University of Toronto Foot-Mounted Inertial Navigation Dataset

This dataset consists of measurements from a foot-mounted inertial measurement unit (IMU). In total, we provide data from five different test subjects travelling over more than 7.6 km. The data are combined with various forms of ground truth positioning information that can be used to evaluate the accuracy of a zero-velocity-aided, foot-mounted inertial navigation system (INS). In contrast to other similar datasets, our data incorporate several non-walking motions, such as running, crawling, and stair-climbing, as well as mixed-motion trials in which the test subjects alternated between walking and running. In addition to the dataset itself, we also provide an open source foot-mounted INS, with several zero-velocity detector implementations already coded up. The Python-based INS (called PyShoe), along with a suite of data processing tools, is available in the provided Github repository.