Published Technical Disclosure Archive

Enhanced Synergistic Combinations Technical Implementation

Publication ID: 24-11858140_0003_PTD
Published: October 29, 2025
Category:Synergistic Combinations

Legal Citation

pr1or.art Inc., “Enhanced Synergistic Combinations Technical Implementation,” Published Technical Disclosure No. 24-11858140_0003_PTD, Published October 29, 2025, available at https://archive.pr1or.art/24-11858140_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. 11,858,140.

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 B25J9/163
B B25 B25J9/1697
B B25 B25J9/1602
B B25 B25J9/1679
B B25 B25J13/08

Field of Art

Robotics and Automated Systems, specifically robotic assembly and machine learning-enhanced robotic control systems, with expertise in robotic arm manipulation, sensor integration, and adaptive learning algorithms

Person of Ordinary Skill (PHOSITA) Profile

A robotics engineer with advanced degree in mechanical or electrical engineering, proficient in machine learning techniques, robotic control systems, sensor integration, and adaptive algorithmic design, with 3-5 years professional experience in industrial robotics

Obviousness Rationale

A PHOSITA would recognize that the PTD's synergistic combination enhancements represent predictable variations of the source patent's robotic learning system. The disclosed technical improvements leverage known machine learning and robotic control techniques that would be readily apparent to someone skilled in the art. The PTD's approach extends the original patent's adaptive learning framework through straightforward technical modifications that do not require inventive complexity.

Obvious Combinations & Variations

Source Patent Element
Robot system with state detection sensor and learning control unit
PTD Variation
Enhanced sensor integration with expanded state value detection and multi-dimensional learning algorithms
Obviousness Reasoning
Predictable extension of existing sensor-based learning techniques, representing a known method of improving robotic system performance through more granular state tracking
Source Patent Element
Additional learning unit calculating next work state based on current state value
PTD Variation
Implementing advanced predictive modeling techniques to anticipate and optimize robotic task sequences
Obviousness Reasoning
Applying known machine learning approaches to extend the original patent's adaptive learning framework, representing an obvious design optimization
Source Patent Element
Operator input-driven model updating mechanism
PTD Variation
Introducing dynamic feedback loops and enhanced human-robot interaction protocols
Obviousness Reasoning
Utilizing well-established human-machine interface design principles to improve learning system responsiveness, representing a standard engineering design choice
Source Patent Element
Switching device for converting operator and calculation operation forces
PTD Variation
Implementing more sophisticated force translation and adaptive control algorithms
Obviousness Reasoning
Applying known control system techniques to enhance operational flexibility, representing a predictable technological progression
Source Patent Element
Machine learning-based robot system for task performance
PTD Variation
Expanding learning models to incorporate more complex contextual and environmental variables
Obviousness Reasoning
Extending existing machine learning paradigms through systematic feature integration, representing an obvious technical improvement within the state of the art
35 U.S.C. § 103 Summary: Based on a comprehensive analysis of US Patent 11858140 and the corresponding Published Technical Disclosure, a Person Having Ordinary Skill In The Art would find the claimed technical variations obvious and lacking inventive step. The disclosed synergistic combinations represent predictable extensions of existing robotic learning system technologies, employing standard engineering approaches that would be readily conceived by a skilled practitioner without requiring extraordinary innovation.

Original Patent Information

Patent NumberUS 11,858,140
TitleRobot system and supplemental learning method
Assignee(s)KAWASAKI JUKOGYO KABUSHIKI KAISHA