Leg Joint Torque Control for Adaptive Load Reduction

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Solution Overview

Problem

Existing load reduction devices struggle to provide appropriate torque output for varying user motions, leading to suboptimal load reduction.

Innovation Solution

A load reduction device equipped with a determination unit to identify repeated user motions and a torque control unit that uses machine learning to compare extracted motion characteristics with a reference model, adjusting torque output accordingly.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If conventional load reduction devices use fixed torque output, then device complexity is reduced, but load reduction effectiveness deteriorates for varying user motions

Engineering Contradiction:

Improveload reduction effectivenessVSAvoidcontrol system complexity

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The patent implements dynamic torque adjustment by detecting user motion state (walking, running, stationary) and sequentially changing torque output characteristics accordingly. The control unit adjusts torque based on detected motion patterns, transforming the fixed torque system into a dynamic adaptive system that matches user needs across different activities.

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The patent employs feedback mechanisms where the control unit continuously detects user motion state through sensors and adjusts torque output based on this information. The system monitors user motion characteristics and modifies torque delivery in real-time, creating a closed-loop control system that improves load reduction effectiveness while maintaining manageable complexity through intelligent feedback processing.

Inventive Principle:

Principle #23Feedback

2Reliability

If load reduction device adjusts torque for each motion type, then load reduction effectiveness is improved, but ease of operation deteriorates due to complex control

Engineering Contradiction:

Improveload reduction effectivenessVSAvoidcontrol simplicity

Core Design Contradiction:

ReliabilityVSEase of operation

Solution Approach 1:

The patent implements self-service control where the system automatically detects user motion state and adjusts torque characteristics without requiring manual user input. The control unit autonomously identifies whether the user is walking, running, or stationary and sequentially modifies torque output accordingly, eliminating the need for user intervention while maintaining operation simplicity.

Inventive Principle:

Principle #25Self-service

3Adaptability or versatility

If machine learning is used to extract motion characteristics, then adaptability is improved, but device complexity increases

Engineering Contradiction:

Improvemotion pattern recognitionVSAvoidprocessing complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The patent replaces complex mechanical or manual motion analysis systems with machine learning-based characteristic extraction. The system uses ML algorithms to automatically identify and classify user motion patterns from sensor data, substituting what would otherwise require complex mechanical sensing and analysis mechanisms with intelligent data processing that achieves higher adaptability with manageable complexity.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Data Source

PatentUS12208054B2Load reduction device, load reduction method, and storage medium storing program

Publication Date: 2025.01.28 NEC CORP

AI summary

A load reduction device includes a determination unit configured to determine a repeated motion that is repeated by a user; and a torque control unit configured to control, by comparing a characteristic extracted on the basis of machine learning for repeated motions and a reference model, torque output by a drive mechanism to reduce a load on the user at a joint of a leg of the user.