Anup Teejo Mathew — accepted AI-conference papers

2026

Structure-Preserving Model Order Reduction of Slender Soft Robots Via Autoencoder-Parameterized Strain

Abdulaziz Y. Alkayas, Anup Teejo Mathew, Daniel Feliu, Yahya Zweiri, Thomas George Thuruthel, Federico Renda

ICRA 2026poster

While soft robots offer advantages in adaptability and safe interaction, their modeling remains challenging. This letter presents a novel, data-driven approach for model order reduction of slender soft robots using autoencoder-parameterized strain within the Geometric Variable Strain (GVS) framework…

Cited by 0 Source ↗Scholar ↗

2025

3-Axis Angular Strain Estimation With Hall Effect Sensors for Proprioception of Soft Robotic Manipulators

Yusuf Abdullahi Adamu, Daniel Feliú-Talegon, Anup Teejo Mathew, Federico Renda

RA-L 2025

Slender soft robots offer significant advantages for real-life applications, particularly in areas that require delicate and adaptable interaction with complex environments. However, their effectiveness and safety can be greatly limited in the absence of sensing capabilities. Hall effect sensors, kn

Cited by 3 Source ↗Scholar ↗

2025

Trident: A Multi-Functional Soft Appendage for Underwater Locomotion and Grasping

Aysha Ali Alshehhi, Costanza Armanini, Anup Teejo Mathew, Daniel Feliú-Talegon, Federico Renda

RA-L 2025

Soft underwater robots, designed to mimic the movement and adaptability of aquatic animals, use flexible materials like silicone and rubber to change shape and navigate complex environments. These robots can squeeze through narrow spaces and avoid obstacles, making them ideal for exploring underwate

Cited by 2 Source ↗Scholar ↗

2024

Dynamics and Control of Soft Robots With Implicit Strain Parametrization

Federico Renda, Anup Teejo Mathew, Daniel Feliú-Talegon

RA-L 2024

Efficient modeling of soft robots for design optimization and control is an active area of research. When representing soft robots as an assembly of rods and rigid bodies, strain-based parametrization has proved to be able to reduce the required number of degrees of freedom drastically. However, thi

Cited by 22 Source ↗Scholar ↗

2022

Geometrically-Exact Inverse Kinematic Control of Soft Manipulators With General Threadlike Actuators' Routing

Federico Renda, Costanza Armanini, Anup Teejo Mathew, Frédéric Boyer

RA-L 2022

The inverse kinematic control of soft robots appears as an open challenge that has been the subject of a number of letters presented in the last decade. Some solutions have been provided based on specific assumptions on the robot’s shape or the actuation mechanism. Other more generic approaches are

Cited by 33 Source ↗Scholar ↗

2022

Model-Based Design Optimization of Underwater Flagellate Propellers

Costanza Armanini, Aysha Ali Alshehhi, Anup Teejo Mathew, Ikhlas Mohamed Ben Hmida, Cesare Stefanini, Federico Renda

RA-L 2022

A new family of soft underwater propellers has been recently presented. Mimicking the swimming strategy of bacterial flagella, these modules passively adapt to the surrounding fluid to provide a propulsive thrust. In the present paper we aim at further investigating the behaviour of this device and

Cited by 4 Source ↗Scholar ↗