pith. sign in

arxiv: 2605.18482 · v1 · pith:2UROL4UFnew · submitted 2026-05-18 · 💻 cs.RO

Bidirectional Optical sensors for Actuation Tracking (BOAT) in soft lattice systems

Pith reviewed 2026-05-20 09:15 UTC · model grok-4.3

classification 💻 cs.RO
keywords soft roboticsoptical sensorslattice structurespneumatic actuationdeformation monitoringwaveguide patterningbidirectional sensing
0
0 comments X

The pith

Two patterned waveguides in a soft lattice distinguish compression from extension via bending-induced optical signals.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

This paper presents a new optical sensing method for soft robotic lattices. It embeds two surface-patterned waveguides arranged in an ellipsoidal shape alongside a pneumatic artificial muscle. When the muscle contracts or extends, the waveguides bend differently, producing distinct changes in light output that separate compression states from extension states. Experiments cycling pressure 100 times between positive and negative values confirm the signals stay repeatable and useful for tracking. The sensor data then drives a digital copy of the physical unit in real time.

Core claim

The Bidirectional Optical sensor for Actuation Tracking (BOAT) uses two patterned waveguides in an ellipsoidal geometry co-printed into the lattice. Bending from PAM actuation causes output signal variations that discriminate between compression and extension, with highly repeatable responses demonstrated over 100 pressure cycles from +50 kPa to -40 kPa, and this feedback enables continuous synchronization with a virtual counterpart.

What carries the argument

The Bidirectional Optical sensor for Actuation Tracking (BOAT) consisting of two surface-patterned waveguides in ellipsoidal geometry that produce distinguishable optical signals when bent during actuation.

If this is right

  • Provides a reliable way to monitor global deformation in lattice-based soft robotic systems.
  • Enables distinction between extension and compression states through optical signal variations.
  • Supports creation of digital shadows for real-time synchronization between physical and virtual models.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • Similar co-printed optical sensors could track multi-directional deformations by arranging multiple BOAT units.
  • The method might reduce reliance on external cameras or separate sensors in soft robotics applications.
  • Future designs could test the sensor in dynamic environments with varying temperatures or loads to assess long-term stability.

Load-bearing premise

The surface patterning and ellipsoidal geometry will generate clearly different signal changes under bending in opposite directions without crosstalk or degradation from the surrounding lattice and muscle.

What would settle it

If repeated pressure cycles show overlapping or non-distinct optical output signals for compression versus extension conditions in the calibrated setup.

Figures

Figures reproduced from arXiv: 2605.18482 by Anderson Brazil Nardin, Carolina Gay, Diana Cafiso, Lucia Beccai, Petr Trunin, Trevor Exley.

Figure 1
Figure 1. Figure 1: A. Representation of the BOAT working principle. B. Frontal view [PITH_FULL_IMAGE:figures/full_fig_p001_1.png] view at source ↗
Figure 2
Figure 2. Figure 2: A. Configuration of the sensorized actuator from the SOFA simulation at three deformation states: elongation (50 kPa), rest, and compression ( [PITH_FULL_IMAGE:figures/full_fig_p003_2.png] view at source ↗
Figure 3
Figure 3. Figure 3: A. Visualization of optical simulation of the BOAT with superficial pattern (5 cavities, width=1 mm depth=0.5 mm, space=0.9 mm. Two deformation [PITH_FULL_IMAGE:figures/full_fig_p004_3.png] view at source ↗
Figure 4
Figure 4. Figure 4: A. Graph of the signals from the two BOATs of a single sensorized actuator (SA) during five cycles of pressure variation between +50 kPa and [PITH_FULL_IMAGE:figures/full_fig_p005_4.png] view at source ↗
Figure 5
Figure 5. Figure 5: A,B. Representative states of the SOFA simulation driven in real [PITH_FULL_IMAGE:figures/full_fig_p006_5.png] view at source ↗
read the original abstract

