My research lies at the intersection of Robotics, Computer Vision, and Machine Learning. I work on developing learning-based methods for manipulation with soft and hybrid robotic arms, focusing on dexterous control in cluttered and unstructured environments. I also work on tactile‑centric policies for manipulation, enabling vision‑free exploration and object reconstruction , for both rigid arms and anthropomorphic hands. This work finds use in many applications such as autonomous harvesting, human assistive devices, medical imaging, underwater exploration, manufacturing and more!
TACTFUL: Tactile-Driven Exploration For Object Localization and
Identification in Confined Environments Shivani Kamtikar, Chung Hee Kim, Camilla Tabasso, Tye Brady, Josh Migdal, Taskin Padir
Under Review
We present a vision-free framework that enables a multi-fingered robot to autonomously explore confined workspaces, discover objects through contact, and identify them via tactile reconstruction
Grasp, Slide, Roll: Comparative
Analysis of Contact Modes for Tactile-Based Shape Reconstruction
Chung Hee Kim, Shivani Kamtikar, Tye Brady, Taskin Padir, Josh Migdal
IEEE International Conference on Robotics and Automation (ICRA), 2026
We present a study on how different contact modes affect object shape reconstruction using a tactile-enabled dexterous gripper.
A deep learning-based visual servoing framework enabling robust 3D positioning of soft continuum arms, achieving sub-2 cm translation error and sub-0.25 rad rotation error in structured settings.
Extending visual servoing to hybrid continuum manipulators in cluttered, unstructured scenes, combining vision and modeling for robust pose control.
Patents
System for Translating Indian Sign Language into a Common Language and a Method Therefore Shivani K. Kamtikar, Esha Gavali, Ayeshatasnim Hannure, Urvi Lendhe, Dr. Anagha Kulkarni
The Patent Office, Government Of India certificate