Enhanced New Applications & Use Cases Technical Implementation

Publication ID: 24-11858149_0007_PTD

Published: October 29, 2025

Category:New Applications & Use Cases

Legal Citation

pr1or.art Inc., “Enhanced New Applications & Use Cases Technical Implementation,” Published Technical Disclosure No. 24-11858149_0007_PTD, Published October 29, 2025, available at https://archive.pr1or.art/24-11858149_0007_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 new applications & use cases that builds upon the source patent's technical foundation.

Background and Problem Solved

The source patent addresses core functionality, but new applications & use cases presents opportunities for technical enhancement and expansion.

Detailed Description of the Inventive Concept

A comprehensive technical system that implements new applications & use cases 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 new applications & use cases 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 new applications & use cases enhancements.

CPC Classifications

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

Section 103 Obviousness Analysis (PHOSITA)

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Field of Art

Robotics and Autonomous Systems, specifically focusing on robot localization, navigation, and image-based positioning technologies with expertise in machine learning, computer vision, and robotic sensing systems

Person of Ordinary Skill (PHOSITA) Profile

A robotics engineer with advanced degree in robotics/computer science, proficient in machine learning models, image processing techniques, robotic navigation algorithms, and familiar with state-of-the-art robotic localization methodologies

Obviousness Rationale

A PHOSITA would recognize that the PTD's disclosed variations represent predictable extensions of the source patent's core localization framework by introducing incremental technical improvements that leverage known machine learning and image processing techniques. The variations demonstrate standard engineering problem-solving approaches that build upon existing robotic navigation methodologies. The technical solutions proposed are consistent with established practices in autonomous robotic system design and would be considered routine optimization strategies.

Obvious Combinations & Variations

Source Patent Element

Image-based robot localization using trained machine learning models

PTD Variation

Enhanced machine learning model architectures with expanded training data sets and multi-modal image processing techniques

Obviousness Reasoning

Expanding machine learning model complexity is a predictable design choice for improving localization accuracy, representing a known technique in computer vision and robotics

Source Patent Element

Reference image collection for robot positioning

PTD Variation

Dynamic reference image generation with augmented data collection strategies

Obviousness Reasoning

Introducing more sophisticated image collection methods is an obvious optimization approach that a skilled practitioner would recognize as improving system performance

Source Patent Element

Rotation-based image acquisition method

PTD Variation

Advanced rotation strategies incorporating multi-angle image capture and enhanced spatial mapping techniques

Obviousness Reasoning

Refining rotation methods to improve spatial understanding represents a standard engineering approach with predictable incremental improvements

Source Patent Element

Global positioning determination using machine learning

PTD Variation

Probabilistic positioning models with enhanced uncertainty quantification and contextual adaptation

Obviousness Reasoning

Introducing probabilistic modeling techniques is a known approach for improving machine learning-based localization systems

Source Patent Element

Robot environment image processing

PTD Variation

Expanded environmental feature extraction with semantic segmentation and advanced computer vision techniques

Obviousness Reasoning

Implementing more sophisticated computer vision techniques represents a predictable evolution of existing image processing methodologies

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, with reasonable expectation of success, based on the foundational teachings of US Patent 11858149. The proposed technical implementations represent routine engineering optimization and predictable combinations of known robotic localization techniques, thereby rendering potential derivative claims obvious and unpatentable.

Original Patent Information

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