%0 Conference Paper %1 vorst2010icra %A Vorst, Philipp %A Zell, Andreas %B 2010 IEEE International Conference on Robotics and Automation (ICRA) %C Anchorage, Alaska, USA %D 2010 %I IEEE %K EPC RFID SLAM UHF autonomous estimation fully graph-based long-range mobile passive robot supermarket trajectory %P 1867--1872 %T Fully Autonomous Trajectory Estimation with Long-Range Passive RFID %U http://www.ra.cs.uni-tuebingen.de/publikationen/2010/vorst2010icra.pdf %X We present a novel approach which enables a mobile robot to estimate its trajectory in an unknown environment with long-range passive radio-frequency identification (RFID). The estimation is based only on odometry and RFID measurements. The technique requires no prior observation model and makes no assumptions on the RFID setup. In particular, it is adaptive to the power level, the way the RFID antennas are mounted on the robot, and environmental characteristics, which have major impact on long-range RFID measurements. Tag positions need not be known in advance, and only the arbitrary, given infrastructure of RFID tags in the environment is utilized. By a series of experiments with a mobile robot, we show that trajectory estimation is achieved accurately and robustly. %@ 978-1-4244-5040-4

@inproceedings{vorst2010icra, abstract = {We present a novel approach which enables a mobile robot to estimate its trajectory in an unknown environment with long-range passive radio-frequency identification (RFID). The estimation is based only on odometry and RFID measurements. The technique requires no prior observation model and makes no assumptions on the RFID setup. In particular, it is adaptive to the power level, the way the RFID antennas are mounted on the robot, and environmental characteristics, which have major impact on long-range RFID measurements. Tag positions need not be known in advance, and only the arbitrary, given infrastructure of RFID tags in the environment is utilized. By a series of experiments with a mobile robot, we show that trajectory estimation is achieved accurately and robustly. }, added-at = {2010-06-10T13:52:20.000+0200}, address = {Anchorage, Alaska, USA}, author = {Vorst, Philipp and Zell, Andreas}, biburl = {https://www.bibsonomy.org/bibtex/2cb2791bd2bc474ea97b0283012566f78/fifo79}, booktitle = {2010 IEEE International Conference on Robotics and Automation (ICRA)}, interhash = {d09f2b5fe184ca36bce61b9c3f6938a9}, intrahash = {cb2791bd2bc474ea97b0283012566f78}, isbn = {978-1-4244-5040-4}, keywords = {EPC RFID SLAM UHF autonomous estimation fully graph-based long-range mobile passive robot supermarket trajectory}, month = may, pages = {1867--1872}, publisher = {IEEE}, timestamp = {2010-06-10T13:52:20.000+0200}, title = {Fully Autonomous Trajectory Estimation with Long-Range Passive {RFID} }, url = {http://www.ra.cs.uni-tuebingen.de/publikationen/2010/vorst2010icra.pdf}, year = 2010 }