Work

Nonlinear compensation of stretchable strain sensors with application to proprioceptive sensing of soft robotic arm

Year: 2025

Type: article

Abstract: With advances in materials and manufacturing techniques, recent years have seen a number of conductive composite materials that exhibit pronounced strain-dependent electrical resistivity, allowing them to be used for embedded, cost-effective strain sensing in various applications. The strain-resistivity relationship of these materials, however, is often highly nonlinear and dynamic, posing challenges for effective use of such strain sensors. In this paper, a computationally efficient scheme is proposed for compensating the nonlinear, dynamic strain-resistance behavior of a soft conductive rubber using a time delay neural network. The accuracy and feasibility of the technique is evaluated with a soft robotic arm incorporating three strain sensors for proprioception. Experimental results show that the sensing scheme is able to predict both the tip position and the shape of the robotic manipulator, achieving an average tip positional error of less than 4% relative to the total length of the manipulator.

Source: Smart Materials and Structures

DOI: 10.1088/1361-665x/adb2c7

Authors: Vedant Naik, Preston Fairchild, Xiaobo Tan

Institution: Michigan State University

Language: English

Topic: Soft Robotics and Applications

Subfield: Biomedical Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: hybrid

Estimated APC paid: $3,325

Funders: Division of Computer and Network Systems, Division of Electrical, Communications and Cyber Systems