The DIRo lab is working on developing intelligent multi-robot networks for tackling engineering problems across several domains. 

We are always looking for collaborations with industrial and academic partners to develop engineering solutions for societal problems.

Robot Learning for Contact-rich Manipulation

One of the goals of our research group is to have semi-autonomous multi-robot assembly (manufacturing) and disassembly (recycling and remanufacturing)  cells. The following are our current efforts towards this goal.

We are working towards planning and control of robots during contact-rich manipulation under task uncertainties.

1. Issue 1: Robot-based assembly under task uncertainties: Assembly remains a challenging robotic manipulation task in presence of tight tolerances and complex contact interactions. While Learning from Demonstration (LfD) frameworks like Dynamic Movement Primitives (DMPs) can effectively encode trajectories from a single demonstration, they are highly sensitive to variations in initial grasp configurations and external contact forces. Such variations often lead to task failures during the contact rich phases. 

Multi-Agent Coordination and Control
(... writing in progress)