Project ZaVI -State Estimation Solely Based on Inertial Sensors and Prior Knowledge

alt Track Cycling can be tracked with an IMU alone

Inertial Navigation Systems (INS) are commonly used to track the pose (position and orientation) of an object. But the pose estimate of an INS alone does drift away from the true pose with time. Thus, they are often complemented by a Global Navigation Satelite Systems (GNSS) as the GPS. In certain environments, GNSS are unavailable. This would result in an increasing error of the pose estimate which yields the pose tracker unusable.

In the Project ZaVI we try to correct the drift of inertial sensors, by fusing the sensors with prior knowledge about the object. In general, the tracked object is subject to several motion and environmental constraints. These constraints allow to observe states of the object that would drift otherwise. The goal of the project is to understand how the constraints affect the observability of states.

The Project is funded by the German Research Federation.

ZaVI Project Overview

Ongoing Research

We are currently investigating the prior knowledge available at bouldering. https://up2date.uni-bremen.de/en/research/climbing-with-sensors

Datasets

Our recorded IMU datasets from Track Cycling and Bouldering are available at: http://www.informatik.uni-bremen.de/zavi-datasets/info.html

Code Repositories: https://github.com/TomLKoller/

Publications

Tom Koller, Tim Laue, Udo Frese (2019). State Observability through Prior Knowledge: A Conceptional Paradigm in Inertial Sensing. In Oleg Gusikhin (Ed.), Proceedings of the 16th International Conference on Informatics in Control, Automation and Robotics, 1 (781-788). SCITEPRESS. Presented at ICINCO 19 http://www.icinco.org/ Icinco19.pdf

Tom Koller, Udo Frese (2019). State Observability through Prior Knowledge: Tracking Track Cyclers with Inertial Sensors. In International Conference on Indoor Positioning and Indoor Navigation IPIN at Pisa, Italy. IPIN.pdf

Tom Koller, Udo Frese (2020). State Observability through Prior Knowledge: Analysis of the Height Map Prior for Track Cycling. In MDPI Sensors Special Issue on Sensors and Sensing Technologies for Indoor Positioning and Indoor Navigation. MDPI

Video: Results of Tracking a track cycler with an IMU and prior Knowledge only

Researchers

Tom Koller

Prof. Dr.-Ing. Udo Frese

Dr.-Ing. Tim Laue

zavi (zuletzt geƤndert am 2022-04-27 07:19:21 durch TomKoller)