A non-myopic, receding horizon control strategy for an AUV to track an underwater target in a bistatic sonar scenario

Goldhahn

LePage

2015

OCEANS 2015 - Genova

Self Cite

We present an adaptive, data driven Mission Management Layer (MML) to manage the phases (surveillance, track prosecution and target reacquisition) of the mission of AUVs operating as receiver nodes in a multistatic network for littoral surveillance. Among the tracks produced by the on board tracker, the MML selects those which are likely originated by a target. The MML then issues commands to the vehicle Control Layer to trigger data-driven optimization behaviours to prosecute these candidate tracks.Selecting few candidate tracks is indeed crucial since the addressed scenario usually presents many tracks hence resulting challenging from the tracking point of view. To select the candidate tracks, a metric is introduced to quantify their quality. It is based on the kinematic features of the target, on an acoustic model and on the quality of measurement-totrack associations. By selecting a limited subset of produced tracks, the MML can improve the benefits of using datadriven behaviours activating them only on interesting cues and reducing the time wasted to optimize tracks not related to a target. This aims at achieving a balance between the surveillance of the area of interest and exploitation of target cues (tracks). These features are essential for improving the overall mission performance and for an effective AUV decision making in realistic conditions. We present results from sea trials demonstrating the effectiveness of our approach and how the proposed MML can represent a step forward towards the full autonomy of our system. These results represent one of the first examples of AUVs autonomously taking decisions in a realistic and complex littoral surveillance scenario.

Section: E Mission Manager Layer: Descriptionmentioning

confidence: 99%

Section: E Mission Manager Layer: Descriptionmentioning

confidence: 99%

Section: B Track Scoringmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Towards fully autonomous underwater vehicles in ASW scenarios: An adaptive, data driven AUV mission management layer

Goldhahn

LePage

2015

OCEANS 2015 - Genova

Self Cite

An Acoustic Network Navigation System

Munafó

Journal of Field Robotics

2017

Self Cite

This work describes a system for acoustic‐based navigation that relies on the addition of localization services to underwater networks. The localization capability has been added on top of an existing network, without imposing constraints on its structure/operation. The approach is based on the inclusion of timing information within acoustic messages through which it is possible to know the time of an acoustic transmission in relation to its reception. Exploiting such information at the network application level makes it possible to create an interrogation scheme similar to that of a long baseline. The advantage is that the nodes/autonomous underwater vehicles (AUVs) themselves become the transponders of a network baseline, and hence there is no need for dedicated instrumentation. The paper reports at sea results obtained from the COLLAB–NGAS14 experimental campaign. During the sea trial, the approach was implemented within an operational network in different configurations to support the navigation of the two Centre for Maritime Research and Experimentation Ocean Explorer (CMRE OEX) vehicles. The obtained results demonstrate that it is possible to support AUV navigation without constraining the network design and with a minimum communication overhead. Alternative solutions (e.g., synchronized clocks or two‐way‐travel‐time interrogations) might provide higher precision or accuracy, but they come at the cost of impacting on the network design and/or on the interrogation strategies. Results are discussed, and the performance achieved at sea demonstrates the viability to use the system in real, large‐scale operations involving multiple AUVs. These results represent a step toward location‐aware underwater networks that are able to provide node localization as a service.

Cooperative robotic networks for underwater surveillance: an overview

Munafó

Teseï

et al. 2017

IET Radar Sonar & Navi

Self Cite

120

Underwater surveillance has traditionally been carried out by means of surface and undersea manned vessels equipped with advanced sensor systems. This approach is often costly and manpower intensive. Marine robotics is an emerging technological area that enables the development of advanced networks for underwater surveillance applications. In contrast with the use of standard assets, these advanced networks are typically composed of small, low-power, and possibly mobile robots, which have limited endurance, processing and wireless communication capabilities. When deployed in a region of interest, these robots can cooperatively form an intelligent network achieving high performance with significant features of scalability, adaptability, robustness, persistence and reliability. Such networks of robots can be the enabling technology for a wide range of applications in the maritime domain. However, they also introduce new challenges for underwater distributed sensing, data processing and analysis, autonomy and communications. The main thrust of this study is to review the underwater surveillance scenario within a framework of four research areas: (i) underwater robotics, (ii) acoustic signal processing, (iii) tracking and distributed information fusion, and (iv) underwater communications networks. Progress in each of these areas as well as future challenges is presented.