Using RFID Snapshots for Mobile Robot Self-Localization. - Sebastian Schneegans; Philipp Vorst; Andreas Zell (EMCR, 2007)

Semi-autonomous Learning of an RFID Sensor Model for Mobile Robot Self-localization. - Philipp Vorst; Andreas Zell (EUROS, 2008)

Self-Localization with RFID snapshots in densely tagged environments. - Philipp Vorst; Sebastian Schneegans; Bin Yang; Andreas Zell (IROS, 2008)

Improved Mapping of RFID Tags by Fusion with Spatial Structure. - Karsten Rohweder; Philipp Vorst; Andreas Zell (ECMR, 2009)

Loop closure and trajectory estimation with long-range passive RFID in densely tagged environments. - Philipp Vorst; Bin Yang; Andreas Zell (ICAR, 2009)

Particle filter-based trajectory estimation with passive UHF RFID fingerprints in unknown environments. - Philipp Vorst; Andreas Zell (IROS, 2009)

Fully autonomous trajectory estimation with long-range passive RFID. - Philipp Vorst; Andreas Zell (ICRA, 2010)

A Comparison of Efficient Global Image Features for Localizing Small Mobile Robots. - Marius Hofmeister; Philipp Vorst; Andreas Zell (ISR/ROBOTIK, 2010)

A Comparison of Similarity Measures for Localization with Passive RFID Fingerprints. - Philipp Vorst; Andreas Zell (ISR/ROBOTIK, 2010)

Visual mapping with uncertainty for correspondence-free localization using Gaussian process regression. - Timo Schairer; Benjamin Huhle; Philipp Vorst; Andreas Schilling 001; Wolfgang Straßer (IROS, 2011)

Efficient self-adjusting, similarity-based location fingerprinting with passive UHF RFID. - Philipp Vorst; Artur Koch; Andreas Zell (RFID-TA, 2011)

Path following for indoor robots with RFID received signal strength. - Ran Liu 007; Philipp Vorst; Artur Koch; Andreas Zell (SoftCOM, 2011)

MORPHOSIS: A Lightweight Method Facilitating Sustainable Software Architectures. - Heiko Koziolek; Dominik Domis; Thomas Goldschmidt; Philipp Vorst; Roland J. Weiss (WICSA/ECSA, 2012)

Measuring Architecture Sustainability. - Heiko Koziolek; Dominik Domis; Thomas Goldschmidt; Philipp Vorst (IEEE Softw., 2013)

Energy Cloud: Real-Time Cloud-Native Energy Management System to Monitor and Analyze Energy Consumption in Multiple Industrial Sites. - Hugo Sequeira; Paulo Carreira 001; Thomas Goldschmidt; Philipp Vorst (UCC, 2014)