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Siddhartha Kapuria

4 accepted papers

2026

MINT: A Vision-Based Soft Sensor for Mutual Integration of Normal Interaction Force and Texture Perception

Mohammad Rafiee Javazm, Siddhartha Kapuria, Ozdemir Can Kara, Sonika Kiehler, Rami Hamada, Joga Ivatury +1
ICRA 2026poster

Inspired by the design of Vision-based Tactile Sensors (VTSs) and soft resistive strain sensors, in this paper, we introduce MINT: a vision-based soft sensor for Mutual Integration of Normal interaction force and Texture perception. MINT is a hybrid vision-based tactile sensor that simultaneously in…

Cited by 0Scholar ↗
2025

Augmented Bridge Spinal Fixation: A New Concept for Addressing Pedicle Screw Pullout via a Steerable Drilling Robot and Flexible Pedicle Screws

Yash Kulkarni, Susheela Sharma, Omid Rezayof, Siddhartha Kapuria, Jordan P. Amadio, Mohsen Khadem +2
IROS 2025

To address the screw loosening and pullout limitations of rigid pedicle screws in spinal fixation procedures, and to leverage our recently developed Concentric Tube Steerable Drilling Robot (CT-SDR) and Flexible Pedicle Screw (FPS), in this paper, we introduce the concept of Augmented Bridge Spinal

Cited by 3Source ↗Scholar ↗
2025

Towards Evaluating the User Comfort and Experience of a Novel Steerable Drilling Robotic System in Pedicle Screw Fixation Procedures: A User Study

Susheela Sharma, Frigyes Samuel Racz, Sarah Go, Siddhartha Kapuria, Omid Rezayof, Jordan P. Amadio +3
ICRA 2025

Aiming at developing a safe, intuitive, and collaborative steerable drilling robotic system for pedicle screw fixation procedures, in this paper, we leverage our recently developed steerable drilling robotic framework, and developed a collaborative drilling mode to control this system. In this contr

Cited by 0Source ↗Scholar ↗
2024

Robot-Enabled Machine Learning-Based Diagnosis of Gastric Cancer Polyps Using Partial Surface Tactile Imaging

Siddhartha Kapuria, Jeff Bonyun, Yash Kulkarni, Naruhiko Ikoma, Sandeep Chinchali, Farshid Alambeigi
IROS 2024poster

In this paper, to collectively address the existing limitations on endoscopic diagnosis of Advanced Gastric Cancer (AGC) Tumors, for the first time, we propose (i) utilization and evaluation of our recently developed Vision-based Tactile Sensor (VTS), and (ii) a complementary Machine Learning (ML) a…

Cited by 2Source ↗Scholar ↗