Recent Advances and Development Trends of Multi Core Fiber Based Shape Sensing Technologies

Shape sensing has become a key enabling technology in minimally invasive surgery, soft robotics, and structural health monitoring [1-6]. Traditional reconstruction methodsincluding fiber Bragg gratings (FBGs) or interferometric arrays-often face limitations in spatial continuity, cost, wiring complexity, and susceptibility to environmental fluctuations [7-9].

Multi core fiber (MCF) embeds several light guiding cores symmetrically within a single cladding. Each core experiences a distinct strain profile during bending or twisting, allowing determination of local curvature and torsion via differential phase or wavelength measurements [10-12]. Over the past decade, MCF based shape sensors have evolved rapidly, offering compact, flexible, and sensitive alternatives to conventional strain networks.

Principles of multi core fiber shape sensing

The basic principle relies on detecting optical path length changes among multiple cores. When the fiber bends, the outer cores undergo different elongations or compressions, producing measurable phase shifts or spectral changes [13]. Common interrogation techniques include:
Rayleigh based Optical Frequency Domain Reflectometry (OFDR), enabling distributed strain and curvature reconstruction with sub millimeter spatial resolution [14,15]; FBG array-based methods for localized sensing but with discrete sampling [16]; Brillouin based systems, which offer temperature insensitive strain and twist measurement [17]. Geometric algorithms estimate curvature vectors along the fiber and integrate them to recover the global 3D shape.

Recent progress and representative advances Fiber structure and materials

Advances in fiber drawing have produced seven core, nineteen core [18], and helically twisted MCFs with continuous Bragg gratings [19], improving torsion resolution and cross sensitivity discrimination. Some designs introduce polarization maintaining (PM) cores [20] or tailored dopant distributions for temperature stability (Figure 1).

Figure 1: Recent trending research areas in multi-core fiber development.

Interrogation systems

Optical frequency domain reflectometry (OFDR) is now a major tool for high resolution distributed shape sensing, enabling simultaneous curvature and twist retrieval; FPGA based processing reduces latency for real time monitoring [21].

Reconstruction algorithms

Machine learning assisted calibration and Kalman filter based dynamic tracking improve accuracy under complex deformations. Hybrid approaches that combine physical models with data driven priors provide noise suppression and better generalization [22].

Application demonstrations

Medical: MCF sensors integrated into catheters and guidewires enable accurate 3D tracking in minimally invasive procedures [23].

Soft robotics: Embedding MCFs in continuum robots enables self sensing feedback for closed loop control [24,25].

Structural monitoring: Large scale MCF networks monitor deformation in aerospace and flexible structures [26] (Figure 2).

Figure 2:(1) Sensing system and structure of the biomimetic soft finger [24]. (2) Experimental verification system of discontinuous deformation monitoring of smart aerospace structure [26]. (3) Response of the electronic skin [27]. (4) Complex deformation and shape reconstruction in magnetic structures [25].

Challenges and future trends

Despite rapid progress, several challenges remain before multi-core fiber (MCF) shape sensing can achieve large-scale applications. Temperature-induced cross-sensitivity must be mitigated through hybrid sensing schemes or optimized core geometry. Accurate system calibration is equally essential, as even minor geometric deviations among cores can accumulate into significant reconstruction errors. Robust fan-in/fan-out packaging and seamless integration are required for long-term reliability, while the massive data volume from distributed interrogation calls for efficient compression and intelligent analysis algorithms [10,27-30].

Recent research trends also emphasize Rayleigh scattering enhancement through controlled core doping or artificial scattering centers, which can improve signal-to-noise ratio and spatial resolution in OFDR-based sensing. In parallel, the development of high-temperature-resistant coatings and protective buffer layers is vital for ensuring environmental adaptability, enabling stable performance under harsh or thermally dynamic conditions.

Future directions include: (i) integration with silicon photonics for compact modules; (ii) AI based real time 3D reconstruction; (iii) specialty fibers that combine sensing and actuation; and (iv) further miniaturization for endoscopic and robotic deployment.

The development of MCF-based shape sensing signifies a transformative stage in modern fiber-optic sensing. Advances in fiber design, interrogation architecture, and algorithmic modelling are collectively driving improvements in accuracy, compactness, and intelligence, reinforcing its potential for integration into nextgeneration medical, robotic, and structural sensing platforms.