Unmanned surface vehicles, 15 years of development

Manley, Justin

doi:10.1109/oceans.2008.5152052

Cited by 243 publications

(130 citation statements)

References 9 publications

Supporting

Mentioning

112

Contrasting

Unclassified

Order By: Relevance

“…Whilst COLREGS were made for ships operated by a crew, their key elements are also applicable for automatic collision avoidance systems, either as decision support systems for the crew or in autonomously operated and unmanned ships [2], [3], [4]. In an autonomous system implementation, COLREGS implicitly impose requirements on the information that must be provided by sensor systems, and the correct actions that should occur in hazardous situations.…”

Section: A Backgroundmentioning

confidence: 99%

Ship Collision Avoidance and COLREGS Compliance Using Simulation-Based Control Behavior Selection With Predictive Hazard Assessment

Johansen

Pérez

Cristofaro

2016

IEEE Trans. Intell. Transport. Syst.

259

224

View full text Add to dashboard Cite

Abstract-This paper describes a concept for a collision avoidance system for ships, based on model predictive control. A finite set of alternative control behaviors are generated by varying two parameters: offsets to the guidance course angle commanded to the autopilot, and changes to the propulsion command ranging from nominal speed to full reverse. Using simulated predictions of the trajectories of the obstacles and ship, the compliance with COLREGS and collision hazards associated with each of the alternative control behaviors are evaluated on a finite prediction horizon, and the optimal control behavior is selected. Robustness to sensing error, predicted obstacle behavior, and environmental conditions can be ensured by evaluating multiple scenarios for each control behavior. The method is conceptually and computationally simple and yet quite versatile as it can account for the dynamics of the ship, the dynamics of the steering and propulsion system, forces due to wind and ocean current, and any number of obstacles. Simulations show that the method is effective and can manage complex scenarios with multiple dynamic obstacles and uncertainty associated with sensors and predictions.

show abstract

Section: A Backgroundmentioning

confidence: 99%

Ship Collision Avoidance and COLREGS Compliance Using Simulation-Based Control Behavior Selection With Predictive Hazard Assessment

Johansen

Pérez

Cristofaro

2016

IEEE Trans. Intell. Transport. Syst.

259

224

View full text Add to dashboard Cite

show abstract

“…The interconnection of these systems has the potential to allow for holistic traffic management and the use as a service of the data generated by the vehicle. This trend is not only limited to vehicles however, ships [36] and aerial vehicles [37] are also being automated for similar tasks.…”

Section: B Autonomous Vehiclesmentioning

confidence: 99%

Massive-Scale Automation in Cyber-Physical Systems: Vision & Challenges

McKee

Clement

Almutairi

et al. 2017

2017 IEEE 13th International Symposium on Autonomous Decentralized System (ISADS)

View full text Add to dashboard Cite

Abstract-The next era of computing is the evolution of the Internet of Things (IoT) and Smart Cities with development of the Internet of Simulation (IoS). The existing technologies of Cloud, Edge, and Fog computing as well as HPC being applied to the domains of Big Data and deep learning are not adequate to handle the scale and complexity of the systems required to facilitate a fully integrated and automated smart city. This integration of existing systems will create an explosion of data streams at a scale not yet experienced. The additional data can be combined with simulations as services (SIMaaS) to provide a shared model of reality across all integrated systems, things, devices, and individuals within the city. There are also numerous challenges in managing the security and safety of the integrated systems. This paper presents an overview of the existing stateof-the-art in automating, augmenting, and integrating systems across the domains of smart cities, autonomous vehicles, energy efficiency, smart manufacturing in Industry 4.0, and healthcare. Additionally the key challenges relating to Big Data, a model of reality, augmentation of systems, computation, and security are examined.

show abstract

“…The development of Autonomous Surface Crafts (ASC), such as our MARE platform, have been mostly restricted to research domains, as opposed to the wide-spread commer-cialization of Autonomous Underwater Vehicles (AUV) [4]. This trend however has been changing recently with the increasing scope of applications that are possible due to the collaboration of ASCs with AUVs.…”

Section: Related Workmentioning

confidence: 99%

“…Finally, a detailed study on the design developments of ASCs over the last 15 years is provided in [4].…”

Section: Related Workmentioning

confidence: 99%

MARE: Marine Autonomous Robotic Explorer

Girdhar

Dey

et al. 2011

2011 IEEE/RSJ International Conference on Intelligent Robots and Systems

View full text Add to dashboard Cite

Abstract-We present MARE, an autonomous airboat robot that is suitable for exploration-oriented tasks, such as inspection of coral reefs and shallow seabeds. The combination of this platform's particular mechanical properties and its powerful software framework enables it to function in a multitude of potential capacities, including autonomous surveillance, mapping, and search operations. In this paper we describe two different exploration strategies and their implementation using the MARE platform. First, we discuss the application of an efficient coverage algorithm, for the purpose of achieving systematic exploration of a known and bounded environment. Second, we present an exploration strategy driven by surprise, which steers the robot on a path that might lead to potentially surprising observations.

show abstract

Unmanned surface vehicles, 15 years of development

Cited by 243 publications

References 9 publications

Ship Collision Avoidance and COLREGS Compliance Using Simulation-Based Control Behavior Selection With Predictive Hazard Assessment

Ship Collision Avoidance and COLREGS Compliance Using Simulation-Based Control Behavior Selection With Predictive Hazard Assessment

Massive-Scale Automation in Cyber-Physical Systems: Vision & Challenges

MARE: Marine Autonomous Robotic Explorer

Contact Info

Product

Resources

About