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.
Eric's paper on optimal SAR planning has been accepted to ICRA 2026 in Vienna, Austria. ASAR finds search patterns that minimize the expected detection time of an object given uncertainty about its location. There is an open access version of the paper on arXiv, a trailer video on YouTube, and we're really looking forward to sharing more about it at ICRA!
Tyler's paper on asymptotically optimal RRT-Connect (AORRTC) has been published in RA-L. We'll be presenting it with Wil Thomason and Zak Kingston (CoMMA Lab, Purdue University) at ICRA 2026 and are looking forward to seeing everyone in Vienna in June 2026. The paper is already up on on arXiv with an associated video on YouTube and the algorithm available in both VAMP and OMPL.
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!
