Development of a real-time control architecture for a semi-autonomous underwater vehicle for intervention missions

The need for autonomous underwater vehicles (AUVs) for intervention missions becomes greater as they can perform underwater tasks requiring physical contacts with the underwater environment, such as underwater plug-in/plug-out, construction and repair, cable streaming, mine hunting, munitions retrieval, and scientific sampling. This paper describes a semi-autonomous underwater vehicle for intervention missions that has multiple on-board CPUs, redundant sensors and actuators, on-board power source and a robotic manipulator for dextrous underwater performance. Such a complex robotic vehicle system requires advanced control software architecture for on-board intelligence with a wide range of sensors and actuators to carry out required missions. In this paper, AUV control architectures are reviewed and a sensor data bus based control architecture (SDBCA) is presented. SDBCA is a modified hierarchical architecture that offers good controllability and stability while sensor data bus increases flexibility of system design, making it possible to have a prompt response from high-level control with respect to low-level sensor data. The overall sensor input mechanism of SDBCA becomes similar to the sensor input mechanism of subsumption architecture.     

Semi‐decentralized nonlinear cooperative control strategies for a network of heterogeneous autonomous underwater vehicles

In this paper, we develop nonlinear distributed or semi‐decentralized cooperative control schemes for a team of heterogeneous autonomous underwater vehicles (AUVs). The objective is to have the network of AUVs follow a desired trajectory, while the agents maintain a desired formation when there is a virtual leader whose position information is only available and known to a very small subset of the agents. The virtual leader does not receive any feedback and information from the other agents and the agents only communicate with their nearest neighboring agents. It is assumed that the model parameters associated with each vehicle/agent is different, although the order of the agents is the same. The developed and proposed nonlinear distributed cooperative control schemes are based on the dynamic surface control methodology for a network of heterogeneous autonomous vehicles with uncertainties. The development and investigation of the dynamic surface control methodology for a team of cooperative heterogenous multi‐agent nonlinear systems is accomplished for the first time in the literature. Simulation results corresponding to a team of six AUVs are provided to demonstrate and illustrate the advantages and superiority of our proposed cooperative control strategies as compared to the methods that are available in the literature. Copyright © 2016 John Wiley & Sons, Ltd.     

Optimal hybrid fault recovery in a team of unmanned aerial vehicles

This paper introduces and develops an optimal hybrid fault recovery methodology for a team of unmanned vehicles by taking advantage of the cooperative nature of the team to accomplish the desired mission requirements in presence of faults/failures. The proposed methodology is developed in a hybrid framework that consists of a low-level (an agent level and a team level) and a high-level (discrete-event system level) fault diagnosis and recovery modules. A high-level fault recovery scheme is proposed within the discrete-event system (DES) supervisory control framework, whereas it is assumed that a low-level fault recovery designed based on classical control techniques is already available. The low-level recovery module employs information on the detected and estimated fault and modifies the controller parameters to recover the team from the faulty condition. By taking advantage of combinatorial optimization techniques, a novel reconfiguration strategy is proposed and developed at the high-level so that the faulty vehicles are recovered with minimum cost to the team. A case study is provided to illustrate and demonstrate the effectiveness of our proposed approach for the icing problem in unmanned aerial vehicles, which is a well-known structural problem in the aircraft industry.     

Review of mission planning for autonomous marine vehicle fleets

The deployment of a fleet of autonomous marine vehicles (AMVs) allows for the parallelisation of missions, intervehicle support for longer deployment times, adaptability and redundancy to in situ mission changes, and effective use of the right vehicle for the right purpose. End users and operators of AMVs face challenges in planning complex missions due to the limitations of their vehicles, dynamic, operationally constrictive, and unstructured environments, and in minimising risks to equipment, the mission, and personnel. Automated mission planning for AMV fleets can be a tool to reduce the complexity of programming vehicle tasking, and to perform validity assessments for end user‐specified goals, allowing the operator to focus on risk assessment. We present a critical review of the current advances in automated planning for AMV fleets, investigating the limitations of available state‐of‐the‐art tools and providing a road map of the goals and challenges based on analysis of field reports and end user initiatives.     

