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Investigation of Control Parameters for Human-Robot Cooperative Lifting Tasks Using EMG Signals

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Abstract:

This paper investigates how humans perform the cooperative lifting task and propose an estimation method for controlling the parameters of human-robot cooperative tasks using electromyography (EMG) signals. When a person initiates a task, they must simultaneously transfer their motor intention such as movement direction and dynamic force to the robot. Two subjects, a leader and a follower, were asked to lift a bar-shaped object from both ends while the movement speed and object weight varied. This study developed a simple mathematical model to predict the person's movement intention. The results confirm that the proposed method can be used to estimate the leader's movement intentions during a cooperative lifting task. Through a logistic regression model, the movement direction was estimated, with approximately 81% accuracy, and time-varying hand path was estimated with approximately 78% accuracy for 60% of the subjects.

Keywords: CONTINUOUS HAND PATH; COOPERATIVE LIFTING TASK; EMG SIGNALS; LOGISTIC REGRESSION MODEL; MOVEMENT DIRECTION

Document Type: Research Article

DOI: https://doi.org/10.1166/sl.2012.2283

Publication date: 2012-05-01

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