Published Technical Disclosure Archive

Enhanced New Applications & Use Cases Technical Implementation

Publication ID: 24-11858140_0002_PTD
Published: October 29, 2025
Category:New Applications & Use Cases

Legal Citation

pr1or.art Inc., “Enhanced New Applications & Use Cases Technical Implementation,” Published Technical Disclosure No. 24-11858140_0002_PTD, Published October 29, 2025, available at https://archive.pr1or.art/24-11858140_0002_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 new applications & use cases that builds upon the source patent's technical foundation.

Background and Problem Solved

The source patent addresses core functionality, but new applications & use cases presents opportunities for technical enhancement and expansion.

Detailed Description of the Inventive Concept

A comprehensive technical system that implements new applications & use cases 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 new applications & use cases 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 new applications & use cases 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 learning and adaptive control systems with a focus on machine learning-enabled robotic work processes

Person of Ordinary Skill (PHOSITA) Profile

A robotics engineer with expertise in machine learning, robotic control systems, adaptive learning algorithms, and industrial automation, holding at least a master's degree or equivalent professional experience in robotics engineering

Obviousness Rationale

A PHOSITA would recognize that the PTD's disclosed variations represent predictable extensions of the source patent's core robotic learning methodology by introducing incremental technical improvements that leverage known machine learning and robotic control techniques. The variations maintain the fundamental architecture of adaptive robotic systems while exploring alternative implementation strategies that would be apparent to a skilled practitioner. These extensions demonstrate standard engineering problem-solving approaches within robotic system design.

Obvious Combinations & Variations

Source Patent Element
Robot system with state detection sensor and learning control unit
PTD Variation
Enhanced sensor integration with expanded state detection capabilities across multiple work contexts
Obviousness Reasoning
Known technique of expanding sensor resolution and data collection methods to improve machine learning model accuracy, representing a predictable optimization within robotic system design
Source Patent Element
Additional learning unit that calculates next work state
PTD Variation
Implementing probabilistic modeling and multi-dimensional state transition prediction algorithms
Obviousness Reasoning
Applying standard machine learning techniques to improve state transition modeling, which would be an obvious refinement to a skilled robotics engineer
Source Patent Element
Operator input-driven learning mechanism
PTD Variation
Introducing collaborative learning interfaces with enhanced human-robot interaction feedback loops
Obviousness Reasoning
Extending human-machine interaction paradigms using known adaptive learning techniques, representing a design choice within robotic system development
Source Patent Element
Robot system configured to work based on operation commands
PTD Variation
Implementing context-aware command interpretation with machine learning-driven decision trees
Obviousness Reasoning
Applying standard artificial intelligence techniques to improve command processing, which would be a predictable evolution of existing robotic control systems
Source Patent Element
Switching device for converting operation forces
PTD Variation
Dynamic force translation mechanisms with real-time adaptive calibration
Obviousness Reasoning
Utilizing known control system optimization techniques to improve force translation accuracy, representing an incremental technical improvement
35 U.S.C. § 103 Summary: Based on the teachings of US Patent 11858140 and the disclosed technical variations, a person having ordinary skill in the art would find the claimed subject matter obvious, as the PTD demonstrates that the proposed technical solutions represent predictable extensions of existing robotic learning and control methodologies, employing standard engineering techniques to achieve incremental system improvements.

Original Patent Information

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