Cooperative bathymetry-based localization using low-cost autonomous underwater vehicles

We present a cooperative bathymetry-based localization approach for a team of low-cost autonomous underwater vehicles (AUVs), each equipped only with a single-beam altimeter, a depth sensor and an acoustic modem. The localization of the individual AUV is achieved via fully decentralized particle filtering, with the local filter’s measurement model driven by the AUV’s altimeter measurements and ranging information obtained through inter-vehicle communication. We perform empirical analysis on the factors that affect the filter performance. Simulation studies using randomly generated trajectories as well as trajectories executed by the AUVs during field experiments successfully demonstrate the feasibility of the technique. The proposed cooperative localization technique has the potential to prolong AUV mission time, and thus open the door for long-term autonomy underwater.     

Virtual motion camouflage based phantom track generation through cooperative electronic combat air vehicles

As an example of complex cooperative missions, coherent phantom track generation through controlling multiple electronic combat air vehicles is currently an area of great interest to the defense agency for the purpose of deceiving a radar network. However, it has been a challenge to design the optimal or even feasible coherent trajectories for this type of problem due to the high dimensionality and the strong coupling between the phantom and actual vehicles. This problem becomes even more difficult to solve when realistic kinematic, dynamics, and geometric constraints in a three-degree-of-freedom formation have to be considered. This paper describes how an interesting bio-inspired motion strategy can be used to design real-time trajectories for a (1) feasible constant speed coherent mission, (2) maximum-duration constant speed coherent mission, and (3) optimal trajectory mission for general cases. The proposed method will dramatically reduce the dimension of the problem and thus real-time optimal trajectory design can be achieved. Also the fact that fewer equality constraints are involved in solving the formulated nonlinear programming will make the convergence a lot easier.     

Model-driven design space exploration for multi-robot systems in simulation

Multi-robot systems are increasingly deployed to provide services and accomplish missions whose complexity or cost is too high for a single robot to achieve on its own. Although multi-robot systems offer increased reliability via redundancy and enable the execution of more challenging missions, engineering these systems is very complex. This complexity affects not only the architecture modelling of the robotic team but also the modelling and analysis of the collaborative intelligence enabling the team to complete its mission. Existing approaches for the development of multi-robot applications do not provide a systematic mechanism for capturing these aspects and assessing the robustness of multi-robot systems. We address this gap by introducing ATLAS, a novel model-driven approach supporting the systematic design space exploration and robustness analysis of multi-robot systems in simulation. The ATLAS domain-specific language enables modelling the architecture of the robotic team and its mission and facilitates the specification of the team’s intelligence. We evaluate ATLAS and demonstrate its effectiveness in three simulated case studies: a healthcare Turtlebot-based mission and two unmanned underwater vehicle missions developed using the Gazebo/ROS and MOOS-IvP robotic platforms, respectively.

     

Decentralized planning and control for UAV–UGV cooperative teams

In this paper we study a symbiotic aerial vehicle-ground vehicle robotic team where unmanned aerial vehicles (UAVs) are used for aerial manipulation tasks, while unmanned ground vehicles (UGVs) aid and assist them. UGV can provide a UAV with a safe landing area and transport it across large distances, while UAV can provide an additional degree of freedom for the UGV, enabling it to negotiate obstacles. We propose an overall system control framework that includes high-accuracy motion planning for each individual robot and ad-hoc decentralized mission planning for complex missions. Experimental results obtained in a mockup arena for parcel transportation scenario show that the system is able to plan and execute missions in various environments and that the obtained plans result in lower energy consumption.     

智能海洋机器人技术进展

智能海洋机器人是可以在复杂海洋环境中执行各种任务的智能化无人平台, 包括智能水下机器人和智能水面机器人. 基于实践和在相关技术难题上的经验, 提出了一些关键技术问题的解决方案. 在智能水下机器人方面, 探讨了体系结构、运动控制、智能规划与决策和系统仿真等关键技术. 在智能水面机器人方面, 探讨了快速性和智能化问题. 我国在智能海洋机器人技术研究方面已经取得了较大的进步, 但距离全面应用还有很大差距.     

