ASPIRE Lab
Advancing Autonomous Robotic Systems with Perception, Learning, and Intelligent Decision-Making
Department of Artificial Intelligence
Indian Institute of Technology Hyderabad
Latest News
View all →ASPIRE Lab is hiring a Junior Project Assistant to work on robotics research. BTech in Mechanical, Mechatronics, Robotics, Electrical, or ECE required. Applications close 31st August 2026.
Learn moreCongratulations to Our Graduating Students
Congratulations to Dr Krishnendu Roy for his doctor-hood at the 15th Convocation at IIT Hyderabad. Many congratulations to Sathwik, Saurabh, and Viswa Kiran for their well-earned MTech degrees, and to Shriram for his graduation!
Congratulations to VVS Viswa Kiran et al. for receiving the Best Poster Award at the 2026 IEEE Applied Sensing Conference (APSCON) for their work on a multi-sensor fusion framework for UAV navigation and inspection in GPS-denied and degraded environments.
Learn moreWe are now accepting applications for internship positions at ASPIRE Lab. Click the link to learn more and apply.
Learn moreNew Website and New Name: ASPIRE Lab
We are excited to launch our new website alongside our new name, ASPIRE Lab (Autonomous Systems, Perception, Intelligence, Robotics, and Exploration). The lab was formerly known as the Robotics and Intelligent Systems Lab (RIS Lab). Our previous website can still be viewed via the Wayback Machine archive.
Meet Our Team
Discover the talented researchers and students driving innovation at ASPIRE Lab.
Our Research
Explore our latest publications and contributions to robotics and autonomous systems.
Join Our Lab
Looking for PhD, postdoc, or research positions? Check out available opportunities.
About ASPIRE
ASPIRE Lab at Indian Institute of Technology Hyderabad (IIT Hyderabad) focuses on advancing autonomous robotic systems endowed with perception, learning, and intelligent decision-making in complex environments. Our research covers a broad spectrum of robotic platforms, including but not limited to, swarms of aerial drones, quadruped robots, biped / humanoid robots, human-robot interaction, wheeled mobile robots, and AUVs / underwater robots.
Our work combines principles of conventional control theory with learning-based approaches such as deep reinforcement learning and robot vision to develop systems capable of adaptive, data-driven behavior. Through these efforts, ASPIRE aims to integrate model-based understanding with data-driven intelligence to develop reliable and efficient autonomous systems for exploration, interaction, and real-world operation.