TY - CHAP A1 - Brooks, Alex A1 - Makarenko, Alexei A1 - Kaupp, Tobias A1 - Williams, Stefan A1 - Durrant-Whyte, Hugh F. T1 - Implementation of an indoor active sensor network T2 - 9th International Symposium on Experimental Robotics 2004, Singapore Y1 - 2004 ER - TY - CHAP A1 - Upcroft, Ben A1 - Ridley, Matthew A1 - Ong, Lee Ling A1 - Douillard, Bertrand A1 - Kaupp, Tobias A1 - Kumar, Suresh A1 - Bailey, Tim A1 - Ramos, Fabio A1 - Makarenko, Alexei A1 - Brooks, Alex A1 - Sukkarieh, Salah A1 - Durrant-Whyte, Hugh F. T1 - Multilevel state estimation in an outdoor decentralised sensor network T2 - 10th International Symposium on Experimental Robotics 2006 (ISER'06), Rio de Janeiro, Brazil Y1 - 2006 ER - TY - JOUR A1 - Makarenko, Alexei A. A1 - Kaupp, Tobias A1 - Durrant-Whyte, Hugh F. T1 - Scalable human-robot interactions in active sensor networks JF - IEEE Pervasive Computing N2 - Decentralized sensor networks promise virtually unlimited scalability and can tolerate individual component failures. Interaction with human operators plays an important role in the overall system design. The authors describe an experimental active sensor network and identify modes of human-robot interaction that keep up with the network's arbitrary growth. Y1 - 2003 U6 - https://doi.org/10.1109/MPRV.2003.1251170 VL - 2 IS - 4 SP - 63 EP - 71 ER - TY - CHAP A1 - Grocholsky, Ben A1 - Makarenko, Alexei A1 - Kaupp, Tobias A1 - Durrant-Whyte, Hugh F. ED - Zhao, Feng ED - Guibas, Leonidas T1 - Scalable control of decentralised sensor platforms T2 - Information Processing in Sensor Networks ; Lecture Notes in Computer Science (LNCS, Volume 2634) N2 - This paper describes an information-theoretic approach to decentralised and coordinated control of multi-robot sensor systems. It builds on techniques long established for the related problem of Decentralised Data Fusion (DDF). The DDF architecture uses information measures to communicate state estimates in a network of sensors. For coordinated control of robot sensors, the control objective becomes maximisation of these information measures. A decentralised coordinated control architecture is presented. The approach taken seeks to achieve scalable solutions that maintain consistent probabalistic sensor fusion and payoff formulations. It inherits the many benefits of the DDF method including scalability, seamless handling of sub-system activation and deactivation, and interoperability among heterogeneous units. These features are demonstrated through application to practical multi-feature localisation problems on a team of indoor robots equipped with laser range finders. Y1 - 2003 SN - 978-3-540-02111-7 SN - 978-3-540-36978-3 U6 - https://doi.org/10.1007/3-540-36978-3_7 SP - 96 EP - 112 PB - Springer CY - Berlin, Heidelberg ER - TY - CHAP A1 - Upcroft, Ben A1 - Ridley, Matthew A1 - Ong, Lee Ling A1 - Douillard, Bertrand A1 - Kaupp, Tobias A1 - Kumar, Suresh A1 - Bailey, Tim A1 - Ramos, Fabio A1 - Makarenko, Alexei A1 - Brooks, Alex A1 - Sukkarieh, Salah A1 - Durrant-Whyte, Hugh F. ED - Khatib, Oussama ED - Kumar, Vijay ED - Rus, Daniela T1 - Multi-level state estimation in an outdoor decentralised sensor network T2 - Experimental Robotics: The 10th International Symposium on Experimental Robotics ; Springer Tracts in Advanced Robotics (STAR, volume 39) N2 - Decentralised estimation of heterogeneous sensors is performed on an outdoor network. Attributes such as position, appearance, and identity represented by non-Gaussian distributions are used in in the fusion process. It is shown here that real-time decentralised data fusion of non-Gaussian estimates can be used to build rich environmental maps. Human operators are also used as additional sensors in the network to complement robotic information. Y1 - 2008 SN - 978-3-540-77456-3 U6 - https://doi.org/10.1007/978-3-540-77457-0_33 SP - 355 EP - 365 PB - Springer CY - Berlin, Heidelberg ER - TY - CHAP A1 - Wang, X. Rosalind A1 - Kumar, Suresh A1 - Ramos, Fabio A1 - Kaupp, Tobias A1 - Upcroft, Ben A1 - Durrant-Whyte, Hugh F. T1 - Learning in hyperspectral images using a nonlinear dimensionality reduction technique T2 - 9th International Conference on Information Fusion (Fusion 2006), Florence, Italy Y1 - 2006 ER -