A Generic Approach to Self-localization and Mapping of Mobile Robots Without Using a Kinematic Model

Patrick Kesper, Lars Berscheid, Florentin Wörgötter, Poramate Manoonpong

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Abstrakt

In this paper a generic approach to the SLAM (Simultaneous Localization and Mapping) problem is proposed. The approach is based on a probabilistic SLAM algorithm and employs only two portable sensors, an inertial measurement unit (IMU) and a laser range finder (LRF) to estimate the state and environment of a robot. Scan-matching is applied to compensate for noisy IMU measurements. This approach does not require any robot-specific characteristics, e.g. wheel encoders or kinematic models. In principle, this minimal sensory setup can be mounted on different robot systems without major modifications to the underlying algorithms. The sensory setup with the probabilistic algorithm is tested in real-world experiments on two different kinds of robots: a simple two-wheeled robot and the six-legged hexapod AMOSII. The obtained results indicate a successful implementation of the approach and confirm its generic nature. On both robots, the SLAM problem can be solved with reasonable accuracy.
OriginalsprogEngelsk
TitelTowards Autonomous Robotic Systems : 16th Annual Conference, TAROS 2015, Liverpool, UK, September 8-10, 2015, Proceedings
RedaktørerClare Dixon, Karl Tuyls
ForlagSpringer
Publikationsdato2015
Sider136-142
ISBN (Trykt)978-3-319-22415-2
ISBN (Elektronisk)978-3-319-22416-9
DOI
StatusUdgivet - 2015
Begivenhed16th Annual Conference Towards Autonomous Robotic Systems - Liverpool, Storbritannien
Varighed: 8. sep. 201510. sep. 2015

Konference

Konference16th Annual Conference Towards Autonomous Robotic Systems
LandStorbritannien
ByLiverpool
Periode08/09/201510/09/2015
NavnLecture Notes in Computer Science
Vol/bind9287
ISSN0302-9743

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