Physics

Heading (navigation)

Inertial measurement unit

Inertial navigation system

Geodesy

Philosophy

Ground truth

Inertial frame of reference

Benchmark (surveying)

Artificial intelligence

Geography

Phone

Computer science

Linguistics

Quantum mechanics

Computer vision

This paper sets a new foundation for data-driven inertial navigation research, where the task is the estimation of horizontal positions and heading direction of a moving subject from a sequence of IMU sensor measurements from a phone. In contrast to existing methods, our method can handle varying phone orientations and placements.More concretely, the paper presents 1) a new benchmark containing more than 40 hours of IMU sensor data from 100 human subjects with ground-truth 3D trajectories under natural human motions; 2) novel neural inertial navigation architectures, making significant improvements for challenging motion cases; and 3) qualitative and quantitative evaluations of the competing methods over three inertial navigation benchmarks. We share the code and data to promote further research. (http://ronin.cs.sfu.ca).

RoNIN: Robust Neural Inertial Navigation in the Wild: Benchmark, Evaluations, &amp; New Methods

RoNIN: Robust Neural Inertial Navigation in the Wild: Benchmark, Evaluations, &amp; New Methods

RoNIN: Robust Neural Inertial Navigation in the Wild: Benchmark, Evaluations, & New Methods