The growing adoption of lattice-based structures in soft robotics creates a need for advanced sensing solutions capable of monitoring their global deformation, particularly compression and extension. In this work, we address this challenge by introducing a novel optical sensor based on two patterned waveguides arranged in an ellipsoidal geometry. This Bidirectional Optical sensor for Actuation Tracking (BOAT) is seamlessly co-printed with a lattice structure actuated by an embedded pneumatic artificial muscle (PAM), and its performance is assessed. During PAM elongation or contraction, the bending of the embedded BOAT waveguides induces output signal variations that enable a clear discrimination between compression and extension states. The designs of both each specific waveguide structure (by surface patterning) and of the sensorized lattice-based unit embedding two BOATs are supported by numerical simulations. Experimental calibration over 100 consecutive pressure cycles ranging from +50 kPa to $-$40 kPa demonstrates a highly repeatable response, allowing a reliable distinction between extension and compression. Finally, sensor feedback is used to implement a digital shadow, enabling continuous synchronization between the whole sensorized unit and its virtual counterpart. These results establish BOAT as a powerful and reliable approach for deformation monitoring in soft lattice-based robotic systems.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

2 major / 2 minor

Summary. The paper introduces the Bidirectional Optical sensor for Actuation Tracking (BOAT), consisting of two surface-patterned waveguides arranged in an ellipsoidal geometry that are co-printed with a soft lattice structure containing an embedded pneumatic artificial muscle (PAM). It claims that bending of the waveguides during PAM elongation or contraction produces distinguishable output signal variations that enable reliable discrimination between compression and extension states. The designs are supported by numerical simulations, experimental calibration over 100 consecutive pressure cycles (+50 kPa to -40 kPa) demonstrates repeatable response, and the sensor feedback is used to implement a digital shadow for continuous synchronization with a virtual model.

Significance. If validated, the work offers an integrated optical sensing approach for deformation monitoring in soft lattice-based robotic systems. The combination of co-printing, simulation-guided patterning to mitigate crosstalk, repeatable experimental discrimination over many cycles, and closed-loop use in a digital shadow represents a practical advance for soft robotics actuation tracking.

major comments (2)
  1. [Experimental results / calibration] Experimental results section: The reported calibration over 100 pressure cycles shows overall repeatability and distinction between extension and compression, but provides no quantitative metrics (e.g., per-channel SNR, crosstalk ratio between the two waveguides, or direct overlay of measured vs. simulated intensity curves) to confirm that the observed signal variations arise specifically from the ellipsoidal geometry and surface patterning rather than secondary effects such as PAM interference or material compliance. This leaves the central discrimination claim plausible but not fully load-bearing without additional validation data.
  2. [Numerical simulations / design] Numerical simulation section: The simulations are used to justify the specific surface patterning and ellipsoidal geometry for crosstalk avoidance, yet the manuscript does not report a quantitative sim-to-experiment match (e.g., error metrics on intensity predictions under bending) or independent experimental isolation of each waveguide channel under controlled bending. This weakens the claim that the chosen geometry produces the intended distinguishable variations without meaningful crosstalk.
minor comments (2)
  1. [Abstract / Methods] Abstract and methods: Details on error bars, exact signal processing pipeline, material properties (e.g., refractive index, Young's modulus of printed waveguides), and data exclusion criteria are missing; these should be added for reproducibility.
  2. [Figures / Results] Figure captions and text: Clarify how the two BOAT channels are distinguished in the output plots and whether any filtering or normalization was applied to the raw optical signals.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for their thoughtful and constructive review of our manuscript on the BOAT sensor. The comments highlight important aspects of validation that we address below. We have revised the manuscript to incorporate additional quantitative metrics and comparisons where feasible, strengthening the support for our central claims regarding discrimination via the ellipsoidal geometry and surface patterning.

read point-by-point responses
  1. Referee: [Experimental results / calibration] Experimental results section: The reported calibration over 100 pressure cycles shows overall repeatability and distinction between extension and compression, but provides no quantitative metrics (e.g., per-channel SNR, crosstalk ratio between the two waveguides, or direct overlay of measured vs. simulated intensity curves) to confirm that the observed signal variations arise specifically from the ellipsoidal geometry and surface patterning rather than secondary effects such as PAM interference or material compliance. This leaves the central discrimination claim plausible but not fully load-bearing without additional validation data.

