Real time control and fabrication of a soft robotic glove by two parallel sensors with MBD approach

Soft robotic gloves were designed to aid the rehabilitation process with hand pathologies and coordination of gripping exercises. The main issue in soft robotic actuators is to design a control strategy to overcome deformation in grasping exercises. In this paper, a new soft robotic actuator is developed to be protected against swell and deformation. This soft robotic glove is equipped with two sensors; these sensors make the robotic glove more intelligent. In the hardware, it was used two sensors in the new closed-loop method which include an air pressure sensor in the figure tip and a flex sensor to measure finger flexion rate. Two closed-loop control system is developed to regulate inlet air pressure and regulate the angle of the fingers for the soft robotic actuator. A Model-Based Design (MBD) method is presented as a very cost-effective, favorable, and robust method. PID programming on an embedded controller is applied by MBD approach. The soft actuator process contains a molded wooden chamber and fiber reinforcement. Experimental results show that the proposed soft robotic has a soft gripping mechanism, accurate gripping against various objects during daily activities.

Automated summary

Soft robotic gloves were designed to assist in the rehabilitation of hand pathologies and coordination of gripping exercises through a new soft robotic actuator. The use of two sensors in the hardware allows for intelligent control of finger angles and air pressure, while a Model-Based Design method provides a cost-effective and robust control strategy. Experimental results demonstrate the soft robotic glove's ability to accurately grip various objects during daily activities.