Abstract
In this study, we propose a novel power assist control method for a powered exoskeleton without binding its legs. The proposed method uses motion sensors on the wearer’s torso and legs to estimate his/her motion to enable the powered exoskeleton to assist with the estimated motion. It can detect the start of walking motion quickly because it does not prevent the motion of the wearer’s knees at the beginning of the walk. A nine-axis motion sensor on the wearer’s body is designed to work robustly in very hot and humid spaces, where an electromyograph is not reliable due to the wearer’s sweat. Moreover, the sensor avoids repeated impact during the walk because it is attached to the body of the wearer. Our powered exoskeleton recognizes the motion of the wearer based on a database and accordingly predicts the motion of the powered exoskeleton that supports the wearer. Experiments were conducted to prove the validity of the proposed method.
Highlights
Powered exoskeletons are nowadays used in various fields, such as agriculture, and medical and welfare services [1,2,3,4]
Powered exoskeletons have been developed for workers in a nuclear power plant [11,12]
We propose a novel approach for power assist control of powered exoskeletons based on human motion estimation using the nine-axis motion sensors
Summary
Powered exoskeletons are nowadays used in various fields, such as agriculture, and medical and welfare services [1,2,3,4]. Sano et al [22,23] proposed using force sensors attached to the bottom of the wearer’s feet to detect the pressure between the shoes of the exoskeleton and the ground These exoskeletons control joint angle and angular velocity based on the given state of the leg, such as “stance phase” or “swing phase”, estimated by the force switches/sensors. The powered exoskeleton assists the worker to carry the load according to the measured weight of the load It has an advantage of not being affected by human sweat. We propose a novel approach for power assist control of powered exoskeletons based on human motion estimation using the nine-axis motion sensors. This paper shows the effectiveness of the proposed method through experiments with a powered exoskeleton
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