2 research outputs found
RuDaCoP: The Dataset for Smartphone-based Intellectual Pedestrian Navigation
This paper presents the large and diverse dataset for development of
smartphone-based pedestrian navigation algorithms. This dataset consists of
about 1200 sets of inertial measurements from sensors of several smartphones.
The measurements are collected while walking through different trajectories up
to 10 minutes long. The data are accompanied by the high accuracy ground truth
collected with two foot-mounted inertial measurement units and post-processed
by the presented algorithms. The dataset suits both for training of
intellectual pedestrian navigation algorithms based on learning techniques and
for development of pedestrian navigation algorithms based on classical
approaches. The dataset is accessible at http://gartseev.ru/projects/ipin2019
Precision improvement of MEMS gyros for indoor mobile robots with horizontal motion inspired by methods of TRIZ
In the paper, the problem of precision improvement for the MEMS gyrosensors
on indoor robots with horizontal motion is solved by methods of TRIZ ("the
theory of inventive problem solving").Comment: 6 pages, the paper is accepted to 9th IEEE International Conference
on Nano/Micro Engineered and Molecular Systems, Hawaii, USA (IEEE-NEMS 2014)
as an oral presentatio