Robotics research + modeling

Biomechanical modeling and experimental validation of a soft variable-stiffness finger actuator.

M.Sc. thesis in progress: a simulation-first engineering framework for a simplified index-finger actuation system, moving from reduced-order modeling toward closed-loop benchtop validation.

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Thesis object

Index-finger actuator model

Simulation-first validation framework under development.

Model kinematics

Screen actuator designs

Validate against bench data

Engineering workflow

Built as an investigation that moves from model assumptions to measurable bench evidence.

Mathematical modeling

Python simulation

Design screening

CAD / prototype planning

Closed-loop benchtop validation

Calibration + error analysis

Short project overview

A focused actuator-system study, not a finished rehabilitation product.

The thesis investigates a simplified index-finger actuation system for neurorehabilitation-oriented hardware. The goal is to build a modeling and validation framework that can make design decisions more concrete before committing to physical prototypes.

Scope is intentionally limited to an index-finger actuator system.

Claims stay at the engineering-validation level rather than clinical efficacy.

Why it matters

Soft finger-assistive systems need evidence before they need polish.

Finger-assistive hardware can look convincing while hiding difficult trade-offs in tendon routing, stiffness, control authority, and measurement repeatability. This project uses simulation and benchtop data to expose those trade-offs early.

Compares actuator concepts before physical iteration becomes slow or expensive.

Keeps the evaluation tied to measurable behavior: force, displacement, motion, and repeatability.

Modeling approach

Reduced-order mechanics with explicit assumptions.

The model treats the finger and actuator as an inspectable engineering system: reduced-order index-finger kinematics, tendon-routing geometry, passive joint torque estimates, actuator leverage, tendon stroke, and tendon tension estimates.

Controllability and underactuation are treated as design trade-offs.

Variable or adjustable stiffness is modeled as part of the design space rather than assumed as a solved feature.

Current simulation outputs

Python sweeps that narrow the design space.

The current work uses Python simulation to compare candidate geometry and stiffness assumptions, estimate actuator requirements, and identify parameter regions worth taking into CAD and prototype planning.

Outputs support design screening around leverage, stroke, tension, and passive resistance.

Simulation results are framed as hypotheses to validate, not proof that the device works.

Planned benchtop validation

Closed-loop measurement, not just a demo rig.

The validation plan connects actuator input to measurable bench behavior: force-displacement measurement, motion tracking or computer-vision-based measurement, repeatability testing, and calibration against simulation predictions.

Closed-loop actuator input is a design goal for controlled experiments.

Model-vs-experiment error analysis is used to revise assumptions and quantify limits.

Engineering skills demonstrated

A complete simulation-to-test workflow.

The project demonstrates hands-on robotics engineering judgment: simplifying a physical system, writing simulations, screening designs, planning hardware tests, instrumenting measurements, and using experimental error to improve the model.

Relevant to robotics, medtech, controls, simulation, mechatronics, and product engineering roles.

Shows comfort moving between math, software, hardware constraints, and validation data.

Technical scope

Reduced-order index-finger kinematicsTendon-routing geometryPassive joint torque estimatesActuator leverageTendon strokeTendon tension estimatesControllability trade-offsUnderactuation trade-offsVariable stiffness conceptClosed-loop actuator inputForce-displacement measurementComputer-vision motion trackingRepeatability testingModel validation

Stack / themes

Python simulationBiomechanical modelingVariable stiffnessMotion trackingBenchtop validation