processing intermediary serves as a cost-effective mediator that automatically ensures command data accuracy without requiring expensive specialized training. The AI system handles the complex translation and validation processes that would otherwise require trained professionals, thereby maintaining precision while reducing costs.
Solution Approach 2:
The system performs self-validation and self-correction of command data through automated natural language processing, eliminating the need for expensive human expertise. The AI system independently ensures command accuracy by interpreting user intent and generating appropriate control signals without external intervention or specialized knowledge.
Data Source
AI summary
Mobile robots and methods involving mobile robots are provided. One of the mobile robots electronically presents information using a user interface, where the information is indicative of at least one task. The user interface, for example, may present the information in a visual form with a display screen. The user interface receives a selection of the task. The mobile robot thereafter autonomously performs at least a portion of the selected task.