Published Technical Disclosure Archive

Enhanced Direct Improvements & Enhancements Technical Implementation

Publication ID: 24-11858140_0001_PTD
Published: October 29, 2025
Category:Direct Improvements & Enhancements

Legal Citation

pr1or.art Inc., “Enhanced Direct Improvements & Enhancements Technical Implementation,” Published Technical Disclosure No. 24-11858140_0001_PTD, Published October 29, 2025, available at https://archive.pr1or.art/24-11858140_0001_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 direct improvements & enhancements that builds upon the source patent's technical foundation.

Background and Problem Solved

The source patent addresses core functionality, but direct improvements & enhancements presents opportunities for technical enhancement and expansion.

Detailed Description of the Inventive Concept

A comprehensive technical system that implements direct improvements & enhancements 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 direct improvements & enhancements 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 direct improvements & enhancements 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 Manufacturing Systems, specifically robotic control systems with machine learning capabilities, focusing on adaptive robotic assembly and learning techniques

Person of Ordinary Skill (PHOSITA) Profile

A robotics engineer with expertise in machine learning, robotic control systems, and adaptive manufacturing technologies, holding at least a master's degree in robotics, mechanical engineering, or computer science with 3-5 years of industry experience in robotic system design

Obviousness Rationale

A PHOSITA would recognize that the PTD's disclosed improvements represent predictable variations on the source patent's core robotic learning methodology. The technical extensions demonstrate incremental advancements that would be readily conceived by applying standard engineering problem-solving techniques to the existing robotic control framework. These variations represent logical combinations of known robotic control and machine learning techniques that would be obvious to implement.

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 tracking and multi-dimensional learning algorithms
Obviousness Reasoning
Extending sensor capabilities is a predictable design optimization that a PHOSITA would find obvious when seeking improved robotic performance and learning precision
Source Patent Element
Additional learning unit calculating next work state based on current state value
PTD Variation
Implementing probabilistic modeling and advanced state transition prediction mechanisms
Obviousness Reasoning
Applying more sophisticated machine learning techniques to state prediction represents a known approach for improving robotic system adaptability
Source Patent Element
Operator input for defining work states and operation forces
PTD Variation
Introducing adaptive input mechanisms with real-time contextual learning and dynamic model adjustment
Obviousness Reasoning
Enhancing human-robot interaction through more flexible input processing is a standard engineering approach for improving robotic system responsiveness
Source Patent Element
Switching device for converting operator and calculation operation forces
PTD Variation
Implementing advanced force translation algorithms with machine learning-driven adaptive switching
Obviousness Reasoning
Developing more intelligent switching mechanisms using known machine learning techniques represents an obvious optimization for robotic control systems
Source Patent Element
Robot system configured to work based on machine learning models
PTD Variation
Introducing multi-modal learning approaches with enhanced generalization and transfer learning capabilities
Obviousness Reasoning
Expanding machine learning methodologies to improve robotic system adaptability is a predictable evolution of existing robotic control technologies
35 U.S.C. § 103 Summary: Based on the teachings of US Patent 11858140 and the disclosed technical variations, a person of ordinary skill in the art would find the claimed technical improvements obvious and lacking inventive distinctiveness. The published technical disclosure demonstrates that the claimed variations represent predictable extensions of existing robotic learning and control methodologies, thereby rendering potential patent claims obvious under 35 U.S.C. Section 103.

Original Patent Information

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