Autonomous underwater vehicles: Hybrid control of mission and motion

This paper provides an experimental implementation and verification of a hybrid (mixed discrete state/ continuous state) controller for semi-autonomous and autonomous underwater vehicles in which the missions imply multiple task robot behavior. An overview of some of the missions being considered for this rapidly developing technology is mentioned including environmental monitoring, underwater inspection, geological survey as well as military missions in mine countermeasures.The functionalities required of such vehicles and their relation to intelligent control technology is discussed. In particular, the use of Prolog as a computer language for the specification of the discrete event system (DES) aspects of the mission control is proposed. The connections between a Prolog specification and the more common Petri Net graphical representation of a DES are made. Links are made between activation commands, transitioning signals, and the continuous state dynamic control system (DCS) responsible for vehicle stabilization.Details are given of the NPS Phoenix vehicle implementation at the present time, together with experimental validation of the concepts outlined using a simplified example mission. The paper ends with a listing of questions and concerns for the evaluation of software controllers. A list of references is given for readers interested in this subject.     

Redundant manipulator techniques for partially decentralized path planning and control of a platoon of autonomous vehicles.

An approach to real-time trajectory generation for platoons of autonomous vehicles is developed from well-known control techniques for redundant robotic manipulators. The partially decentralized structure of this approach permits each vehicle to independently compute its trajectory in real-time using only locally generated information and low-bandwidth feedback generated by a system exogenous to the platoon. Our work is motivated by applications for which communications bandwidth is severely limited, such for platoons of autonomous underwater vehicles. The communication requirements for our trajectory generation approach are independent of the number of vehicles in the platoon, enabling platoons composed of a large number of vehicles to be coordinated despite limited communication bandwidth.     

Simultaneous sensor selection and routing of unmanned aerial vehicles for complex mission plans

Military reconnaissance missions often employ a set of unmanned aerial vehicles (UAVs) equipped with sensors to gather intelligence information from a set of known targets. UAVs are limited by the number of sensors they can hold; also attaching a sensor adds weight to the aircraft which in turn reduces the flight time available during a mission. The task of optimally assigning sensors to UAVs and routing them through a target field to maximize intelligence gain is a generalization of the team orienteering problem studied in the vehicle routing literature. This work presents a mathematical programming model for simultaneous sensor selection and routing of UAVs, which solves optimally using CPLEX for simple missions. Larger missions required the development of three heuristics, which were augmented by Column Generation. Results from a performance study indicated that the heuristics quickly found good solutions. Column Generation improved the solution in many instances, with minimal impact on overall solution time. The rapid nature of the overall solution approach allows it to be used in other mission planning tasks. A fleet sizing application is discussed as an example of its flexible usage.     

Cooperative line of sight target tracking for heterogeneous unmanned marine vehicle teams: From theory to practice

In this paper we present the principle of Cooperative Line Of Sight Target Tracking (CLOSTT) for Heterogeneous Unmanned Marine Vehicle Teams. Thereby CLOSTT is part of a control architecture developed to coordinate existing single heterogeneous autonomous marine vehicles as a team. Within this control architecture CLOSTT separately offers a solution to the task of following a moving underwater target with a team of unmanned marine vehicles.     

Experimental tests of autonomous ground vehicles with preview

This paper describes the design and experimental tests of a path planning and reference tracking algorithm for autonomous ground vehicles. The ground vehicles under consideration are equipped with forward looking sensors that provide a preview capability over a certain horizon. A two-level control framework is proposed for real-time implementation of the model predictive control(MPC)algorithm, where the high-level performs on-line optimization to generate the best possible local reference respect to various constraints and the low-level commands the vehicle to follow realistic trajectories generated by the high-level controller. The proposed control scheme is implemented on an indoor testbed through networks with satisfactory performance.     

Robot-Assisted Bridge Inspection

The Center for Robot-Assisted Search and Rescue (CRASAR®) deployed a customized AEOS man-portable unmanned surface vehicle and two commercially available underwater vehicles (the autonomous YSI EcoMapper and the tethered VideoRay) for inspection of the Rollover Pass bridge in the Bolivar peninsula of Texas in the aftermath of Hurricane Ike. A preliminary domain analysis with the vehicles identified key tasks in subsurface bridge inspection (mapping of the debris field and inspecting the bridge footings for scour), control challenges (navigation under loss of GPS, underwater obstacle avoidance, and stable positioning in high currents without GPS), possible improvements to human-robot interaction (having additional display units so that mission specialists can view and operate on imagery independently of the operator control unit, incorporating 2-way audio to allow operator and field personnel to communicate while launching or recovering the vehicle, and increased state sensing for reliability), and discussed the cooperative use of surface, underwater, and aerial vehicles. The article posits seven milestones in the development of a fully functional UMV for bridge inspection: standardize mission payloads, add health monitoring, improve teleoperation through better human-robot interaction, add 3D obstacle avoidance, improve station-keeping, handle large data sets, and support cooperative sensing.     

