Autonomous Underwater Robotics for Mapping, Monitoring, İntervening with, and Tracking Dynamic Events and Targets
A special issue of Journal of Marine Science and Engineering (ISSN 2077-1312).
Deadline for manuscript submissions: closed (31 May 2016) | Viewed by 9461
Special Issue Editor
Special Issue Information
Dear Colleagues,
Autonomous Underwater Vehicles (AUVs) have matured as a technology to the point where they have become commercially available and are now being employed by government agencies and private companies. These off-the-shelf robot systems can be deployed to reliably follow preset paths and collect geo-referenced sensor measurements of environment variables on missions that last from hours to months. Pushing the boundaries of this technology, researchers have recently been developing the technology necessary for underwater robots to react to sensor measurements in situ, allowing them to make real-time decisions for optimal control and path planning. These developments are making it possible for underwater robots to react to dynamic events, re-plan on-the-fly, and track moving targets.
This Special Issue is launched to provide a compilation of current state-of-the-art and future perspectives in underwater robot technology development, with a focus on its use in handling dynamic events and targets. We invite researchers to submit recent unpublished findings on the topics of underwater robot control, state estimation, localization, artificial intelligence, mapping, path planning, sensors, propulsion, robot hardware design, multi-robot systems, applications, and autonomous navigation as they relate to underwater robots and their use for mapping, monitoring, intervening with, and tracking dynamic events and targets.
Prof. Dr. Christopher Clark
Guest Editor
Manuscript Submission Information
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Keywords
- Autonomous Underwater Vehicles
- Multi-Robot Systems
- SLAM
- Acoustic Communication
- AUV Propulsion
- Motion planning and Control
- Modeling and Prediction of Dynamic and Uncertain Environments
- Online Learning
- Distributed Control
- Applications in Field Robotics
- Localization
- Novel Testbeds, Actuators and Sensors
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