Stability analysis of human hand grasping for the design of pneumatic muscle-driven end effector targeting citrus picking

摘要

• The wavelet transform algorithm was used to quantitatively evaluate the grasping stability of each grasping posture. • Bottom-up Power palm-Thumb abduction had the highest stability, and the grasping direction from the bottom up was more stable than the side grasping. • Taking the finger as the unit, the thumb, index finger and middle finger make the main contribution in grasping. • The average contribution of the distal region of the thumb, index finger and middle finger is the largest in the region. • Based on the bottom-up Power palm-Thumb abduction, a pneumatic muscle-driven citrus picking end-effector was designed. The integration of fruit-picking robots with anthropomorphic hand technology represents a significant advancement in agricultural automation and intelligence. The end effector is a key component for citrus harvesting robots. This paper proposes a new method to analyze and evaluate the stability of human hand grasping of citrus to guide the design of end effectors. A comprehensive assessment of 33 common human hand grasping postures was conducted, summarizing the 4 most commonly used human hand grasping types in citrus picking. Pressure data acquisition gloves were employed to obtain grasping force data from 16 regions, Principal Component Analysis algorithm was utilized to evaluate the functionality of each finger region, and wavelet transform algorithm was applied to assess the stability of the 4 grasping types. A pneumatic muscle-driven end effector for citrus picking was designed. The experimental results indicate that the grasping stability varies among different types. The stability ranking from high to low is as follows: Power palm-Thumb abduction type, Pinch type, Power pad-Thumb abduction type, and Power palm-Thumb adduction type. The stability of grasping direction from bottom to top is higher than that of side. The grasping performance test results show that the pneumatic muscle-driven end effector can stably grasp citrus fruits, with an average grasping time of 1.31 s and a grasping success rate of 100%. This study provides strong support for the design of end effectors for citrus picking robots.