Marine Robots in Environmental Surveys: Current Developments at ISME—Localisation and Navigation

Despite the growing interest that marine engineering has received during the past few decades, autonomous underwater navigation can be still considered a daunting task. Unfavourable environmental conditions and limitations on the typologies of available sensors increase the difficulties autonomous vehicles encounter during the execution of planned missions. As of today, one of the main challenges researchers face is the precise localisation of underwater vehicles, where the limitation of the error drift over time becomes extremely important for long navigation missions. In recent years, the authors, within ISME—Interuniversity Center of Integrated Systems for the Marine Environment, extensively worked on autonomous underwater navigation, with special focus on positioning techniques. Working in parallel, research was conducted on the topics of both the improvement of state-of-the-art navigation techniques and on the employment of local sensor networks to periodically reset position errors. This contribution reports the most significative results obtained by the authors during these years.

[1]  Benedetto Allotta,et al.  A new AUV navigation system exploiting unscented Kalman filter , 2016 .

[2]  Luigi Chisci,et al.  An unscented Kalman filter based navigation algorithm for autonomous underwater vehicles , 2016 .

[3]  Francesco Di Corato,et al.  Thesaurus: AUV teams for archaeological search. Field results on acoustic communication and localization with the Typhoon , 2014, 22nd Mediterranean Conference on Control and Automation.

[4]  Benedetto Allotta,et al.  Preliminary design and fast prototyping of an Autonomous Underwater Vehicle propulsion system , 2015 .

[5]  Sajad Saeedi,et al.  AUV Navigation and Localization: A Review , 2014, IEEE Journal of Oceanic Engineering.

[6]  Jill Carlton 2 – Propulsion systems , 2007 .

[7]  A. Caiti,et al.  Toward underwater acoustic-based simultaneous localization and mapping. Experimental results with the Typhoon AUV at CommsNet13 sea trial , 2014, 2014 Oceans - St. John's.

[8]  Benedetto Allotta,et al.  Single axis FOG aided attitude estimation algorithm for mobile robots , 2015 .

[9]  Ovidio Salvetti,et al.  The ARROWS project: adapting and developing robotics technologies for underwater archaeology , 2015 .

[10]  Francesco Di Corato,et al.  Cooperative navigation of AUVs via acoustic communication networking: field experience with the Typhoon vehicles , 2016, Auton. Robots.

[11]  Robert E. Mahony,et al.  Nonlinear Complementary Filters on the Special Orthogonal Group , 2008, IEEE Transactions on Automatic Control.

[12]  Jeffrey K. Uhlmann,et al.  Unscented filtering and nonlinear estimation , 2004, Proceedings of the IEEE.

[13]  Thor I. Fossen,et al.  Guidance and control of ocean vehicles , 1994 .

[14]  John J. Leonard,et al.  Cooperative Localization for Autonomous Underwater Vehicles , 2009, Int. J. Robotics Res..

[15]  Luigi Chisci,et al.  A comparison between EKF-based and UKF-based navigation algorithms for AUVs localization , 2015, OCEANS 2015 - Genova.

[16]  E. A. de Barros,et al.  Investigation of a method for predicting AUV derivatives , 2008 .

[17]  John J. Leonard,et al.  Cooperative Localization for Autonomous Underwater Vehicles , 2009, Int. J. Robotics Res..

[18]  Benedetto Allotta,et al.  An Attitude Estimation Algorithm for Mobile Robots Under Unknown Magnetic Disturbances , 2016, IEEE/ASME Transactions on Mechatronics.

[19]  Joao Alves,et al.  An application of distributed long baseline — Node ranging in an underwater network , 2014, 2014 Underwater Communications and Networking (UComms).

[20]  Thia Kirubarajan,et al.  Estimation with Applications to Tracking and Navigation: Theory, Algorithms and Software , 2001 .