1. auto N omous, self-Learning, OPTI mal and comp L ete U nderwater S ystems NOPTILUS FP7-ICT-2009.6: Information and Communication Technologies NOPTILUS KoM WP4: Cooperative Distributed Estimation Savvas Chatzichristofis & Elias Kosmatopoulos (CERTH) 16-17 May, 2011 Porto, Portugal

2. [Short Meeting Name], [Date], [Location]2 FP7-270180-NOPTILUS Project Acronym: NOPTILUS Project Number: 270180 Project Start Date: April 2011 Duration: 4 Years Funded by: EU FP7 Program Name: Information and Communication Technologies, FP7-ICT-2009.6 NOPTILUS Contact Information For information regarding this Project: Check the Project Web-Site: http://www.noptilus-fp7.eu http://www.noptilus-fp7.eu NOPTILUS Participants 1Centre for Research and Technology (CERTH, GR) 2Faculdade de Engenharia da Universidade do Porto (FEUP, PT) 3Eidgenössische Technische Hochschule Zürich (ETH, CH) 4Delft University of Technology (TU Delft, NL) 5Telecommunication Systems Institute (TSI, GR) 6Imperial College (Imperial, UK) 7OceanScan - Marine Systems & Technology, Lda (MST, PT) 8Administração dos Portos do Douro e Leixões, SA (APDL, PT)

3. [Short Meeting Name], [Date], [Location]3 FP7-270180-NOPTILUS Key Partners  CERTH  TSI  FEUP  ETHZ and Imperial will also contribute

4. [Short Meeting Name], [Date], [Location]4 FP7-270180-NOPTILUS The Objective (O7) In order to provide efficient and accurate situation and process understanding during situation-awareness operations multi-AUV systems must be able to  construct accurate 3D maps of the area under surveillance and  accurately locate and track dynamic phenomena of interest (e.g. movement and spread of chemical spills).

5. [Short Meeting Name], [Date], [Location]5 FP7-270180-NOPTILUS Which in case of our Demos «translates»to performing with high accuracy the following tasks:  locate and track the location of the ship (drum) while it is sinking  locate the exact location of the ship (drum) when it stabilized on the seafloor  construct a map of the seafloor area around the shipwreck (drum)  track the chemical spill while making sure that AUVs are accurately localized!

6. [Short Meeting Name], [Date], [Location]6 FP7-270180-NOPTILUS Mathematically Speaking … Find X given Y: Y=h(X,ξ)  Y is the vector of all sensor measurements (after processing them using the methodologies of WP3)  X is the vector of all quantities to be estimated:  AUVs’ position (pose)  Map features  Spread of the spill  ξ is the noise.

7. [Short Meeting Name], [Date], [Location]7 FP7-270180-NOPTILUS Problems  Measurements at different spatial and temporal scales  And, of different nature (sonar, GPS, vision,…)  Bandwidth limitations  Need to obtain accurate but low-dimensional representations (reduce size of data without losing crucial information)

8. [Short Meeting Name], [Date], [Location]8 FP7-270180-NOPTILUS Proposed Approach Use – and appropriately adapt/revise – existing approaches that were successful in similar applications:  Gaussian-Process (GPs) based mapping for constructing  3D maps of the seafloor  Dynamic maps of the spill Linear scaling with respect to number of observations!  Sonar-based INS system that treats differently the observations based on the information they carry  Decentralized estimators to reduce computational complexity

9. [Short Meeting Name], [Date], [Location]9 FP7-270180-NOPTILUS Proposed Approach Use – and appropriately adapt/revise – existing approaches that were successful in similar applications:  Extrinsic calibration methods to determine the relative position and attitude of groups of AUVs  Fuse spatially distributed heterogeneous sources of information (e.g., chemical sensors, sonars, cameras, etc)  Allow human operators to access and manipulate collected information at multiple levels.

10. [Short Meeting Name], [Date], [Location]10 FP7-270180-NOPTILUS Proposed Approach Use – and appropriately adapt/revise – existing approaches that were successful in similar applications:  Use of dimensionality reduction and quantization techniques  optimal use of the available memory and computational resources by employing sensor selection