Abstract
Human locomotion is a coordinated motion between the upper and lower limbs, which should be considered in terms of both the user’s normal walking state and abnormal walking state for a walking-aid robot system. Therefore, a novel coordinated motion fusion-based walking-aid robot system was proposed. To develop the accurate human motion intention (HMI) of such robots when the user is in normal walking state, force-sensing resistor (FSR) sensors and a laser range finder (LRF) are used to detect the two HMIs expressed by the user’s upper and lower limbs. Then, a fuzzy logic control (FLC)-Kalman filter (LF)-based coordinated motion fusion algorithm is proposed to synthesize these two segmental HMIs to obtain an accurate HMI. A support vector machine (SVM)-based fall detection algorithm is used to detect whether the user is going to fall and to distinguish the user’s falling mode when he/she is in an abnormal walking state. The experimental results verify the effectiveness of the proposed algorithms.
Highlights
An aging population dictates the need for elderly people to be able to live independently
After detecting two leg positions relative to the laser range finder (LRF), we used the center position of the line segment, which consists of the positions of both legs to estimate the human motion intention (HMI): Ẋ L =
V H and V L are the human intent motion velocities estimated by force-sensing resistor (FSR) sensors and LRF, respectively, and they are the input of the Kalman filter
Summary
An aging population dictates the need for elderly people to be able to live independently. Force sensors are most commonly used in HMI estimations for walking-aid robots because they enable user-friendly HRIsby transforming interaction forces from the user to the desired robot motion velocity. According to the coordinated motion of the human-robot system, force sensors and an laser range finder (LRF) were used to detect the velocities of the human’s upper and lower limbs to estimate HMIs. The synergy of arm and leg movements will help the robot to perceive more accurate HMI and release a part of the user’s hand strength. Compared with the conventional force control methods (such as admittance control), the proposed coordinated motion-based motion control algorithm can detect the user’s abnormal gait in abnormal walking state, remind the robot to react to prevent the user from falling.
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