Journal of Bionic Engineering ›› 2023, Vol. 20 ›› Issue (4): 1544-1554.doi: 10.1007/s42235-023-00344-y
Perception of Static and Dynamic Forces with a Bio-inspired Tactile Fingertip
Longhui Qin1,2; Xiaowei Shi1; Yihua Wang1; Zhitong Zhou3
- 1 School of Mechanical Engineering, Southeast University, Nanjing 211189, China 2 State Key Laboratory of Fluid Power and Mechatronic Systems, Zhejiang University, Hangzhou 310027, China 3 Undergraduate Department of Statistics, University of California, Los Angeles, CA 90095, USA
Perception of Static and Dynamic Forces with a Bio-inspired Tactile Fingertip
Longhui Qin1,2; Xiaowei Shi1; Yihua Wang1; Zhitong Zhou3
- 1 School of Mechanical Engineering, Southeast University, Nanjing 211189, China 2 State Key Laboratory of Fluid Power and Mechatronic Systems, Zhejiang University, Hangzhou 310027, China 3 Undergraduate Department of Statistics, University of California, Los Angeles, CA 90095, USA
摘要： With the aid of different types of mechanoreceptors, human is capable of perceiving stimuli from surrounding environments and manipulating various objects dexterously. In this paper, a bio-inspired tactile fingertip is designed mimicking human fingertip in both structures and functionalities. Two pairs of strain gages and (Polyvinylidene Fluoride) PVDF films are perpendicularly arranged to simulate the Fast-Adapting (FA) and Slowly Adapting (SA) type mechanoreceptors in human hands, while silicones, Polymethyl Methacrylate (PMMA), and electronic wires are applied to mimic the skin, bone and nerve fibers. Both static and dynamic forces can be perceived sensitively. A preprocessing electric circuit is further designed to transform the resistor changes into voltages, and then filter and amplify the four-channel signals. In addition to strong robustness due to the embedded structure, the developed fingertip is found sensitive to deformations via a force test experiment. Finally, two robotic experiments explore its recognition ability of contact status and object surface. Excellent performance is found with high accuracy of 99.72% achieved in discriminating six surfaces that are ubiquitous in daily life, which demonstrates the effectiveness of our designed tactile sensor.