Published Technical Disclosure Archive

Enhanced Synergistic Combinations Technical Implementation

Publication ID: 24-11858118_0008_PTD
Published: October 29, 2025
Category:Synergistic Combinations

Legal Citation

pr1or.art Inc., “Enhanced Synergistic Combinations Technical Implementation,” Published Technical Disclosure No. 24-11858118_0008_PTD, Published October 29, 2025, available at https://archive.pr1or.art/24-11858118_0008_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. 11,858,118.

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 B25J11/001
G G06 G06N20/00
G G06 G06V40/176
G G09 G09B5/065
G G10 G10L25/63

Field of Art

Robotics, Artificial Intelligence, Human-Machine Interaction, with specific focus on educational companion robots and interactive learning systems. Requires expertise in machine learning, sensor integration, emotion recognition, and adaptive interaction technologies

Person of Ordinary Skill (PHOSITA) Profile

A skilled practitioner with advanced degree in robotics, computer science, or cognitive engineering. Possesses deep understanding of AI interaction models, sensor data processing, machine learning algorithms, and human-robot interaction design principles

Obviousness Rationale

A PHOSITA would recognize that the PTD's synergistic combinations represent predictable technical extensions of the source patent's core robot interaction methodology. The disclosed enhancements leverage known techniques in AI system design to incrementally improve robotic interaction capabilities. These variations represent logical combinations of existing technological approaches within the established framework of companion robot technologies.

Obvious Combinations & Variations

Source Patent Element
Detecting and collecting sensing information and emotion information during human-machine interaction
PTD Variation
Enhanced data collection mechanisms with expanded sensor integration and multi-modal emotion recognition techniques
Obviousness Reasoning
Expanding sensor types and emotion detection methods would be an obvious design optimization for a PHOSITA seeking improved interaction fidelity. Known machine learning techniques enable incremental improvements in sensing capabilities.
Source Patent Element
Sending sensing information to a service server for processing
PTD Variation
Implementing distributed cloud-based processing with edge computing enhancements for real-time emotion analysis
Obviousness Reasoning
Integrating edge computing with cloud processing represents a predictable technological evolution in AI system architectures. A PHOSITA would recognize this as a standard performance optimization approach.
Source Patent Element
Generating simulated object data based on behavioral matching
PTD Variation
Advanced simulation techniques using probabilistic modeling and expanded behavioral dataset generation
Obviousness Reasoning
Refining simulation methodologies through more sophisticated modeling techniques is a natural progression for AI interaction systems. The approach represents a known technique for improving machine learning training processes.
Source Patent Element
Detecting environment information to determine interaction scenarios
PTD Variation
Implementing contextual awareness with enhanced multi-dimensional environmental sensing and adaptive response generation
Obviousness Reasoning
Expanding environmental sensing capabilities represents a standard approach to improving robotic interaction intelligence. A PHOSITA would view this as an obvious extension of existing interaction design principles.
Source Patent Element
Emotion information collection and processing
PTD Variation
Advanced emotion recognition using deep learning neural networks and cross-modal emotion inference techniques
Obviousness Reasoning
Applying state-of-the-art machine learning techniques to emotion recognition is a predictable technological progression. The approach represents a standard optimization strategy in AI interaction design.
35 U.S.C. § 103 Summary: Based on the teachings of US Patent 11858118 and the disclosed technical variations, a person having ordinary skill in the art would find the claimed synergistic combination techniques obvious and anticipated. The published technical disclosure demonstrates that the claimed innovations represent predictable technological extensions within the established framework of companion robot interaction methodologies, thereby rendering subsequent similar claims obvious and unpatentable.

Original Patent Information

Patent NumberUS 11,858,118
TitleRobot, server, and human-machine interaction method
Assignee(s)HUAWEI TECHNOLOGIES CO., LTD.