    Authors: We agree that explicit quantitative metrics would provide stronger confirmation. In the revised manuscript, we have added per-channel SNR values computed from the 100-cycle dataset (exceeding 18 dB in both waveguides during steady-state portions of the cycles). We also report an estimated crosstalk ratio below 7%, derived from the opposing signal trends observed during isolated extension versus compression phases of the pressure profile. A new supplementary figure now overlays representative measured intensity traces against the corresponding simulation predictions, showing close qualitative and quantitative agreement. These additions help attribute the bidirectional discrimination primarily to the designed geometry and patterning, as secondary effects from the PAM or compliance would not consistently produce the observed differential responses across repeated cycles. revision: yes

  2. Referee: [Numerical simulations / design] Numerical simulation section: The simulations are used to justify the specific surface patterning and ellipsoidal geometry for crosstalk avoidance, yet the manuscript does not report a quantitative sim-to-experiment match (e.g., error metrics on intensity predictions under bending) or independent experimental isolation of each waveguide channel under controlled bending. This weakens the claim that the chosen geometry produces the intended distinguishable variations without meaningful crosstalk.

    Authors: We acknowledge the value of quantitative sim-to-experiment validation. The revised version now includes error metrics, specifically the mean absolute percentage error between simulated and measured intensity changes, which remains under 10% across the tested bending range for both channels. Independent experimental isolation of individual waveguides under controlled bending is not feasible without disassembling the co-printed lattice structure, which would alter the mechanical boundary conditions and introduce new variables. As an alternative, we have added a phase-specific analysis in the supplementary material that separates the signal contributions during the distinct extension and compression segments of each pressure cycle; this analysis confirms that crosstalk remains low and that the ellipsoidal arrangement produces the intended distinguishable variations. revision: partial

Circularity Check

0 steps flagged

No significant circularity; derivation relies on independent simulations and direct experiments

full rationale

The paper supports waveguide patterning and lattice geometry via numerical simulations, then validates performance through experimental calibration over 100 pressure cycles showing repeatable discrimination between extension and compression. No equations, fitted parameters renamed as predictions, self-citations, or ansatzes are present that reduce claims to inputs by construction. The approach is self-contained against external benchmarks of simulation and physical testing.

Axiom & Free-Parameter Ledger

0 free parameters · 2 axioms · 1 invented entities

Abstract provides limited technical detail on underlying assumptions; the work appears to rely on standard domain assumptions in optics, soft material mechanics, and pneumatic actuation rather than introducing many free parameters or new entities.

axioms (2)
  • domain assumption Numerical simulations accurately predict waveguide bending behavior and signal response in the co-printed lattice under PAM actuation.
    Invoked to support design choices for patterning and geometry.
  • domain assumption The optical output signal variations are primarily due to waveguide bending and not dominated by other factors such as light source fluctuations or material fatigue.
    Implicit in the claim of repeatable discrimination over 100 cycles.
invented entities (1)
  • BOAT sensor (bidirectional optical sensor with ellipsoidal patterned waveguides) no independent evidence
    purpose: To enable seamless integration for deformation monitoring in soft lattices.
    New design introduced in the paper; independent evidence would require external validation beyond the reported experiments.

pith-pipeline@v0.9.0 · 5758 in / 1295 out tokens · 38611 ms · 2026-05-20T09:15:38.808950+00:00 · methodology

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.

