Mission Oriented Operating Suite Research Articles

Design and Implementation of Autonomous Underwater Vehicle Simulation System Based on MOOS and Unreal Engine

An effective autonomous underwater vehicle (AUV) simulation system can greatly improve development efficiency and reduce the cost and risk of actual equipment operation. In this paper, a comprehensive simulation system is developed using Mission Oriented Operating Suite (MOOS) and Unreal Engine 4 (UE4). The former provides an open-source development framework and application components, which are widely used in the field of underwater robots. The latter is a well-known game development engine that has realistic effects and various plugins. As far as we know, there are few simulation systems based on MOOS and UE4. Moreover, a modular architecture for the simulation system is designed and implemented in the paper. The developed system consists of four subsystems, including the simulation editing and controlling subsystem, shore-based operation subsystem, simulation engine subsystem, and three-dimensional (3D) visualization subsystem. These subsystems have modular characteristics and independent functions and communicate with each other through network sockets. Through the system, users can customize simulation scenarios, send missions and control simulation progress from the graphic user interface. And the system can be used in operation training, software testing, algorithm verification of AUV, etc.

Deep Learning-Based Trajectory Tracking Control forUnmanned Surface Vehicle

Trajectory tracking control based on waypoint behavior is a promising way for unmanned surface vehicle (USV) to achieve autonomous navigation. This study is aimed at the guidance progress in the kinematics; the artificial intelligence method of deep learning is adopted to improve the trajectory tracking level of USV. First, two deep neural network (DNN) models are constructed to evaluate navigation effects and to estimate guidance law parameters in real time, respectively. We then pretrain the DNN using a Gaussian–Bernoulli restricted Boltzmann machine to further improve the accuracy of predicting navigation effect. Finally, two DNNs are connected in parallel with the control loop of USV to provide predictive supervision and auxiliary decision making for traditional control methods. This kind of parallel way conforms to the ship manipulation of habit. Furthermore, we develop a new application on the basis of Mission Oriented Operating Suite Interval Programming named “pDeepLearning.” It can predict the navigation effect online by DNN and adjust the guidance law parameters according to the effect level. The experimental results show that, compared with the original waypoint behavior of USV, the prediction model proposed in this study reduces the trajectory tracking error by 19.0% and increases the waypoint behavior effect level.

Research on Synergy Pursuit Strategy of Multiple Underwater Robots

This paper presents a synergy pursuit strategy that multiple underwater robots pursue a single moving target based on finite state machine. The processes of the pursuit are defined as seven different states, and to implement each state, the corresponding strategies are designed. As the strategy for each state is implemented by a corresponding formation control, a synergy control law is also designed for multiple underwater robots. In the design of the pursuit strategy, the definition of encirclement is put forward for the underwater robots. Furthermore, the proof that a point is encircled by other points on the plane is given. To solve the problem of the concealment in the tracking and the pursuit, a semicircular pursuit strategy and a circular pursuit strategy are also proposed. Finally, based on this pursuit strategy, the simulation of whole process is carried out with the MOOS(Mission Oriented Operating Suite) platform, and the effectiveness of the semicircular and circular pursuit strategy are verified by lake experiment with practical robots. The results of simulation and lake experiment prove that this pursuit strategy can realize synergy tracking and pursuit for a single moving target under the given conditions.

Communication and Collaboration Among Heterogeneous Unmanned Systems Using SAE JAUS Standard Formats and Protocols

The Naval Undersea Warfare Center Division Newport (NUWCDIVNPT) and Georgia Tech Research Institute (GTRI) completed a successful at-sea exercise with autonomous UAS and UUV systems demonstrating communication and collaboration. The exercise represented for the first time the use of standard protocols and formats that effectively support cross-domain unmanned system operations. Four man-portable Iver2 UUVs operating in coordinated missions autonomously collected environmental data, which was compressed in-stride, re-formatted, and exfiltrated via UAS relay for display and tactical decision making. Two UAS with autonomous flight take-off and mission execution were sequenced to serve as ISR platforms and to support communications as RF relays for the UUVs performing Intelligence Preparation of the Environment missions. Two Command and Control nodes ashore provided unmanned system tasking and re-tasking, and they served to host and display both geo-positional data and status for UAS and UUV vehicles during the operational scenarios run during the exercise. The SAE Joint Architecture for Unmanned Systems (JAUS) standards were used for all message traffic between shore-based C2 nodes, UAS, and UUVs active in the exercise area. Development for this project highlighted both the strengths and shortfalls of JAUS and captured the requirements for moving forward in effective cross-domain communications that support distributed, agile C2 nodes to meet evolving CONOPS for growing unmanned system presence and mission roles. The JAUS architecture was introduced to the NUWC and GTRI unmanned systems though an instantiation of the Mission Oriented Operating Suite (MOOS) autonomy framework on secondary CPUs integrated into the Iver2 UUVs and the GTRI UAS. This work represents a critical step in communications for networking of heterogeneous unmanned systems and establishes a solid platform for alignment of development and ongoing programs.

Real time simulation of element level time series for active sonars in deep ocean environment

The simulation of experiments in deep ocean environments is becoming increasingly important to researches due to expensive and complex modern equipment. Accurate simulations allow for more efficient use of ship time. LAMSS (Laboratory for Autonomous Marine Sensing Systems) at MIT has developed an indispensable tool for simulating real time active sonar experiments using a combination of ray tracing software (Bellhop), MATLAB, and MOOS-IvP (Mission Oriented Operating Suite - Interval Programming). A new key component to this toolbox is a module that models surface reverberation. Experiments in deep ocean environments are subject to environmental effects, such as the scattering of acoustic ray bundles on the ocean boundary due to upward refraction. Therefore, modeling surface reverberation is essential in deep ocean simulations when identifying target signatures in real time through active sonar. The implementation of this model is intended to simulate deep ocean active sonar experiments more accurately, thus optimizing on site data collection and evaluation.

Development of a Flexible Command and Control Software Architecture for Marine Robotic Applications

AbstractThis paper reports the implementation of a supervisory control framework and modular software architecture built around the lightweight communication and marshalling (LCM) publish/subscribe message passing system. In particular, we examine two diverse marine robotics applications using this modular system: (i) the development of an unmanned port security vehicle, a robotic surface platform to support first responders reacting to transportation security incidents in harbor environments, and (ii) the adaptation of a commercial off-the-shelf autonomous underwater vehicle (the Ocean-Server Iver2) for visual feature-based navigation. In both cases, the modular vehicle software infrastructures are based around the open-source LCM software library for low-latency, real-time message passing. To elucidate the real-world application of LCM in marine robotic systems, we present the software architecture of these two successful marine robotic applications and illustrate the capabilities and flexibilities of this approach to real-time marine robotics. We present benchmarking test results comparing the throughput of LCM with the Mission-Oriented Operating Suite, another robot software system popular in marine robotics. Experimental results demonstrate the capacity of the LCM framework to make large amounts of actionable information available to the operator and to allow for distributed supervisory control. We also provide a discussion of the qualitative tradeoffs involved in selecting software infrastructure for supervisory control.