IITGN Robotics Lab

At the IITGN Robotics Lab, we engage in a wide range of projects in robotics that often span the entire spectrum from mathematical theory, modelling & analysis, learning algoroithms, controller development, ML/DL/AI tools, design, computational simulations, robot experiments & validations, and in some cases human subject studies. The lab has diverse interests and also attracts a diverse set of people from varying backgrounds who are passionate about different aspects of robotics.


We frequently post lab openings on our LinkedIn pages and IITGN careers page. We can be contacted at robotics [at] iitgn [dot] ac [dot] in.

Research

Learning for Robot Control

Robot control problems such as contact impedance modeling, tracking problems, redundancy resolution and agile motion generation are solved through learning based approaches such as Iterative Learning Control, reinforcement learning and impedance learning.

Soft Robotics

Our lab explores the frontiers of soft robotics, developing technologies that redefine interaction in unpredictable environments. We innovate across flexible surgical robots, adaptable grippers, and soft legged robots, aiming to enhance operational safety and efficiency. Our research is integral to advancing robotics in healthcare, manufacturing, and exploration, pushing boundaries towards more intuitive and resilient robotic systems.

Mobile Robots

Our lab advances mobile robotics with current projects like robot hopping, gait synthesis and learning of soft quadrupeds, and developing scalable path planning algorithms for multirobot systems. Our research can benefit applications in defense, agriculture, and rough terrain navigation, etc and we are exploring new frontiers to further enhance autonomous mobility.

Humanoids & Grasping

We concentrate on developing state-of-the-art manipulation and grasping strategies, particularly for humanoids and bi-manual robots, by leveraging robotics, AI, and sensor technology to refine accuracy and flexibility. Our research aims to deliver novel solutions that improve how robots interact with various environments, leading to smarter and dexterous manipulation.

Lab Videos

People

Harish Palanthandalam-Madapusi

Professor, Mechanical Engineering, IITGN

Madhu Vadali

Associate Professor, Mechanical Engineering, IITGN