Real-Time Exoskeleton Collaboration Feedback for Energy-Efficient Assistance
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Solution Overview
Problem
Existing exoskeleton technologies lack effective methods to optimize user-exoskeleton interaction and collaboration, leading to inefficient energy usage and potential interference with natural body motion.
Innovation Solution
A real-time feedback-based optimization system that determines a collaboration metric between the user and the exoskeleton, adjusting parameters such as torque, velocity, and battery power to enhance interaction and reduce physiological impact.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If the exoskeleton provides more force to assist movement, then the user's physiological burden is reduced, but the energy consumption of the exoskeleton increases
Solution Approach 1:
The system employs a feedback mechanism where the controller continuously monitors collaboration metrics between the user and exoskeleton, and adjusts the level of force provided in real-time. This allows the exoskeleton to optimize its energy consumption by providing assistance only when and where it is most needed, rather than continuously maximizing force output.
Solution Approach 2:
The exoskeleton dynamically adjusts its mechanical power output based on real-time collaboration metrics. The system transitions from static force provision to dynamic adaptation, modifying torque, velocity, and power delivery according to the user's instantaneous needs and the determined collaboration level, thereby optimizing energy efficiency.
2Productivity
If the exoskeleton provides more mechanical power to assist movement, then the user's performance is enhanced, but the battery power consumption increases
Solution Approach 1:
The system changes operational parameters (torque, velocity, mechanical power) based on the determined collaboration metric. By dynamically adjusting these parameters in real-time according to user-exoskeleton interaction quality, the system enhances user performance while optimizing battery power consumption rather than maintaining constant high power output.
Solution Approach 2:
The exoskeleton system autonomously monitors its own energy consumption and performance output, using the collaboration metric to self-regulate power delivery. This self-service capability allows the system to optimize the balance between user performance enhancement and battery power conservation without external intervention.
3Ease of operation
If the exoskeleton parameters are adjusted in real-time based on collaboration metrics, then the interaction efficiency is improved, but the device complexity increases
Solution Approach 1:
The patent replaces complex mechanical adjustment mechanisms with a control system that uses sensors and algorithms to determine collaboration metrics and adjust parameters electronically. This substitution of mechanical systems with electronic control and software-based solutions improves interaction efficiency while managing device complexity through intelligent control rather than mechanical complexity.
Data Source
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AI summary
Systems and methods for determining a level of collaboration between a user and an exoskeleton boot are provided. A device, using an exoskeleton boot, can provide a level of force to a limb of a user to aide movement of the limb. The device can measure one or more parameters of the exoskeleton boot during the movement of the limb using the exoskeleton boot. The device can determine one or more biometrics of the user during the movement of the limb using the exoskeleton boot. The device can determine, based on the one or more biometrics and the one or more parameters of the device, a metric indicative of a collaboration between the user and the exoskeleton boot during the movement.