Designing Of The Cavity Type Pneumatic Soft Gripper And Surface Modification Research

As one of the important components of soft robots,soft grippers have wide application prospects in home service,agricultural harvesting,medical equipment,and other fields due to their good flexibility,adaptability,and safety of human-robot interaction.At present,the complex and changing operating environment has put forward higher requirements on the functions of the soft gripper such as versatility,environmental adaptability,and safety.Therefore,in order to obtain a functional surface with anti-fouling,anti-bacterial and frictionenhancing effects,we need to do the surface modification of the soft gripper surface and make the functional surface integrated with the inherent mechanical properties of the soft gripper,which is important to improve its task performance and environmental adaptability.This paper focuses on the following areas of research:(1)Analysis of the optimal structural parameters of the soft gripper.First,the basic structure and working principle of the cavity type pneumatic soft gripper were introduced.Second,the static mathematical model of the soft gripper bending angle was established by using the moment balance principle.Third,the affecting factors of the soft gripper bending angle were analyzed and the finite element analysis method was used to analyze the influence of the number of cavities and the thickness of the flexible sealing layer on the soft gripper driving performance.Finally,the structural parameters of the soft gripper with smaller Mises stress in the cavity,larger bending angle,and larger end force were determined through parameter optimization.(2)A prediction model was established between soft gripper bending angle and soft gripper structural parameters.Mainly by introducing the principle,structure,and training process of the BP neural network,we determined the number of layers and the number of nodes in each layer required for the neural network.At the same time,we did some experiments to obtain sample data as the training set of the neural network model and perform training and prediction testing.(3)Preparation and characterization of functional surfaces.A three-factor,the four-level orthogonal test was designed to investigate the effects of different laser processing parameters on surface wettability to obtain optimized laser processing parameters.A PDMS surface with superhydrophobic properties was obtained by selecting different laser processing paths and processing methods.The results showed that the wettability of the surface prepared by laser processing was better.The surface morphology,composition,surface wettability,anti-fouling property and wear resistance were also characterized and analyzed.(4)Preparation and testing of soft grippers with anti-fouling,anti-bacterial and frictionenhancing effects.Based on the analysis and study of the superhydrophobic effect of the surface prepared above,the superhydrophobic surface was combined with the soft gripper.Based on the structural design of the soft gripper,the materials of the cavity,strain-limiting layer,and flexible sealing layer were selected.Moreover,the soft gripper was modeled and analyzed by Solidworks.At the same time,the soft gripper was molded using light-curing 3D printing,and a pneumatic control circuit was built to control the soft gripper.The bending performance,end force,anti-fouling,anti-bacterial ability,and surface friction increase were investigated in combination with relevant theories and experiments.Finally,its physical gripping ability was verified.The results show that the soft gripper has good anti-fouling,antibacterial and physical gripping abilities,which provides a reference for its application in complex environments.