AIR Lab Robot Autonomy Seminar Series

The AIR Lab Robot Autonomy Seminar Series is a dynamic platform at the intersection of robotics, artificial intelligence, and autonomous systems. This seminar series provides an invaluable forum for experts, researchers, and enthusiasts to delve into the latest advancements and breakthroughs in the field of robot autonomy. Through engaging talks, demonstrations, and interactive discussions, the seminar series explores a wide spectrum of topics, from state-of-the-art machine-learning algorithms for robot perception and control to novel approaches in human-robot interaction and cutting-edge technologies that are reshaping the future of autonomous robotics. Whether you’re a seasoned professional or just starting your journey in robotics, this seminar series is a vital hub for sharing knowledge, fostering collaboration, and staying on the cutting edge of the ever-evolving field of robot autonomy.

Check the upcoming and past seminars.

A simpler path to supercharge robotic systems

Professor Subhrajit Bhattacharya has earned a prestigious NSF CAREER award for project using the mathematical field of topology, which could help streamline complex robotic systems used in healthcare, transportation, and manufacturing.

The prestigious CAREER award is given annually to junior faculty members across the U.S. who exemplify the role of teacher-scholars through outstanding research, excellent education, and the integration of education and research.


Siami ’14G ’17 PhD awarded NSF grant for research on complex networks

Mechanical engineering alum Milad Siami ’14G ’17 PhD, an assistant professor at Northeastern University, has been awarded a $300,000 grant from the National Science Foundation in support of his research on streamlining complex networks.

The project seeks “to make large-scale complex networks simpler by sparse interactions in the right place at the right time.”

Siami received his MS and PhD from Lehigh and was advised by mechanical engineering and mechanics professor Nader Motee, who directs Lehigh’s Distributed Control and Dynamical Systems Laboratory and Autonomous and Intelligent Robotics (AIR) Lab.

Congratulations Milad!

Papers in IROS 2021

Non-Prehensile Manipulation of Cuboid Objects Using a CatenaryRobot (IROS + RAL)

Gustavo A. Cardona, Diego S. D’Antonio, Cristian-Ioan Vasile, and David Saldaña

Abstract: Manipulating objects with quadrotors has been widely studied in the literature, but the majority of those approaches assume quadrotors and loads are previously attached. This setup requires human intervention that is not always achievable or desirable in practice. Furthermore, most of the robot configurations consider rods, manipulators, magnets, and cables modeled as rigid links attached to predefined places on objects. In contrast, we are interested in manipulating objects that are not specifically designed to interact with quadrotors, e.g., no predefined connections, and that do not require humans to set up. In this paper, we control a catenary robot composed of a cable and two quadrotors attached to its ends. Our robot is tasked with moving cuboid objects (boxes) on a planar surface. We design a controller that allows the catenary robot to place the cable in a specific area on the box to perform dragging or rolling. We validate our control design in simulation and with real robots, where we show them rolling and dragging boxes to track desired trajectories.


AIRLab Members Contribute to the US Robotics Roadmap and Science Robotics

Professor Jeff Trinkle has been sharing his expertise and experiences with the robotics community for decades.

His recent effort is co-authoring the 2020 Edition of the “Roadmap for US Robotics – From Internet to Robotics”, which will be published as a Journal paper in a few weeks.

We are looking forward to its publication!



Available now, Prof. Jeff Trinkle and his Ph.D. student, Jinda Cui, published a review paper on Science robotics:
(Author’s Publication Page for full-text)

This paper summarizes types of variations robots may encounter in human environments, and categorizes, compares, and contrasts the ways in which learning has been applied to manipulation problems through the lens of adaptability. Promising avenues for future research are proposed at the end.

A quick summary of this paper can be found in this report:


Lehigh’s AIRLab is set to create and share knowledge in Robotics starting from its creation, and it will continue doing that.