An FBG-based slip recognition and monitoring method for non-destructive grasping of flexible manipulator

Slip sensation is an important aspect of tactile perception for robots. Real-time slip monitoring is crucial for stable grasping. However, the existing slip sensors still have some limitations in materials, structure, and detection methods. Especially some large-sized and inflexible sensors are not easy to integrate and affect the movement of manipulators. In this paper, we use a fiber Bragg grating (FBG) sensor integrated into each flexible fingertip to detect and monitor the contact status between the flexible manipulator and objects. Firstly, the contact process between the flexible finger and the rigid plane from rest to relative sliding can determine the slip criterion by simulation analysis. The slip criterion is that the moment when the maximum tangential force occurs is the critical slip point. Then, the critical slip point in the corresponding FBG signal is determined by the variation of the tangential force in the three-directional force sensor. We verify the reliability of the recognition method under different contact conditions, same speed but different forces, same force but different speeds, and different roughness. Lastly, we develop the wavelet transformation-maximum root mean square discrepancy (WM) algorithm to monitor and predict the critical slip point in the FBG signal. Besides, its prediction time is about 0.7 s earlier than its monitoring time providing sufficient adjustment time for the control system to prevent overall slip. Therefore, the study has great application prospects in the non-destructive grasping of soft robots. [Display omitted] •Real-time monitoring of the critical slip point is the key to stable grasping for the flexible manipulator.•The simulation analysis of the contact state provides a judgment basis of the critical slip point in the FBG signal.•The WM algorithm can monitor and predict the critical slip point in the FBG signal in real time.•FBG-based monitoring and prediction of the slip state provide a new idea for feedback control of soft manipulators.