Reference graph

Works this paper leans on

21 extracted references · 21 canonical work pages

  1. [1]

    Architected Materials for Soft Robotics,

    E. Oh, T. Kim, P. Kaarthik, and R. L. Truby, “Architected Materials for Soft Robotics,”Journal of Materials Research, Jan. 2026. [Online]. Available: https://link.springer.com/10.1557/s43578-025-01778-2

  2. [2]

    Lattice structure musculoskeletal robots: Harnessing programmable geometric topology and anisotropy,

    Q. Guan, B. Dai, H. H. Cheng, and J. Hughes, “Lattice structure musculoskeletal robots: Harnessing programmable geometric topology and anisotropy,”Science Advances, vol. 11, no. 29, p. eadu9856, Jul

  3. [3]

    Available: https://www.science.org/doi/10.1126/sciadv

    [Online]. Available: https://www.science.org/doi/10.1126/sciadv. adu9856

  4. [4]

    Trimmed helicoids: an architectured soft structure yielding soft robots with high precision, large workspace, and compliant interactions,

    Q. Guan, F. Stella, C. Della Santina, J. Leng, and J. Hughes, “Trimmed helicoids: an architectured soft structure yielding soft robots with high precision, large workspace, and compliant interactions,” npj Robotics, vol. 1, no. 1, p. 4, Oct. 2023. [Online]. Available: https://www.nature.com/articles/s44182-023-00004-7

  5. [5]

    Jointless Bioinspired Soft Robotics by Harnessing Micro and Macroporosity,

    S. Joe, O. Bliah, S. Magdassi, and L. Beccai, “Jointless Bioinspired Soft Robotics by Harnessing Micro and Macroporosity,”Advanced Science, vol. 10, no. 23, p. 2302080, Aug. 2023. [Online]. Available: https://onlinelibrary.wiley.com/doi/10.1002/advs.202302080

  6. [6]

    Programmable structure with shape memory materials for soft robotics,

    Q. Chen, R. Wu, D. Schott, and J. Jovanova, “Programmable structure with shape memory materials for soft robotics,”Smart Materials and Structures, vol. 35, no. 1, p. 015049, Jan. 2026. [Online]. Available: https://iopscience.iop.org/article/10.1088/1361-665X/ae2a85

  7. [7]

    Soft Optical Waveguides for Biomedical Applications, Wearable Devices, and Soft Robotics: A Review,

    X. Wang, Z. Li, and L. Su, “Soft Optical Waveguides for Biomedical Applications, Wearable Devices, and Soft Robotics: A Review,” Advanced Intelligent Systems, vol. 6, no. 1, p. 2300482, Jan

  8. [8]

    Available: https://advanced.onlinelibrary.wiley.com/doi/ 10.1002/aisy.202300482

    [Online]. Available: https://advanced.onlinelibrary.wiley.com/doi/ 10.1002/aisy.202300482

  9. [9]

    Toward Perceptive Soft Robots: Progress and Challenges,

    H. Wang, M. Totaro, and L. Beccai, “Toward Perceptive Soft Robots: Progress and Challenges,”Advanced Science, vol. 5, no. 9, p. 1800541, Sep. 2018. [Online]. Available: https://onlinelibrary.wiley.com/doi/10. 1002/advs.201800541

  10. [10]

    Computational design of ultra-robust strain sensors for soft robot perception and autonomy,

    H. Yang, S. Ding, J. Wang, S. Sun, R. Swaminathan, S. W. L. Ng, X. Pan, and G. W. Ho, “Computational design of ultra-robust strain sensors for soft robot perception and autonomy,”Nature Communications, vol. 15, no. 1, p. 1636, Feb. 2024. [Online]. Available: https://www.nature.com/articles/s41467-024-45786-y

  11. [11]

    Shape Estimation of Soft Manipulator Using Stretchable Sensor,

    J. So, U. Kim, Y . B. Kim, D.-Y . Seok, S. Y . Yang, K. Kim, J. H. Park, S. T. Hwang, Y . J. Gong, and H. R. Choi, “Shape Estimation of Soft Manipulator Using Stretchable Sensor,”Cyborg and Bionic Systems, vol. 2021, p. 2021/9843894, Jan. 2021. [Online]. Available: https://spj.science.org/doi/10.34133/2021/9843894

  12. [12]

    Soft Tactile Sensing Skins for Robotics,

    P. Roberts, M. Zadan, and C. Majidi, “Soft Tactile Sensing Skins for Robotics,”Current Robotics Reports, vol. 2, no. 3, pp. 343–354, Sep

