Enhanced Specialized Variations & Niche Solutions Technical Implementation

Publication ID: 24-11858149_0004_PTD

Published: October 29, 2025

Category:Specialized Variations & Niche Solutions

Legal Citation

pr1or.art Inc., “Enhanced Specialized Variations & Niche Solutions Technical Implementation,” Published Technical Disclosure No. 24-11858149_0004_PTD, Published October 29, 2025, available at https://archive.pr1or.art/24-11858149_0004_PTD

This technical disclosure describes improvements that would be readily apparent to a Person Having Ordinary Skill In The Art (PHOSITA) when considered in combination with the foundational architecture disclosed in U.S. Patent No. 11,858,149.

Summary of the Inventive Concept

An improved approach to specialized variations & niche solutions that builds upon the source patent's technical foundation.

Background and Problem Solved

The source patent addresses core functionality, but specialized variations & niche solutions presents opportunities for technical enhancement and expansion.

Detailed Description of the Inventive Concept

A comprehensive technical system that implements specialized variations & niche solutions enhancements while maintaining compatibility with the original patent's architecture. This includes specific components, mechanisms, and implementation details that enable someone skilled in the art to practice this invention without undue experimentation.

Novelty and Inventive Step

Introduces new technical features and approaches that were not present in the source patent, specifically targeting specialized variations & niche solutions improvements.

Alternative Embodiments and Variations

Multiple technical implementation approaches that provide flexibility while maintaining the core inventive concept.

Potential Commercial Applications and Market

Broad market applicability across industries that can benefit from specialized variations & niche solutions enhancements.

CPC Classifications

Section	Class	Group
B	B25	B25J9/1697
B	B25	B25J9/1664

Section 103 Obviousness Analysis (PHOSITA)

▼

Field of Art

Robotics and Autonomous Systems, specifically robot localization and navigation technologies involving image processing and machine learning for spatial positioning

Person of Ordinary Skill (PHOSITA) Profile

A robotics engineer with expertise in computer vision, machine learning, sensor fusion, and robotic navigation systems, holding a master's or PhD in robotics, mechanical engineering, or computer science with 3-5 years of practical experience in autonomous system design

Obviousness Rationale

A PHOSITA would recognize that the published technical disclosure represents predictable variations and extensions of the source patent's core robotic localization methodology by applying standard engineering techniques of modular design, alternative implementation strategies, and incremental technical improvements that do not require inventive complexity.

Obvious Combinations & Variations

Source Patent Element

Image-based robot localization using trained machine learning models

PTD Variation

Enhanced image processing techniques with expanded reference image collection strategies

Obviousness Reasoning

Modifying reference image collection methods would be a routine design optimization for a PHOSITA seeking improved localization accuracy, representing a predictable variation within known machine learning training approaches

Source Patent Element

Rotation-based image acquisition for spatial positioning

PTD Variation

Alternative angle and orientation sampling techniques for reference image generation

Obviousness Reasoning

Adjusting image sampling angles and orientation strategies represents a standard engineering design choice that would be obvious to implement for improved spatial resolution and mapping precision

Source Patent Element

Global positioning determination through machine learning model inference

PTD Variation

Specialized niche solution implementations targeting specific robotic navigation scenarios

Obviousness Reasoning

Adapting machine learning models to specific use cases is a well-established technique in robotics, representing an expected evolutionary approach for domain-specific performance optimization

Source Patent Element

Training data generation using mapping robots or servers

PTD Variation

Enhanced data collection and model training methodologies with expanded input diversity

Obviousness Reasoning

Expanding training data collection techniques represents a standard machine learning engineering approach for improving model generalization and performance

Source Patent Element

Robot localization through image-based pose estimation

PTD Variation

Advanced pose estimation techniques incorporating additional sensor fusion strategies

Obviousness Reasoning

Integrating multiple sensor modalities for improved localization accuracy is a predictable engineering solution within autonomous robotic system design

35 U.S.C. § 103 Summary: Pursuant to 35 U.S.C. § 103, the technical variations disclosed herein would have been obvious to a person having ordinary skill in the art at the time of invention, as they represent predictable extensions of the foundational teachings in US Patent 11858149, employing standard engineering techniques to achieve incremental improvements in robotic localization methodologies without requiring non-obvious inventive complexity.

Original Patent Information

Patent Number	US 11,858,149
Title	Localization of robot
Assignee(s)	LG ELECTRONICS INC.