Recent trends and role of large area flexible electronics in shape sensing application – a review

Abstract

Purpose This paper aims to review the shape sensing techniques using large area flexible electronics (LAFE). Shape perception of humanoid robots using tactile data is mainly focused. Design/methodology/approach Research papers on different shape sensing methodologies of objects with large area, published in the past 15 years, are reviewed with emphasis on contact-based shape sensors. Fiber optics based shape sensing methodology is discussed for comparison purpose. Findings LAFE-based shape sensors of humanoid robots incorporating advanced computational data handling techniques such as neural networks and machine learning (ML) algorithms are observed to give results with best resolution in 3D shape reconstruction. Research limitations/implications The literature review is limited to shape sensing application either two- or three-dimensional (3D) LAFE. Optical shape sensing is briefly discussed which is widely used for small area. Optical scanners provide the best 3D shape reconstruction in the noncontact-based shape sensing; here this paper focuses only on contact-based shape sensing. Practical implications Contact-based shape sensing using polymer nanocomposites is a very economical solution as compared to optical 3D scanners. Although optical 3D scanners can provide a high resolution and fast scan of the 3D shape of the object, they require line of sight and complex image reconstruction algorithms. Using LAFE larger objects can be scanned with ML and basic electronic circuitory, which reduces the price hugely. Social implications LAFE can be used as a wearable sensor to monitor critical biological parameters. They can be used to detect shape of large body parts and aid in designing prosthetic devices. Tactile sensing in humanoid robots is accomplished by electronic skin of the robot which is a prime example of human–machine interface at workplace. Originality/value This paper reviews a unique feature of LAFE in shape sensing of large area objects. It provides insights from mechanical, electrical, hardware and software perspective in the sensor design. The most suitable approach for large object shape sensing using LAFE is also suggested.

Imaging skins: stretchable and conformable on-organ beta particle detectors for radioguided surgery

“…Numerous strategies have been derived to monitor the shape of surface 3D objects. Proprioceptive sensing can be contact-based-through the integration of physical sensors or non-contact-based through the detection or specific markers with cameras [72,73].…”

Guest editorial

“…In the last paper, Shaik and Rufus (2021) review the shape sensing techniques used using large area flexible electronics (LAFE), where shape perception of humanoid robots using tactile data is mainly focused. In this review, the authors investigate papers published in the past 15 years and emphasize on contact-based shape sensors.…”

Multimode fusion perception for transparent glass recognition

“…The combination of different attributes constitutes the diversity and particularity of objects. For robots, the general recognition of object attributes only realizes robotic basic perception (Xu et al , 2019; Shaik and Rufus, 2021). With the increase in environment diversification and application tasks, this low-level perception makes it difficult to meet higher demands, such as clothes category (Fang et al , 2018) just judging functions but cloth attributes (fabric, hand feeling, weight) (Yuan et al , 2018) providing the selection of comfort.…”