MXene and PAN‐Based Carbon Fiber Enhanced Bimodal Triboelectric Sensor for Robotic Arm Perception and Control
Fangyang Dong, Guojun Yu, Hengxu Du, Peishuo Li, Yilin Liu, Hu Cai, Taili Du, Minyi Xu
- 发表年份
- 2025
- 引用次数
- 2
摘要
Abstract Endowing robots with human‐like perception and thinking to match the growing intelligentization remains a challenge. Here, an MXene and polyacrylonitrile (PAN) based carbon fiber enhanced bimodal triboelectric sensor (MPBS) is proposed to integrate with a commercial robotic arm, establishing a novel paradigm for perception and control. The touchless and tactile perception performance are further improved by a functional layer doped with MXene nanosheets and electrodes composed of PAN‐based carbon fibers. With 2 wt.% MXene, the MPBS electrical output increases by 100%, achieving a touchless sensing range of 200 cm and a peak output ratio of 3.65 V cm −2 . Integrating MPBSs into flexible fingers, a soft gripper with bimodal perception capabilities is developed. The touchless signals provide valuable insights into material composition, whereas the tactile mode enables precise shape recognition with an accuracy of 99.4%. The further integrated robotic arm utilizes touchless sensing to autonomously explore objects and run control actions when unexpected events occur. 10 types of object materials and shapes are identified with 98.7% accuracy using a convolutional neural network (CNN) that fuses touchless and tactile data. Demonstration of multitask applications, through the AI‐enabled robotic arm system, is successfully created for object detection, intelligent sorting, and pipeline inspection.
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