Enhanced Synergistic Combinations Technical Implementation

Publication ID: 24-11858149_0003_PTD

Published: October 29, 2025

Category:Synergistic Combinations

Legal Citation

pr1or.art Inc., “Enhanced Synergistic Combinations Technical Implementation,” Published Technical Disclosure No. 24-11858149_0003_PTD, Published October 29, 2025, available at https://archive.pr1or.art/24-11858149_0003_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 synergistic combinations that builds upon the source patent's technical foundation.

Background and Problem Solved

The source patent addresses core functionality, but synergistic combinations presents opportunities for technical enhancement and expansion.

Detailed Description of the Inventive Concept

A comprehensive technical system that implements synergistic combinations 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 synergistic combinations 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 synergistic combinations 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, machine learning, and spatial positioning techniques

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 PTD's synergistic combinations represent predictable technical extensions of the source patent's robot localization framework, utilizing known machine learning and image processing techniques to enhance spatial positioning capabilities through incremental improvements in reference image processing and model training approaches.

Obvious Combinations & Variations

Source Patent Element

Training model using reference images obtained at specific points

PTD Variation

Enhanced training data collection methodology with expanded image acquisition strategies

Obviousness Reasoning

Modifying image collection protocols represents a routine design optimization that would be obvious to a PHOSITA seeking improved localization accuracy through more comprehensive training datasets

Source Patent Element

Robot rotation method for image obtaining characteristics

PTD Variation

Advanced rotation algorithms with optimized angle and directional sampling techniques

Obviousness Reasoning

Refining rotation methods to capture more comprehensive environmental data is a predictable engineering solution within the known capabilities of machine learning-based robotic navigation systems

Source Patent Element

Global position and pose determination using trained models

PTD Variation

Expanded machine learning architectures for more precise spatial positioning inference

Obviousness Reasoning

Implementing more sophisticated neural network architectures to improve localization accuracy represents an obvious technological progression for a skilled practitioner familiar with machine learning techniques

Source Patent Element

Image processing for robot environmental perception

PTD Variation

Enhanced computational approaches for multi-modal sensor fusion and contextual understanding

Obviousness Reasoning

Integrating additional sensor data and developing more complex feature extraction techniques are standard optimization strategies in robotic perception systems

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 the proposed enhancements represent predictable technological extensions of US Patent 11858149's foundational robot localization methodology, employing routine engineering techniques and known machine learning approaches to incrementally improve spatial positioning capabilities.

Original Patent Information

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