In this talk, I will highlight some recent progress in my group on two related research topics: multi-object rearrangement and discrete multi-body motion planning. Object rearrangement represents an everyday task being constantly carried out everywhere, e.g., tidying a desk, sorting out-of-order groceries on shelves, picking and packing food items from a conveyor belt, to list a few. As it turns out, interesting TSP and feedback vertex set problems naturally come out of typical multi-object rearrangement tasks, which can be solved accordingly. On the side of multi-body motion planning, I will outline some recent effort in characterizing the achievable optimality in well-connected environment, with associated algorithms that achieve the corresponding optimality guarantees.
Jingjin Yu is an Assistant Professor in the Department of Computer Science at Rutgers University. He received his B.S. degree from the Univeristy of Science and Technology in China, and M.S. and Ph.D. degrees from the University of Illinois at Urbana-Champaign. Before joining Rutgers, he held several postdoctoral positions at the University of Illinois, Boston University, and the Massachusetts Institute of Technology. He is broadly interested in the areas of algorithmic robotics and control, focusing on issues related to computational complexity and the design of efficient planning algorithms with provable performance guarantees.