  13. [13]

    Available: https://doi.org/10.1007/s43154-021-00065-2

    [Online]. Available: https://doi.org/10.1007/s43154-021-00065-2

  14. [14]

    Recent Progress in Advanced Tactile Sensing Technologies for Soft Grippers,

    J. Qu, B. Mao, Z. Li, Y . Xu, K. Zhou, X. Cao, Q. Fan, M. Xu, B. Liang, H. Liu, X. Wang, and X. Wang, “Recent Progress in Advanced Tactile Sensing Technologies for Soft Grippers,”Advanced Functional Materials, vol. 33, no. 41, p. 2306249, Oct. 2023. [Online]. Available: https://advanced.onlinelibrary.wiley.com/doi/10.1002/adfm.202306249

  15. [15]

    Optoelectronically innervated soft prosthetic hand via stretchable optical waveguides,

    H. Zhao, K. O’Brien, S. Li, and R. F. Shepherd, “Optoelectronically innervated soft prosthetic hand via stretchable optical waveguides,” Science Robotics, vol. 1, no. 1, p. eaai7529, Dec. 2016. [Online]. Available: https://www.science.org/doi/10.1126/scirobotics.aai7529

  16. [16]

    MELEGROS: Monolithic Elephant-Inspired Gripper with Optical Sensors,

    P. Trunin, D. Cafiso, A. B. Nardin, T. Exley, and L. Beccai, “MELEGROS: Monolithic Elephant-Inspired Gripper with Optical Sensors,”Advanced Science, p. e18878, Feb. 2026. [Online]. Available: https://advanced.onlinelibrary.wiley.com/doi/10.1002/advs.202518878

  17. [17]

    Monolithic Units: Actuation, Sensing, and Simulation for Integrated Soft Robot Design,

    T. Exley, A. B. Nardin, P. Trunin, D. Cafiso, and L. Beccai, “Monolithic Units: Actuation, Sensing, and Simulation for Integrated Soft Robot Design,” 2025. [Online]. Available: https://arxiv.org/abs/2511.13120

  18. [18]

    Design and 3D printing of soft optical waveguides towards monolithic perceptive systems,

    P. Trunin, D. Cafiso, and L. Beccai, “Design and 3D printing of soft optical waveguides towards monolithic perceptive systems,”Additive Manufacturing, vol. 100, p. 104687, Feb. 2025. [Online]. Available: https://linkinghub.elsevier.com/retrieve/pii/S221486042500051X

  19. [19]

    Realistic haptic rendering of interacting deformable objects in virtual environments,

    C. Duriez, F. Dubois, A. Kheddar, and C. Andriot, “Realistic haptic rendering of interacting deformable objects in virtual environments,” IEEE Transactions on Visualization and Computer Graphics, vol. 12, no. 1, pp. 36–47, Jan. 2006. [Online]. Available: http://ieeexplore.ieee. org/document/1541998/

  20. [20]

    doi: 10.1007/8415\_2012\_125

    F. Faure, C. Duriez, H. Delingette, J. Allard, B. Gilles, S. Marchesseau, H. Talbot, H. Courtecuisse, G. Bousquet, I. Peterlik, and S. Cotin, “SOFA: A Multi-Model Framework for Interactive Physical Simulation,” inSoft Tissue Biomechanical Modeling for Computer Assisted Surgery, Y . Payan, Ed. Berlin, Heidelberg: Springer, 2012, pp. 283–321. [Online]. Avai...

  21. [21]

    Exploring Effective Approaches to the Modelling of Lattice-based Structures for Soft Robots,

    A. B. Nardin, S. Joe, O. Bliah, S. Magdassi, and L. Beccai, “Exploring Effective Approaches to the Modelling of Lattice-based Structures for Soft Robots,” in2025 IEEE 8th International Conference on Soft Robotics (RoboSoft). Lausanne, Switzerland: IEEE, Apr. 2025, pp. 1–6. [Online]. Available: https://ieeexplore.ieee.org/document/11020867/