Published Technical Disclosure Archive

Enhanced Synergistic Combinations Technical Implementation

Publication ID: 24-11858143_0003_PTD
Published: October 29, 2025
Category:Synergistic Combinations

Legal Citation

pr1or.art Inc., “Enhanced Synergistic Combinations Technical Implementation,” Published Technical Disclosure No. 24-11858143_0003_PTD, Published October 29, 2025, available at https://archive.pr1or.art/24-11858143_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. 11,858,143.

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

SectionClassGroup
B B25 B25J9/1664
B B25 B25J9/1697
G G05 G05D1/0088
G G06 G06F18/2113
G G06 G06F18/22
G G06 G06N3/04
G G06 G06V20/10

Field of Art

Autonomous robotics, computer vision, neural network-based identification systems, with expertise in machine learning, image processing, and mobile device technologies

Person of Ordinary Skill (PHOSITA) Profile

A skilled practitioner with advanced degrees in computer science or robotics engineering, proficient in neural network architectures, image recognition algorithms, and autonomous system design, with 3-5 years of industry experience in machine learning and computer vision applications

Obviousness Rationale

A person skilled in the art would recognize that the published technical disclosure represents predictable variations of the source patent's core autonomous mobile device identification system. The PTD's synergistic combinations approach directly builds upon the existing neural network and image processing framework, applying standard engineering techniques to extend the original patent's functionality. These modifications represent incremental improvements that would be apparent to a skilled practitioner familiar with machine learning and autonomous system design.

Obvious Combinations & Variations

Source Patent Element
Neural network with convolution and attention modules for image-based user identification
PTD Variation
Enhanced neural network architecture with additional attention mechanisms and expanded feature vector processing
Obviousness Reasoning
Modifying neural network architectures by adding or refining attention modules is a known technique in machine learning, representing a predictable optimization approach for improving image recognition accuracy
Source Patent Element
Autonomous mobile device with camera-based image acquisition and user tracking
PTD Variation
Extended system for multi-modal identification incorporating additional sensor inputs and contextual analysis
Obviousness Reasoning
Integrating multiple sensor inputs and expanding contextual analysis represents a standard design choice for improving autonomous system performance, using well-established machine learning techniques
Source Patent Element
Image-based feature vector generation for user identification
PTD Variation
Advanced feature extraction techniques with improved spatial and temporal correlation analysis
Obviousness Reasoning
Refining feature extraction methods through enhanced correlation techniques is a predictable evolution in computer vision and machine learning, representing an obvious optimization to existing identification approaches
Source Patent Element
Orientation estimation and gallery data management for user tracking
PTD Variation
Improved orientation estimation with dynamic gallery data adaptation and machine learning-driven refinement
Obviousness Reasoning
Implementing dynamic adaptation and machine learning refinement for tracking systems represents a standard engineering approach for improving autonomous device performance
Source Patent Element
Neural network-based image processing for user identification
PTD Variation
Extended neural network architectures with enhanced multi-modal fusion and contextual understanding
Obviousness Reasoning
Developing more sophisticated neural network approaches for multi-modal fusion is a predictable progression in machine learning, representing an obvious technical extension of existing identification technologies
35 U.S.C. § 103 Summary: Based on the comprehensive analysis of US Patent 11858143 and the published technical disclosure, a person having ordinary skill in the art would find the claimed variations obvious and anticipated, as the disclosed synergistic combinations represent predictable extensions of existing autonomous mobile device identification technologies through standard engineering optimization techniques.

Original Patent Information

Patent NumberUS 11,858,143
TitleSystem for identifying a user with an autonomous mobile device
Assignee(s)Amazon Technologies, Inc.