Enhanced Future Evolutions & Paradigm Shifts Technical Implementation

Publication ID: 24-11858149_0010_PTD

Published: October 29, 2025

Category:Future Evolutions & Paradigm Shifts

Legal Citation

pr1or.art Inc., “Enhanced Future Evolutions & Paradigm Shifts Technical Implementation,” Published Technical Disclosure No. 24-11858149_0010_PTD, Published October 29, 2025, available at https://archive.pr1or.art/24-11858149_0010_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 future evolutions & paradigm shifts that builds upon the source patent's technical foundation.

Background and Problem Solved

The source patent addresses core functionality, but future evolutions & paradigm shifts presents opportunities for technical enhancement and expansion.

Detailed Description of the Inventive Concept

A comprehensive technical system that implements future evolutions & paradigm shifts 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 future evolutions & paradigm shifts 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 future evolutions & paradigm shifts 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 robotic localization and navigation technologies, involving machine learning, computer vision, and spatial positioning techniques

Person of Ordinary Skill (PHOSITA) Profile

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

Obviousness Rationale

A PHOSITA would recognize that the PTD's disclosed variations represent predictable extensions of the source patent's core robotic localization methodology, applying standard machine learning and computer vision techniques to enhance spatial positioning capabilities through incremental technical improvements that would be apparent to a skilled practitioner in the field.

Obvious Combinations & Variations

Source Patent Element

Robot image obtaining method with reference images at specific points

PTD Variation

Enhanced image collection strategies incorporating multi-angle and multi-perspective reference image generation

Obviousness Reasoning

Expanding image collection techniques represents a known design optimization technique, utilizing predictable machine learning approaches to improve spatial positioning accuracy

Source Patent Element

Trained model for determining robot position and pose

PTD Variation

Advanced machine learning model architectures with improved feature extraction and pose estimation capabilities

Obviousness Reasoning

Iterative improvement of neural network architectures is a standard practice in machine learning, representing an obvious technical evolution for a skilled practitioner

Source Patent Element

Reference image sets for training robotic localization models

PTD Variation

Dynamic training data generation methods with expanded environmental context and contextual feature integration

Obviousness Reasoning

Expanding training data collection and model training techniques represents a predictable optimization approach within machine learning and computer vision domains

Source Patent Element

Rotation-based image obtaining method for robot localization

PTD Variation

Enhanced rotation strategies with improved sensor fusion and multi-modal positioning techniques

Obviousness Reasoning

Integrating additional sensing modalities and refining rotation-based positioning represents a standard engineering approach to improving robotic navigation capabilities

Source Patent Element

Global position and pose estimation using reference images

PTD Variation

Advanced probabilistic modeling and uncertainty quantification in robotic localization systems

Obviousness Reasoning

Implementing more sophisticated statistical modeling techniques represents an obvious technical progression for a PHOSITA seeking to improve positioning accuracy

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, applying standard machine learning and robotics engineering techniques to incrementally improve robotic localization methodologies through well-understood design optimizations and technical refinements.

Original Patent Information

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