Tim Barfoot

BASc (Eng Sci Aero, Toronto), PhD (Toronto), PEng (Ontario)

Institute for Aerospace Studies
University of Toronto
4925 Dufferin Street, Room 189
Toronto, ON M3H 5T6 Canada
tim.barfoot [at] utoronto.ca
+1 416-667-7719 (office)
+1 416-667-7799 (fax)
skype: tim.barfoot
google scholar citations, arXiv, google+, calendar



The purpose of our lab's research program is to advance visual navigation of mobile robots. Our work finds application in transportation, planetary exploration, mining, warehouses, and military scenarios.

Much of our work is focused on a navigation stack we pioneered called visual teach and repeat (VT&R). VT&R has been particularly interesting in that it allows a robot to repeat a long (several kilometre) route that was taught manually, using only a single vision sensor (stereo camera, lidar, kinect) for feedback (no GPS needed). We have also layered a planning framework on top of VT&R to allow a robot to build a network of reusable paths (NRP) autonomously while exploring a space. Imagine a robot finding its way down a long canyon and then realizing it is a dead-end; because it has saved the outbound route, it can backtrack along it using VT&R and then try something else. VT&R has been successful because it avoids the need to construct a visual map of the world in a single priviledged coordinate frame and instead utilizes a topometric map.

Today we are interested in extending our ability to navigate visually to truly long durations (months or years) in order to enable real applications. We need to deal with changes in appearance (lighting, weather), in geometry (obstructions, dynamic objects), in our robots (hardware degradation/replacement/upgrades), and even in our algorithms. As a challenge, how could we build a map that a robot could use to navigate safely for 10 years? We plan to spend the next several years finding out.

Book on State Estimation

For several years I've been teaching a graduate course on state estimation for robotics and have expanded my notes into a book:

State Estimation for Robotics (394 pages)
SO(3) and SE(3) Identities and Approximations (2 pages)
Review by Luca Carlone (MIT)

If you find any typos/errors, please email me as I will continue to keep an up-to-date unofficial copy here as well as a list of errata for the published version. Please make sure you have the latest version before filing a bug report.

The official first edition can be found on the Cambridge University Press page here. A Chinese version of the book is available through the Xi'an Jiao Tong University Press here or as a pdf.


AER1514: Introduction to Mobile Robotics (Winter 2013-2017, 2019)
AER521: Mobile Robotics and Perception (Winter 2015-2017)
AER1513: State Estimation for Aerospace Vehicles (Fall 2009-2016)
AER372: Control Systems (Winter 2011-2012, 2019)
MAT185: Linear Algebra (Winter 2008)
AER407: Space Systems Design (Fall 2007-2012)
AER506: Spacecraft Dynamics and Control I (Fall 2001-2002)

List of UofT Grad Courses for Roboticists




Community Service

General Chair for Field and Service Robotics (FSR) 2015
Associate/Multimedia Editor for the International Journal of Robotics Research (IJRR) 2011-present
Associate Editor for the Journal of Field Robotics (JFR) 2012-present
Program Co-Chair of Computer and Robot Vision (CRV) 2012-13
Associate Editor for the IEEE International Conference on Robotics and Automation (ICRA) 2012
Area Chair for Robotics: Science and Systems (RSS) 2012-13