Navigation Without Localisation: Reliable Teach and Repeat Based on the Convergence Theorem

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F18%3A00328597" target="_blank" >RIV/68407700:21230/18:00328597 - isvavai.cz</a>

Result on the web

<a href="https://ieeexplore.ieee.org/document/8593803" target="_blank" >https://ieeexplore.ieee.org/document/8593803</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/IROS.2018.8593803" target="_blank" >10.1109/IROS.2018.8593803</a>

Result language

angličtina

Original language name

Navigation Without Localisation: Reliable Teach and Repeat Based on the Convergence Theorem

Original language description

We present a novel concept for teach-and-repeat visual navigation. The proposed concept is based on a mathematical model, which indicates that in teach-and-repeat navigation scenarios, mobile robots do not need to perform explicit localisation. Rather than that, a mobile robot which repeats a previously taught path can simply “replay” the learned velocities, while using its camera information only to correct its heading relative to the intended path. To support our claim, we establish a position error model of a robot, which traverses a taught path by only correcting its heading. Then, we outline a mathematical proof which shows that this position error does not diverge over time. Based on the insights from the model, we present a simple monocular teach-and-repeat navigation method. The method is computationally efficient, it does not require camera calibration, and it can learn and autonomously traverse arbitrarily-shaped paths. In a series of experiments, we demonstrate that the method can reliably guide mobile robots in realistic indoor and outdoor conditions, and can cope with imperfect odometry, landmark deficiency, illumination variations and naturally-occurring environment changes. Furthermore, we provide the navigation system and the datasets gathered at www.github.com/gestom/stroll_bearnav.

Czech name

—

Czech description

—

Type

D - Article in proceedings

CEP classification

—

OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

<a href="/en/project/GJ17-27006Y" target="_blank" >GJ17-27006Y: Spatio-temporal representations for life-long mobile robot navigation</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2018

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

ISBN

978-1-5386-8094-0

ISSN

2153-0858

e-ISSN

2153-0866

Number of pages

8

Pages from-to

1657-1664

Publisher name

IEEE Press

Place of publication

New York

Event location

Madrid

Event date

Oct 1, 2018

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

000458872701112