Environment-Adaptive Constraint Selection for Robot Control

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Solution Overview

Problem

Existing control systems for robots and other control targets struggle to adapt to varying execution environments and processing conditions, limiting their ability to perform diverse tasks effectively.

Innovation Solution

A control device that selects and applies environment-compliant constraint condition data based on real-time environment feature information, using similarity calculations to match stored data with actual conditions, and generates control commands accordingly.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If a control system uses fixed control commands for robot operations, then the control logic is simple and easy to implement, but the system cannot adapt to varying execution environments and processing conditions

Engineering Contradiction:

Improveadaptability to execution environmentVSAvoidcontrol system complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The system pre-generates multiple constraint condition data sets corresponding to different execution environments and processing conditions before actual robot operation. These pre-prepared data sets include various constraint conditions that can be selectively applied based on the current environment, allowing the robot to adapt to different scenarios without complex real-time decision-making logic.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The control system dynamically selects appropriate constraint condition data from the pre-generated sets based on real-time detection of execution environment and processing conditions. This dynamic selection mechanism enables the system to adapt flexibly to varying conditions while maintaining a relatively simple overall structure, as the complexity is managed through data selection rather than complex control logic.

Inventive Principle:

Principle #15Dynamics

2Adaptability or versatility

If the control system stores multiple environment-compliant constraint condition data for different environments, then the adaptability to diverse processing tasks improves, but the data storage and selection complexity increases

Engineering Contradiction:

Improvecapability to perform diverse processingVSAvoidamount of constraint condition data

Core Design Contradiction:

Adaptability or versatilityVSQuantity of substance

Solution Approach 1:

The constraint condition data is segmented into multiple distinct data sets, each corresponding to specific execution environments and processing conditions. This segmentation allows the system to store comprehensive constraint information for diverse tasks while organizing the data in a structured manner that facilitates efficient retrieval and selection based on current conditions.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The constraint condition data structure is designed to be universal and multi-functional, where each data set can serve multiple processing tasks within its designated environment. This universality reduces the total amount of data needed, as the same constraint condition data can be applied across different tasks that share similar environmental characteristics.

Inventive Principle:

Principle #6Universality (Multi-functionality)

3Manufacturing precision

If the system selects constraint conditions based on real-time environment detection, then the control precision and task success rate improve, but the processing time and computational load increase

Engineering Contradiction:

Improvecontrol precisionVSAvoidenvironment detection and selection time

Core Design Contradiction:

Manufacturing precisionVSLoss of time

Solution Approach 1:

Environment feature extraction patterns and constraint condition selection criteria are pre-configured and prepared before actual robot operation. This preliminary preparation enables the system to perform rapid real-time detection and selection during execution, as the computational framework is already established and does not require complex processing during time-critical operations.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system employs dynamic thresholding and adaptive selection mechanisms that adjust the detection and selection process based on the specific situation. This allows the system to maintain high control precision while minimizing processing time by focusing computational resources on the most relevant environmental features and constraint conditions for the current task.

Inventive Principle:

Principle #15Dynamics

Data Source

PatentUS20260079460A1Control device, constraint condition selection device, data generation device, control method, constraint condition selection method, data generation method, and storage medium

Publication Date: 2026.03.19 NEC CORP

AI summary

A control device selects, among environment-compliant constraint condition data in which environment feature information that is information related to an execution environment of processing, and a constraint condition of execution of processing in the environment are associated with each other, environment-compliant constraint condition data corresponding to a real environment that is an execution environment of processing subjected to execution. The control device controls a control target to execute the processing subjected to execution based on a constraint condition indicated by the selected environment-compliant constraint condition data.