Welcome to the Estimation, Search, and Planning (ESP) research group, a member of the Ingenuity Labs Research Institute and the Department of Electrical and Computer Engineering (ECE) in Smith Engineering at Queen's University. We motivate a knowledge-based approach to robotics research by taking on challenging, real-world problems. We do this to test our solutions and force us to understand the fundamental challenges of next-generation robots.
Please have a look around our website to find out more about who we are and what we do, including our publicly available code and datasets. You may also be interested in our YouTube, Bluesky, and GitHub accounts.
Jianeng has successfully defended his D.Phil. on Vision-centric State Estimation and Mapping for Visually Challenging Scenarios at the University of Oxford. It includes both work he did with ESP at Oxford and Prof. Maurice Fallon in the Dynamic Robot Systems Group. Jianeng started his degree during the darkest days of the COVID pandemic and persevered through a lot of challenges outside his control, so it's a great pleasure to say: Congratulations, Dr. Wang!
Tyler Wilson presented his work on Fully Connected Informed Trees (FCIT*) at ICRA 2025 in Atlanta, Georgia. You can already read the paper on arXiv, watch a short video on YouTube, and checkout the code yourself.
While there, Tyler also presented an early preview of our recent RA-L submission on asymptotically optimal RRT-Connect (AORRTC), which you can read more about here.
Tyler has an exciting new work that achieves orders-of-magnitude faster asymptotically optimal planning with and without hardware acceleration. This work is with Wil Thomason and Zak Kingston (CoMMA Lab, Purdue University) and is under review at RA-L and an early release will be presented at the RoboARCH workshop at ICRA 2025. You can can watch the video on YouTube, read the paper on arXiv, and checkout both the VAMP and OMPL code.