RT2: real-time ray-tracing for underwater range evaluation

The paper deals with the distributed acoustic localization of teams of autonomous underwater vehicles (AUVs) and proposes a novel algorithm, real-time ray-tracing (RT²), for evaluating the distance between any pair of AUVs in the team. The technique, based on a modified formulation of the non-linear sound-ray propagation laws, allows efficient handling of the distorted and reflected acoustic ray paths. The proposed algorithm can be easily implemented on-board of low-cost AUVs, requiring the presence, on each vehicle, of an acoustic modem and a pair of look-up tables, a-priori built on the basis of the assumed knowledge of the depth-dependent sound velocity profile. On such a basis, every AUV can compute its distance w.r.t. to any other neighbor team member, through time-of-flight measurements and the exchanges of depth information only.     

Cooperative formation control of autonomous underwater vehicles: An overview

Formation control is a cooperative control concept in which multiple autonomous underwater mobile robots are deployed for a group motion and/or control mission. This paper presents a brief review on various cooperative search and formation control strategies for multiple autonomous underwater vehicles (AUV) based on literature reported till date. Various cooperative and formation control schemes for collecting huge amount of data based on formation regulation control and formation tracking control are discussed. To address the challenge of detecting AUV failure in the fleet, communication issues, collision and obstacle avoidance are also taken into attention. Stability analysis of the feasible formation is also presented. This paper may be intended to serve as a convenient reference for the further research on formation control of multiple underwater mobile robots.     

Autonomous UAV path planning and estimation

Unmanned aerial vehicles (UAVs) have shown promise in recent years for autonomous sensing. UAVs systems have been proposed for a wide range of applications such as mapping, surveillance, search, and tracking operations. The recent availability of low-cost UAVs suggests the use of teams of vehicles to perform sensing tasks. To leverage the capabilities of a team of vehicles, efficient methods of decentralized sensing and cooperative path planning are necessary. The goal of this work is to examine practical control strategies for a team of fixed-wing vehicles performing cooperative sensing. We seek to develop decentralized, autonomous control strategies that can account for a wide variety of sensing missions. Sensing goals are posed from an information theoretic standpoint to design strategies that explicitly minimize uncertainty. This work proposes a tightly coupled approach, in which sensor models and estimation objectives are used online for path planning.     

Improving the coordination efficiency of limited‐communication multi–autonomus underwater vehicle operations using a multiagent architecture

This research addresses the problem of coordinating multiple autonomous underwater vehicle (AUV) operations. An intelligent mission executive has been created that uses multiagent technology to control and coordinate multiple AUVs in communication‐deficient environments. By incorporating real‐time vehicle prediction, blackboard‐based hierarchical mission plans, mission optimization, and a distributed multiagent–based paradigm in conjunction with a simple broadcast communication system, this research aims to handle the limitations inherent in underwater operations, namely poor communication, and intelligently control multiple vehicles. In this research, efficiency is evaluated and then compared to the current state of the art in multiple AUV control. The research is then validated in real AUV coordination trials. Results will show that compared to the state of the art, the control system developed and implemented in this research coordinates multiple vehicles more efficiently and is able to function in a range of poor communication environments. These findings are supported by in‐water validation trials with heterogeneous AUVs. © 2010 Wiley Periodicals, Inc.     

MARIUS: an autonomous underwater vehicle for coastal oceanography

An autonomous underwater vehicle (AW), named MARIUS, has been developed under the MAST Programme of the Commission of the European Communities. The primary envisioned missions of the prototype AW are environmental surveying and oceanographic data acquisition in coastal waters. The authors describe the design and implementation of the AW systems for vehicle and mission control, and report the results of the sea trials conducted with the vehicle in Sines, Portugal