
Mapping, Path Following, and Perception with Long Range Passive UHF RFID for Mobile Robots
Ran Liu(Author)
Shaker (Publisher)
1st Edition
Published on 8. August 2018
Book
Paperback/Softback
149 pages
978-3-8440-4636-6 (ISBN)
Description
Due to the low-cost and contactless way of communication, radio-frequency identification (RFID) technology provides a solution to overcome the difficulties (e.g. occlusions) that the traditional line of sight sensors (e.g. cameras and laser range finders) face. In this thesis, we address the applications of using passive ultra high frequency (UHF) RFID as a sensing technology for mobile robots in three fundamental tasks, namely mapping, path following, and tracking.
In this thesis, we address the problem of recovering from mapping failures of static RFID tags and localizing non-static RFID tags which do not move frequently using a particle filter. The usefulness of negative information (e.g. non-detections) is also examined in the context of mapping RFID tags. Moreover, we present a novel three dimensional (3D) sensor model to improve the mapping accuracy of RFID tags. Second, we present a novel approach that combines RFID fingerprints and odometry information as an input of the motion control of a mobile robot for the purpose of path following in unknown environments. Last, we address the problem of tracking dynamic objects for mobile robots using RFID tags. To achieve this, we combine a two stage dynamic motion model with the dual particle filter, to capture the dynamic motion of the object and to quickly recover from failures in tracking. The state estimation from the particle filter is used in a combination with the VFH+ (Vector Field Histogram), which serves as a local path planner for obstacle avoidance, to guide the robot towards the target.
In this thesis, we address the problem of recovering from mapping failures of static RFID tags and localizing non-static RFID tags which do not move frequently using a particle filter. The usefulness of negative information (e.g. non-detections) is also examined in the context of mapping RFID tags. Moreover, we present a novel three dimensional (3D) sensor model to improve the mapping accuracy of RFID tags. Second, we present a novel approach that combines RFID fingerprints and odometry information as an input of the motion control of a mobile robot for the purpose of path following in unknown environments. Last, we address the problem of tracking dynamic objects for mobile robots using RFID tags. To achieve this, we combine a two stage dynamic motion model with the dual particle filter, to capture the dynamic motion of the object and to quickly recover from failures in tracking. The state estimation from the particle filter is used in a combination with the VFH+ (Vector Field Histogram), which serves as a local path planner for obstacle avoidance, to guide the robot towards the target.
More details
Series
Thesis
Doctoral thesis
2014
Eberhard-Karls-Universität Tübingen
Language
English
Place of publication
Aachen
Germany
Target group
Professional and scholarly
Product notice
Klappenbroschur
Illustrations
44
Dimensions
Height: 21 cm
Width: 14.8 cm
Weight
224 gr
ISBN-13
978-3-8440-4636-6 (9783844046366)
Schweitzer Classification