Intelligent Teleoperated Systems with Predictive Control

Publication ID: 24-11857280_0005_PTD

Published: November 07, 2025

Category:Future Evolutions & Paradigm Shifts

Legal Citation

pr1or.art Inc., “Intelligent Teleoperated Systems with Predictive Control,” Published Technical Disclosure No. 24-11857280_0005_PTD, Published November 07, 2025, available at https://archive.pr1or.art/24-11857280_0005_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. 11,857,280.

Summary of the Inventive Concept

A next-generation teleoperated system that leverages cognitive AI, machine learning, and neural networks to predict user intent and adapt to changing environmental conditions, revolutionizing the field of teleoperation.

Background and Problem Solved

The original patent disclosed a master/slave registration and control system for teleoperation, which, although groundbreaking, has limitations in terms of adaptability, user experience, and environmental responsiveness. The new inventive concept addresses these limitations by introducing advanced AI and machine learning capabilities to create a more intuitive, efficient, and effective teleoperated system.

Detailed Description of the Inventive Concept

The new inventive concept comprises a cognitive AI module that predicts user intent based on historical usage patterns, a control system that adjusts its response accordingly, and an input device that receives user input. The system employs machine learning algorithms to process user input, adapt to user behavior and preferences, and adjust the control system's response. The neural network-based control system learns to adapt to changing environmental conditions and user preferences over time, ensuring a seamless and efficient teleoperated experience.

Novelty and Inventive Step

The new inventive concept introduces a paradigm shift in teleoperation by integrating AI, machine learning, and neural networks to create a predictive and adaptive control system. This represents a significant departure from the original patent's master/slave registration and control approach, offering a more advanced, intuitive, and effective solution.

Alternative Embodiments and Variations

Alternative embodiments of the inventive concept could include the use of other AI and machine learning techniques, such as deep learning or reinforcement learning, to further enhance the system's predictive capabilities. Variations could also include the integration of additional sensors or data sources to improve the system's environmental responsiveness and adaptability.

Potential Commercial Applications and Market

The new inventive concept has far-reaching commercial potential in industries such as healthcare, manufacturing, and logistics, where teleoperation plays a critical role. The system's advanced AI and machine learning capabilities could revolutionize the way teleoperated systems are designed, deployed, and used, opening up new market opportunities and revenue streams.

Section 103 Obviousness Analysis (PHOSITA)

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Field of Art

Teleoperation systems, robotics control, human-machine interfaces, with expertise in control systems, reference frame transformations, and input device interaction

Person of Ordinary Skill (PHOSITA) Profile

An engineer with advanced degree in robotics, mechatronics, or control systems engineering, familiar with coordinate transformations, machine learning techniques, and adaptive control strategies

Obviousness Rationale

A PHOSITA would recognize that integrating machine learning and predictive intent recognition into teleoperation control is a natural evolutionary step from existing master/slave registration systems. The source patent's fundamental framework of end-effector orientation and reference frame alignment provides a clear foundation for implementing more sophisticated adaptive control techniques. The proposed AI-driven variations represent predictable extensions of existing teleoperation control methodologies.

Obvious Combinations & Variations

Source Patent Element

End-effector orientation determination relative to reference frames

PTD Variation

Adding machine learning algorithms to predict and adjust end-effector pose based on historical user behavior

Obviousness Reasoning

Predictable application of machine learning to existing control system architecture, representing an incremental technological improvement

Source Patent Element

Input device and control system interaction

PTD Variation

Neural network-based adaptive control system that learns user preferences over time

Obviousness Reasoning

Known technique of applying machine learning to improve human-machine interface responsiveness, representing a design choice within ordinary skill

Source Patent Element

Master/slave registration control mechanism

PTD Variation

Cognitive AI module predicting user intent and dynamically adjusting system response

Obviousness Reasoning

Logical extension of existing control paradigms using well-established machine learning techniques, producing predictable performance improvements

Source Patent Element

Reference frame alignment strategies

PTD Variation

Hybrid control system combining model-based and learning-based approaches

Obviousness Reasoning

Obvious combination of known control methodologies to enhance system adaptability and performance

Source Patent Element

Teleoperation system input processing

PTD Variation

Data collection and machine learning model training for continuous system adaptation

Obviousness Reasoning

Standard machine learning approach for improving system performance, representing an incremental technological advancement

35 U.S.C. § 103 Summary: Based on the teachings of US Patent 11857280 and the disclosed variations, a person of ordinary skill in the art would find the proposed teleoperation system with predictive AI control to be an obvious combination of prior art techniques. The integration of machine learning, neural networks, and adaptive control represents a straightforward technological progression that would be apparent to a skilled practitioner, thereby rendering potential claims covering such variations obvious and unpatentable under 35 U.S.C. § 103.

Original Patent Information

Patent Number	US 11,857,280
Title	Master/slave registration and control for teleoperation
Assignee(s)	INTUITIVE SURGICAL OPERATIONS, INC.